Why there are so many problems with streamlining data strategy ? What are the major problems ? How do you solve them ?
Using an approach based on Agile and Lean Concepts to achieve the goal of actionable data & analytics
Data Strategy - Executive MBA Class, IE Business SchoolGam Dias
For today's enterprise Data is now very much a corporate asset, vital to delivering products and services efficiently and cost effectively. There are few organizations that can survive without harnessing data in some way.
Viewed as a strategic asset, data can be a source of new internal efficiencies, improved competitive advantage or a source of entirely new products that can be targeted at your existing or new customers.
This slide deck contains the highlights of a one day course on Data Strategy taught as part of the Executive MBA Program at IE Business School in Madrid.
3 Steps to Becoming a Successful Chief Data OfficerMario Faria
Presentation delivered at the Enteprise Data Leadership Summit, in Chicago March-2014
Mario Faria, Head of Chief Data Officer, Inc., a consulting and advisory services company, based in Seattle, WA
Increasing Your Business Data & Analytics MaturityMario Faria
Slides of the webinar presented July 10th. The audio can be accessed at : http://www.dataversity.net/webinar-increasing-business-data-analytics-maturity-2/
The Chief Data Officer - quotes from data & analytics thought leadersMario Faria
Data & Analytics have become so important on how business are differentiating themselves in the marketplace. With the help from the most well recognized data leaders of our time, I have put together their thoughts in this material. By sharing our thinking, we want companies to understand what it takes to become a data-driven organization.
The Chief Data Officer Golden Rules to Data Quality and Data Governance SuccessMario Faria
This document summarizes a webinar presented by Mario Faria on establishing successful data quality and governance programs. Faria outlines five "golden rules" for chief data officers: 1) understand why quality and governance matters to the business, 2) define a strategic vision and plan, 3) select a strong leader, 4) secure necessary investments and budget, and 5) consistently deliver results. He emphasizes the importance of a customer-focused mindset for quality and seeing governance as a process for decision making. Faria also discusses establishing baselines, adopting agile methodologies, celebrating successes, and adapting quickly. The webinar provides best practices for CDOs implementing quality and governance programs.
Noise to Signal - The Biggest Problem in DataDATAVERSITY
Our ability to produce, ingest and store data has grown exponentially, but our ability to parse out insights from data has not. In the 90s, an organization’s data would live in a data warehouse with an ETL pipeline and one reporting layer on top. Information was well controlled if not somewhat limited in breadth and slow to trickle down. Now with the onset of self-service analytics, anyone can create a report and an insight and there are many different sources of “truth.” For example, a seemingly straightforward question like "how many customers do we have?" will likely return difference answers from sales, finance and customer success, depending on their definitions and the data at hand. There is simply too much data (and duplicate data), too many tools, and too many systems storing data -- leading to time consuming searches, confusion and a lack of trust. Hear Stephanie discuss how a data catalog can help solve the noise to signal problem - making information easier to find, easier to understand and more trustworthy. She will describe how organizations like Safeway, Albertsons, Munich Re and Pfizer leverage a data catalog to find data and collaborate on data, gain a fuller understanding of its meaning and ultimately, solve important problems.
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
In many organizations and functional areas, data has pulled even with money in terms of what makes the proverbial world go round. As businesses struggle to cope with the 21st century’s newfound data flood, it is more important than ever before to prioritize data as an asset that directly supports business imperatives. However, while organizations across most industries make some attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. Data Quality), the results of these efforts frequently fall far below expectations. At the root of many of these failures is poor organizational Data Management—which fortunately is a remediable problem.
This webinar will cover three lessons, each illustrated with examples, that will help you establish realistic goals and benchmarks for Data Management processes and communicate their value to both internal and external decision-makers:
How organizational thinking must change to include value-added Data Management practices
The importance of walking before you run with data-focused initiatives
Prioritizing specification and Data Governance over “silver bullet” analytical tools
Discuss foundational data-centric concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
7 Pillars Of Data Strategy - High Five 2018Evan Levy
Evan Levy, Director of Advertising at Method Savvy, discusses 7 pillars of a successful data strategy: 1) Asking the right questions, 2) Technical implementation, 3) Users, 4) Data storage and structure, 5) Security, 6) Handling personally identifiable information, and 7) Visualization and analysis needs. He emphasizes starting with specific, action-oriented questions and considering your audience when visualizing data. Following these pillars will help companies get the most value from their data through proper analysis and decision making.
This framework helps organizations align Data Strategy with Business Strategy to prioritize goals around the most pressing operational needs. It introduces Data Management & Data Ability Maturity Matrix to visualize the core path of business digital transformation, which is easy to understand and follow. And it provides the standard template for implementation, which can share the flexibility to engage applications of different industries.
Deep Neural Networks (DNN), or simply Deep Learning (DL), took Artificial Intelligence (AI) by storm and have infiltrated into business at an unprecedented rate. Access to vast amounts of data, recently made available by the Big Data revolution, extensive computational power and a new wave of efficient learning algorithms, helped Artificial Neural Networks to achieve state-of-the-art results in almost all AI challenges.
The implications of DL supported AI in business is tremendous, shaking to the foundations many industries. However, incorporating this technology in established business is far from obvious: cultural inertia in organizations, lack of transparency in most DL models and the complexity in training these models are some of the issues that will be addressed.
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic...DATAVERSITY
Donna Burbank presented techniques for monetizing data as a strategic asset. She discussed improving core business through optimizing revenue, minimizing costs, and reducing risk. New opportunities include developing products and services like smart metering and selling data sets. Data initiatives can yield substantial benefits; for example, BT Group achieved over $800 million from data quality improvements.
Chief Data & Analytics Officer - who are these new kids on the C-Suite block ?Mario Faria
The document discusses the roles of Chief Data Officer, Chief Analytics Officer, and Lead Data Scientist. It describes how these roles lead culture change to create data-driven organizations by managing the data life cycle, including acquisition, analytics, governance, quality, technology, and budget. These roles leverage an organization's data assets to support business strategy and are responsible for enterprise-wide data administration. The document also provides an overview of the responsibilities and skills needed to succeed in these data leadership positions.
Improving Data Analytics with Data GovernanceDATAVERSITY
Organizations are dedicating tremendous resources to improve their analytical capabilities. The focus for many is to improve the quality, understanding, availability and thus the value of the data for data scientists and analysts. These people are focused on providing descriptive, predictive and prescriptive analytics for the betterment of their organization. It all starts with governed data.
Join Bob Seiner and a special guest for this month’s installment of the Real-World Data Governance webinar series where they will discuss the importance of using Data Governance to improve Data Analytics. Bob will challenge the guest with questions about why and how data governance has a positive impact on getting the most out of your data.
In this webinar, Bob and his guest will discuss:
The relationship between Data Governance and Data Analytics
Getting management to understand why Data Governance is necessary
How to focus your Data Governance program on analytics
Using the focus on analytics to bolster your Data Governance program
Final words on the symbiotic relationship between Data Governance and Data Analytics
Developing a Data Strategy -- A Guide For Business Leadersibi
Data is one of our most valuable assets -- yet we rarely understand how to incorporate it into our business plans. This presentation provides an introduction to data strategy for business leaders and points to more resources.
Creating a Data-Driven Organization: an executive summaryCarl Anderson
What does it mean for an organization to be data-driven? It is not about having lots of reports and dashboards or big data but having the right data culture. Learn more about that culture in this executive summary of the key findings in Carl Anderson's new book "Creating a Data-Driven Organization" (2015) from O'Reilly Media.
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...DATAVERSITY
The document introduces a new cloud-based data monetization platform called YourDataConnect focused on helping Chief Data Officers. It notes that 68% of Fortune 1000 companies have a CDO but they struggle to measure ROI on data management spending. YourDataConnect is a SaaS platform that can help CDOs quantify the financial benefits of data across revenue growth, cost reduction, and risk mitigation through an automated dashboard. It allows for data valuation, continuous ROI measurement, data sharing in a marketplace, and regulatory compliance tracking.
The enterprise marketer's playbook: Building an integrated data strategy.
An integrated data strategy can help any business see customer journeys more clearly ― and then give customers more relevant ads and experiences that get results. So why doesn't everyone have such a strategy? We look at what sets the marketing leaders apart.
Let marketing data be your guide
If you've ever felt too swamped by data to find the customer insights you need, you're not alone. But there's a new and better approach to gaining deeper audience insights: building an integrated data strategy.
Read this report to learn how:
86% of senior executives agree that eliminating organizational silos is critical to expanding the use of data and analytics in decision-making.
75% of marketers agree that lack of education and training on data and analytics is the biggest barrier to more business decisions being made based on data insights.
Leading marketers are 59% more likely to use digital analytics to optimize the user experience in real time.
Does your organization need a Chief Data Officer (CDO) ?Mario Faria
A question that will have one answer : it depends ! It depends on your company maturity level and how upper management will support it. This is material I presented at meeting organized by PointB, an strategic consulting company for the data leaders of the Seattle area in Aug-2013
Data-Ed Webinar: Data Governance StrategiesDATAVERSITY
Much like project team management and home improvement, Data Governance sounds a lot simpler than it actually is. In a nutshell, Data Governance is the process by which an organization delegates responsibility and exercises control over mission-critical data assets. In practice, though, Data Governance directs how all other Data Management functions are performed, meaning that much of your Data Management strategy’s capacity to function at all depends on your effectiveness in governing its implementation. Understanding these aspects of governance is necessary to eliminate the ambiguity that often surrounds effective Data Management and stewardship programs, since the goal of governance is to manage the data that supports organizational strategy.
This webinar will:
Illustrate what Data Governance functions are required for effective Data Management, how they fit with other Data Management disciplines, and why Data Governance can be tricky for many organizations
Help you develop a detailed vocabulary and set of narratives to facilitate understanding of your business objectives and imperatives that demand governance
Provide direction for selling Data Governance to organizational management as a specifically motivated initiative
Discuss foundational Data Governance concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Data Leadership - Stop Talking About Data and Start Making an Impact!DATAVERSITY
<!-- wp:paragraph -->
<p>For any organization to be successful, whatever we do with data must connect to meaningful business improvements—and those must be measured. If current data efforts lack results or accountability, then Data Leadership is our answer.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>But Data Leadership isn’t really about the data at all. What makes Data Leadership so powerful is its ability to completely transform organizations. Going beyond traditional data management and governance, Data Leadership builds momentum and delivers the change we’ve long known our businesses need. Data Leadership helps us overcome the lingering data challenges our legacy approaches never will.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>This webinar will cover the key concepts of Data Leadership, and what anybody can do to start making a bigger impact for their teams and businesses. Whether your role today is large or small, Data Leadership will be essential to your future data success! </p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>Key Learnings Include:</p>
<!-- /wp:paragraph -->
<!-- wp:list -->
<ul><li>What Data Value really is, and why creating it is the goal of everything we do with data</li><li>Introduction to the Data Leadership Framework</li><li>Why Data Leadership is fundamentally about balance</li><li>How to immediately start making a Data Leadership impact in your organization</li></ul>
<!-- /wp:list -->
Data-Centric Analytics and Understanding the Full Data Supply ChainDATAVERSITY
While model development is an important part of analytics, this activity can be compromised by a lack of understanding of the data used in these models and poor Data Quality. For insights to be relied upon and truly actionable, data-related issues must be addressed.
The data supply chain (the set of architectural components that moves data around the enterprise from points where it is created or acquired to points where it is used) must be managed to supply the needs of analytics and other constituencies.
This webinar describes how the data supply chain should be designed and operated to provide analytics with the data it needs, and how Data Scientists should interact with the data supply chain to obtain the data they need. It also covers:
Data-centric considerations that must be taken into account in the development of analytic models
Features of a modern data supply chain
Major components in the data supply chain, with a focus on Data Lakes
Major roles and responsibilities in the data supply chain
How analytics must interact with the data supply chain
When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
Lead Your Data Revolution - How to Build a Foundation of Trust and Data Gover...DATAVERSITY
<!-- wp:paragraph -->
<p>Becoming a data-driven organization is something many companies aspire to, but few are able to obtain. Let’s face it: Data is confusing. It is complicated, dirty, and spread out all over a business. While companies are making big investments in Data Management projects, only a few are seeing the payoff. </p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>New research from Experian shows that despite many ongoing data initiatives, 69 percent of organizations struggle to be data-driven. The struggles are real. Companies face a large data debt, look at data projects through a siloed lens, and still have a large volume of inaccurate data. In fact, 65 percent report inaccurate data is undermining key initiatives. <br></p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>However, the tide is turning. Businesses are starting to adopt data enablement, or a practice of empowering a larger group of individuals within the business to understand and harness the power of data and analytics. Companies that empower wider data usage are better able to comply with regulations, improve decision-making, and, of course, deliver a superior customer experience. Are these the results you’re striving for? </p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>Join us to uncover new research from more than 500 Data Management practitioners as we take a deep dive into:</p>
<!-- /wp:paragraph -->
<!-- wp:list -->
<ul><li>The top challenges in becoming a data-driven organization </li><li>Trends and the rise of data enablement </li><li>The profile of a mature organization </li><li>Tips for how you can adopt data enablement practices</li></ul>
<!-- /wp:list -->
The document discusses the importance of developing a data strategy before building a data warehouse. It defines a data strategy as a unified, organization-wide plan for using corporate data as a vital asset. The data strategy should address critical data issues like quality, metadata, performance, distribution, ownership, security and privacy. Developing a data strategy requires identifying strategic and operational decisions, aligning the strategy with business goals, and answering many questions across various data-related topics.
A straight forward and repeatable approach to creating Enterprise Agility by Connecting Strategy to Execution through the use of Facilitated Articulation, A3 Planning, Kanban Project Management, and Agile technology development. The approach results in alignment and drives effective change management.
Creating a clearly articulated data strategy—a roadmap of technology-driven capability investments prioritized to deliver value—helps ensure from the get-go that you are focusing on the right things, so that your work with data has a business impact. In this presentation, the experts at Silicon Valley Data Science share their approach for crafting an actionable and flexible data strategy to maximize business value.
In many organizations and functional areas, data has pulled even with money in terms of what makes the proverbial world go round. As businesses struggle to cope with the 21st century’s newfound data flood, it is more important than ever before to prioritize data as an asset that directly supports business imperatives. However, while organizations across most industries make some attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. Data Quality), the results of these efforts frequently fall far below expectations. At the root of many of these failures is poor organizational Data Management—which fortunately is a remediable problem.
This webinar will cover three lessons, each illustrated with examples, that will help you establish realistic goals and benchmarks for Data Management processes and communicate their value to both internal and external decision-makers:
How organizational thinking must change to include value-added Data Management practices
The importance of walking before you run with data-focused initiatives
Prioritizing specification and Data Governance over “silver bullet” analytical tools
Discuss foundational data-centric concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
7 Pillars Of Data Strategy - High Five 2018Evan Levy
Evan Levy, Director of Advertising at Method Savvy, discusses 7 pillars of a successful data strategy: 1) Asking the right questions, 2) Technical implementation, 3) Users, 4) Data storage and structure, 5) Security, 6) Handling personally identifiable information, and 7) Visualization and analysis needs. He emphasizes starting with specific, action-oriented questions and considering your audience when visualizing data. Following these pillars will help companies get the most value from their data through proper analysis and decision making.
This framework helps organizations align Data Strategy with Business Strategy to prioritize goals around the most pressing operational needs. It introduces Data Management & Data Ability Maturity Matrix to visualize the core path of business digital transformation, which is easy to understand and follow. And it provides the standard template for implementation, which can share the flexibility to engage applications of different industries.
Deep Neural Networks (DNN), or simply Deep Learning (DL), took Artificial Intelligence (AI) by storm and have infiltrated into business at an unprecedented rate. Access to vast amounts of data, recently made available by the Big Data revolution, extensive computational power and a new wave of efficient learning algorithms, helped Artificial Neural Networks to achieve state-of-the-art results in almost all AI challenges.
The implications of DL supported AI in business is tremendous, shaking to the foundations many industries. However, incorporating this technology in established business is far from obvious: cultural inertia in organizations, lack of transparency in most DL models and the complexity in training these models are some of the issues that will be addressed.
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic...DATAVERSITY
Donna Burbank presented techniques for monetizing data as a strategic asset. She discussed improving core business through optimizing revenue, minimizing costs, and reducing risk. New opportunities include developing products and services like smart metering and selling data sets. Data initiatives can yield substantial benefits; for example, BT Group achieved over $800 million from data quality improvements.
Chief Data & Analytics Officer - who are these new kids on the C-Suite block ?Mario Faria
The document discusses the roles of Chief Data Officer, Chief Analytics Officer, and Lead Data Scientist. It describes how these roles lead culture change to create data-driven organizations by managing the data life cycle, including acquisition, analytics, governance, quality, technology, and budget. These roles leverage an organization's data assets to support business strategy and are responsible for enterprise-wide data administration. The document also provides an overview of the responsibilities and skills needed to succeed in these data leadership positions.
Improving Data Analytics with Data GovernanceDATAVERSITY
Organizations are dedicating tremendous resources to improve their analytical capabilities. The focus for many is to improve the quality, understanding, availability and thus the value of the data for data scientists and analysts. These people are focused on providing descriptive, predictive and prescriptive analytics for the betterment of their organization. It all starts with governed data.
Join Bob Seiner and a special guest for this month’s installment of the Real-World Data Governance webinar series where they will discuss the importance of using Data Governance to improve Data Analytics. Bob will challenge the guest with questions about why and how data governance has a positive impact on getting the most out of your data.
In this webinar, Bob and his guest will discuss:
The relationship between Data Governance and Data Analytics
Getting management to understand why Data Governance is necessary
How to focus your Data Governance program on analytics
Using the focus on analytics to bolster your Data Governance program
Final words on the symbiotic relationship between Data Governance and Data Analytics
Developing a Data Strategy -- A Guide For Business Leadersibi
Data is one of our most valuable assets -- yet we rarely understand how to incorporate it into our business plans. This presentation provides an introduction to data strategy for business leaders and points to more resources.
Creating a Data-Driven Organization: an executive summaryCarl Anderson
What does it mean for an organization to be data-driven? It is not about having lots of reports and dashboards or big data but having the right data culture. Learn more about that culture in this executive summary of the key findings in Carl Anderson's new book "Creating a Data-Driven Organization" (2015) from O'Reilly Media.
Slides: Data Monetization — Demonstrating Quantifiable Financial Benefits fro...DATAVERSITY
The document introduces a new cloud-based data monetization platform called YourDataConnect focused on helping Chief Data Officers. It notes that 68% of Fortune 1000 companies have a CDO but they struggle to measure ROI on data management spending. YourDataConnect is a SaaS platform that can help CDOs quantify the financial benefits of data across revenue growth, cost reduction, and risk mitigation through an automated dashboard. It allows for data valuation, continuous ROI measurement, data sharing in a marketplace, and regulatory compliance tracking.
The enterprise marketer's playbook: Building an integrated data strategy.
An integrated data strategy can help any business see customer journeys more clearly ― and then give customers more relevant ads and experiences that get results. So why doesn't everyone have such a strategy? We look at what sets the marketing leaders apart.
Let marketing data be your guide
If you've ever felt too swamped by data to find the customer insights you need, you're not alone. But there's a new and better approach to gaining deeper audience insights: building an integrated data strategy.
Read this report to learn how:
86% of senior executives agree that eliminating organizational silos is critical to expanding the use of data and analytics in decision-making.
75% of marketers agree that lack of education and training on data and analytics is the biggest barrier to more business decisions being made based on data insights.
Leading marketers are 59% more likely to use digital analytics to optimize the user experience in real time.
Does your organization need a Chief Data Officer (CDO) ?Mario Faria
A question that will have one answer : it depends ! It depends on your company maturity level and how upper management will support it. This is material I presented at meeting organized by PointB, an strategic consulting company for the data leaders of the Seattle area in Aug-2013
Data-Ed Webinar: Data Governance StrategiesDATAVERSITY
Much like project team management and home improvement, Data Governance sounds a lot simpler than it actually is. In a nutshell, Data Governance is the process by which an organization delegates responsibility and exercises control over mission-critical data assets. In practice, though, Data Governance directs how all other Data Management functions are performed, meaning that much of your Data Management strategy’s capacity to function at all depends on your effectiveness in governing its implementation. Understanding these aspects of governance is necessary to eliminate the ambiguity that often surrounds effective Data Management and stewardship programs, since the goal of governance is to manage the data that supports organizational strategy.
This webinar will:
Illustrate what Data Governance functions are required for effective Data Management, how they fit with other Data Management disciplines, and why Data Governance can be tricky for many organizations
Help you develop a detailed vocabulary and set of narratives to facilitate understanding of your business objectives and imperatives that demand governance
Provide direction for selling Data Governance to organizational management as a specifically motivated initiative
Discuss foundational Data Governance concepts based on “The DAMA Guide to the Data Management Body of Knowledge” (DAMA DMBOK)
Data Leadership - Stop Talking About Data and Start Making an Impact!DATAVERSITY
<!-- wp:paragraph -->
<p>For any organization to be successful, whatever we do with data must connect to meaningful business improvements—and those must be measured. If current data efforts lack results or accountability, then Data Leadership is our answer.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>But Data Leadership isn’t really about the data at all. What makes Data Leadership so powerful is its ability to completely transform organizations. Going beyond traditional data management and governance, Data Leadership builds momentum and delivers the change we’ve long known our businesses need. Data Leadership helps us overcome the lingering data challenges our legacy approaches never will.</p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>This webinar will cover the key concepts of Data Leadership, and what anybody can do to start making a bigger impact for their teams and businesses. Whether your role today is large or small, Data Leadership will be essential to your future data success! </p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>Key Learnings Include:</p>
<!-- /wp:paragraph -->
<!-- wp:list -->
<ul><li>What Data Value really is, and why creating it is the goal of everything we do with data</li><li>Introduction to the Data Leadership Framework</li><li>Why Data Leadership is fundamentally about balance</li><li>How to immediately start making a Data Leadership impact in your organization</li></ul>
<!-- /wp:list -->
Data-Centric Analytics and Understanding the Full Data Supply ChainDATAVERSITY
While model development is an important part of analytics, this activity can be compromised by a lack of understanding of the data used in these models and poor Data Quality. For insights to be relied upon and truly actionable, data-related issues must be addressed.
The data supply chain (the set of architectural components that moves data around the enterprise from points where it is created or acquired to points where it is used) must be managed to supply the needs of analytics and other constituencies.
This webinar describes how the data supply chain should be designed and operated to provide analytics with the data it needs, and how Data Scientists should interact with the data supply chain to obtain the data they need. It also covers:
Data-centric considerations that must be taken into account in the development of analytic models
Features of a modern data supply chain
Major components in the data supply chain, with a focus on Data Lakes
Major roles and responsibilities in the data supply chain
How analytics must interact with the data supply chain
When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
Lead Your Data Revolution - How to Build a Foundation of Trust and Data Gover...DATAVERSITY
<!-- wp:paragraph -->
<p>Becoming a data-driven organization is something many companies aspire to, but few are able to obtain. Let’s face it: Data is confusing. It is complicated, dirty, and spread out all over a business. While companies are making big investments in Data Management projects, only a few are seeing the payoff. </p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>New research from Experian shows that despite many ongoing data initiatives, 69 percent of organizations struggle to be data-driven. The struggles are real. Companies face a large data debt, look at data projects through a siloed lens, and still have a large volume of inaccurate data. In fact, 65 percent report inaccurate data is undermining key initiatives. <br></p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>However, the tide is turning. Businesses are starting to adopt data enablement, or a practice of empowering a larger group of individuals within the business to understand and harness the power of data and analytics. Companies that empower wider data usage are better able to comply with regulations, improve decision-making, and, of course, deliver a superior customer experience. Are these the results you’re striving for? </p>
<!-- /wp:paragraph -->
<!-- wp:paragraph -->
<p>Join us to uncover new research from more than 500 Data Management practitioners as we take a deep dive into:</p>
<!-- /wp:paragraph -->
<!-- wp:list -->
<ul><li>The top challenges in becoming a data-driven organization </li><li>Trends and the rise of data enablement </li><li>The profile of a mature organization </li><li>Tips for how you can adopt data enablement practices</li></ul>
<!-- /wp:list -->
The document discusses the importance of developing a data strategy before building a data warehouse. It defines a data strategy as a unified, organization-wide plan for using corporate data as a vital asset. The data strategy should address critical data issues like quality, metadata, performance, distribution, ownership, security and privacy. Developing a data strategy requires identifying strategic and operational decisions, aligning the strategy with business goals, and answering many questions across various data-related topics.
A straight forward and repeatable approach to creating Enterprise Agility by Connecting Strategy to Execution through the use of Facilitated Articulation, A3 Planning, Kanban Project Management, and Agile technology development. The approach results in alignment and drives effective change management.
Taming the Enterprise: Delivering a Unified Cross-Company Subscription Strate...Zuora, Inc.
It’s one thing to understand the intricate needs of the enterprise customer - the real heavy lifting comes with the delivery of solutions that actual achieve the desired end-state. Learn how Zuora is being leveraged to meet the multifaceted requirements of Google Wildfire, providing speed, flexibility, and streamlined subscription management. This journey started in a business unit and is spreading to encompass a unified corporate strategy throughout the enterprise.
This presentation was given as a guest lecture in Laurel Hart's Spring 2011 Masters progra course for Corporate and Organizational Communications in the NYU school of continuing studies by Amy Sample Ward. Learn more at http://amysampleward.org
This document outlines a framework for agile strategy execution using sprints, scrums, and reflections. It includes establishing 3 year objectives, quarterly projects, 30 day sprints, and 12 month objectives. Teams plan sprints at the start, do the work, review progress at the end, and reflect quarterly on successes and improvements. Foundational elements include an "A" team, communications, learning, and shared values. The approach aggregates marginal gains and is based on Rockefeller Habits, agile project management, and faster execution than competitors.
Acting on Analytics - How to Build a Data-Driven Enterprise - Brighttalk webi...Mario Faria
Big Data and Analytics have become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. However, there is one component that can halt any initiative: YOUR COMPANY's ANALYTICS MATURITY.
How prepared is your company to implement and use the available data, the high end modeling techniques and the data as well as analytics expertise?
From what I have learned and experienced, companies are still not adequately prepared, hurting their ability to compete in the market.
This presentation will help executives and data professionals to understand the steps needed to create an analytics organization, and provide some real life examples on companies who succeeded and some who failed miserably.
WTF is a Data Strategy? - WTF Programmatic UK, 11/11/14Digiday
A data strategy provides insights about customers to inform business goals across marketing channels. It creates a unified view of each customer by collecting data from websites, apps, purchases, and other sources to optimize their experiences. An effective data strategy uses analytics like machine learning and predictive modeling to segment customers and personalize interactions in real-time across channels.
Subscribed 2016: Metrics that Matter - An Operational Framework for Running Y...Zuora, Inc.
Unlike traditional financial metrics, subscription metrics are forward-looking metrics that give insight into your customer’s success as well as the health of your business. From ARR to churn, learn from best-in-class companies how your metrics can drive growth.
Check out Zuora Academy for more actionable advice for finance, marketing, tech, operations, product, and more. All the info you need to build and run an amazing subscription business: https://www.zuora.com/academy/
Strategy Planning and Deployment Process Training ModuleFrank-G. Adler
The Strategy Planning and Deployment Training Module v6.0 includes:
1. MS PowerPoint Presentation including 97 slides covering our Strategy Planning and Deployment Process using Strategy Maps and Hoshin Kanri, including Introduction to Strategy Planning, Organizing the Process, Current State Analysis (CSA), Strategic Vision Elements, Strategic Breakthrough Objectives, Strategy Maps, Strategic Initiatives and Tactics, Strategy Deployment Matrix, and Strategy Implementation and Review.
2. MS Excel Templates for Annual Planning, Criticality Analysis, Force Field Analysis, Radar Gap Analysis Chart, Strategy Grid Alignment Matrix, Strategy Grid Correlation Matrix, Project Selection Matrix, Bowling Chart, and Strategy Implementation Review Table.
3. MS Word Current State Analysis (CSA) Questionnaire
4. MS Excel Hoshin Kanri Strategy Deployment X-Matrix Template
CDO Webinar: 2017 Trends in Data StrategyDATAVERSITY
December is traditionally a time to start to look into next year. Trends are derived, and lessons learned applied. Join Kelle and John while we ask several of our peers and CDOs to look ahead at what might be new, and look back at what has worked and not worked. We will make our own predictions and offer up some advice on how to prepare yourself for maximum agility.
Agile strategy execution framework, part 1Alan Leeds
This presentation shows how agile concepts can be combined with strategy execution best practices, resulting in a meaningful, practical and quickly deployable strategy execution framework.
A successful business requires both a well developed strategy and the ability to execute on that strategy. Strategy without execution is merely theory. Many companies develop robust strategies, but fail at operationalizing their strategies into implementable steps.
This slideshare covers frameworks that deal with both sides—Strategy Development and Strategy Execution. In this presentation, we will discuss 12 business frameworks. For each framework, we will provide an overview, explain its proper usage, and highlight the analyses involved.
This slideshare will also provide references to more detailed documentation, guides, and methodologies if you would like more information.
The following business frameworks will be discussed:
Consolidation-Endgame Curve
Porter’s Five Forces
BCG Growth-Share Matrix
Marketing Mix (4/7 P’s)
Blue Ocean Strategy
SWOT Analysis
PEST Analysis
Product Lifecycle
Consumer Adoption Curve
Balanced Scorecard
Organizational Hurdles
Hoshin Kanri
Each framework is geared towards a specific type of analysis—pick and choose the best frameworks to use for your particular business problem.
Pricing Strategy: How To Win With Subscription Pricing ModelsZuora, Inc.
http://bit.ly/PricingStrategySlide This presentation is focused on your pricing strategy and how to drive massive revenue growth. Zuora and our partner Simon-Kucher do lot of events together – pricing is always one of the most popular topics, because it’s such an important strategic lever. Pricing is even more important for subscription businesses – We’ll discuss why. We’re fortunate to work with a lot different types of subscription businesses and we learn about their subscription journeys – this is the content that we want to share with you. http://bit.ly/PricingStrategySlide
Dynamic Talks: "Data Strategy as a Conduit for Data Maturity and Monetization...Grid Dynamics
Organizations need to tap into the huge potential of their vast volumes of data, but a use case tactical approach is not going to work. Instead, they need to work in the definition of a data strategy linked to the most relevant goals for the enterprise.
Data Architecture Strategies: Building an Enterprise Data Strategy – Where to...DATAVERSITY
The majority of successful organizations in today’s economy are data-driven, and innovative companies are looking at new ways to leverage data and information for strategic advantage. While the opportunities are vast, and the value has clearly been shown across a number of industries in using data to strategic advantage, the choices in technology can be overwhelming. From Big Data to Artificial Intelligence to Data Lakes and Warehouses, the industry is continually evolving to provide new and exciting technological solutions.
This webinar will help make sense of the various data architectures & technologies available, and how to leverage them for business value and success. A practical framework will be provided to generate “quick wins” for your organization, while at the same time building towards a longer-term sustainable architecture. Case studies will also be provided to show how successful organizations have successfully built a data strategies to support their business goals.
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
The Business Value of Metadata for Data GovernanceRoland Bullivant
In today’s digital economy, data drives the core processes that deliver profitability and growth - from marketing, to finance, to sales, supply chain, and more. It is also likely that for many large organizations much of their key data is retained in application packages from SAP, Oracle, Microsoft, Salesforce and others. In order to ensure that their foundational data infrastructure runs smoothly, most organizations have adopted a data governance initiative. These typically focus on the people and processes around managing data and information. Without an actionable link to the physical systems that run key business processes, however, governance programs can often lack the ‘teeth’ to effectively implement business change.
Metadata management is a process that can link business processes and drivers with the technical applications that support them. This makes data governance actionable and relevant in today’s fast-paced and results-driven business environment. One of the challenges facing data governance teams however, is the variety in format, accessibility and complexity of metadata across the organization’s systems.
Data Integrity: From speed dating to lifelong partnershipPrecisely
Governance has little to do with governance…it’s about delivering and demonstrating value. It’s one thing for your colleagues to intellectually believe in the value of data, good data, and governed data, but it’s another thing entirely to have them emotionally engaged and excited to be involved. In this presentation from the CDO Sit-Down series, Shaun Connolly, Vice President of International Strategic Services, shares his thoughts and experience on approaches to win over reluctant leaders and business teams and describe the key components of successful programs.
DataEd Webinar: Implementing Successful Data Strategies - Developing Organiza...DATAVERSITY
The document discusses developing an effective data strategy. It begins by introducing Micheline Casey and Peter Aiken, experts in data strategy. It then discusses what a data strategy is, why it is important to have one, and key characteristics of an effective data strategy. The document outlines the process for developing a data strategy, including pre-planning, aligning with organizational goals, prioritizing initiatives, and performing assessments. It emphasizes the importance of implementing foundational data practices before advanced practices. The presentation concludes with discussing challenges to developing a data strategy and taking a question.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Slides: Empowering Data Consumers to Deliver Business ValueDATAVERSITY
Today, the role of Chief Data Officers and their teams has expanded from risk and compliance-based activities to delivering business value through trusted data. With the exponential growth in data and data consumers throughout an organization, ensuring that everyone gets the information that they need — and that it can be relied upon — is no small feat. CDOs need to rely on modern Data Governance leaders to discover where all of the data lives, define the context, measure the quality, ensure privacy, and then democratize data to empower the rest of the organization. Join us for this informative webinar as we highlight the challenges of today’s data leaders, how they can democratize trusted, secure data, and ultimately discover how to deliver business value.
DAS Slides: Building a Data Strategy – Practical Steps for Aligning with Busi...DATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in today’s marketplace from digital transformation, to marketing, to customer centricity, population health, and more. This webinar will help de-mystify data strategy and data architecture and will provide concrete, practical ways to get started.
Building a Data Strategy – Practical Steps for Aligning with Business GoalsDATAVERSITY
Developing a Data Strategy for your organization can seem like a daunting task – but it’s worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in today’s marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
Data Insights and Analytics Webinar: CDO vs. CAO - What’s the Difference?DATAVERSITY
At one time, there were well-stated distinctions between the Chief Data Officer and Chief Analytics Officer roles. But not today. In some organizations, this role confusion actually causes serious concerns.
John and Kelle will revisit the definitions, suggest where lack of clarity first began, and discuss how best to manage the role distinctions going forward.
This webinar will address:
Differences in the CAO and CDO roles
CDOs who aren’t responsible for all organizational data
Why role clarity matters
Organizational success without one or both roles
DAS Slides: Data Quality Best PracticesDATAVERSITY
Tackling data quality problems requires more than a series of tactical, one off improvement projects. By their nature, many data quality problems extend across and often beyond an organization. Addressing these issues requires a holistic architectural approach combining people, process and technology. Join Nigel Turner and Donna Burbank as they provide practical ways to control data quality issues in your organization.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
The document discusses building a data governance framework. It provides examples of components to consider for a framework, including vision and strategy, organization and people, processes and workflows, data management and measures, culture and communications, and tools and technology. The framework is intended to help align data governance efforts with business needs, ensure a holistic approach, and provide a baseline for a data governance program. Key questions are provided under each component to help assess where activities may be needed.
President and Chief Performance Officer,
Transformation Leadership Coach, Speaker, Author,
Adjunct Associate Professor of Business Administration
Professor Dr. Frank L Harper Jr. PMP® is a proven deliverer of innovation and operations excellence through leading numerous process-and productivity-improvement initiatives, leverages emerging technologies for business transformation, orchestrates organizational change, while identifying and developing collaborative opportunities between business units and technology.
A self-proclaimed Strategic Hustler™, his technical savvy, leadership, teaching, solutions-focused thinking and execution has directed or contributed to strategic programs/projects with combined budgets of $4+ Billion supporting business units to identify, develop, and implement business solutions that maximize throughput, operational efficiency, customer service, and competitiveness. The effectiveness of these efforts generated combined revenues and savings of $10+ Billion for companies and governments on five continents [North & South America, Asia, Africa, and Europe].
A former shoe shine boy, or Street hustler, and scholar-athlete, he has received national and international honors for his pioneering work in the fields of information technology, industrial engineering, and project management. Community leaders applauded his views on community-based education and training. His forty-plus years of leadership and management experience extends beyond the corporate setting into community, sports, and spiritual endeavors.
Currently, Professor Dr. Harper who also holds an MBA in Marketing, MSc in Industrial Engineering, and BSc in Computer Technology/Industrial Engineering; is an Adjunct Associate Professor of Business Administration for the Cambridge Corporate University (Switzerland), President and Chief Performance Officer of Intelligent Systems Services LLC, (US) and Strategic Advisor / Trainer / Business Transformation Consultant for Innovative Management Services, Pakistan.
Emerging Trends in Data Architecture – What’s the Next Big Thing?DATAVERSITY
With technological innovation and change occurring at an ever-increasing rate, it’s hard to keep track of what’s hype and what can provide practical value for your organization. Join this webinar to see the results of a recent DATAVERSITY survey on emerging trends in Data Architecture, along with practical commentary and advice from industry expert Donna Burbank.
Data Governance Takes a Village (So Why is Everyone Hiding?)DATAVERSITY
Data governance represents both an obstacle and opportunity for enterprises everywhere. And many individuals may hesitate to embrace the change. Yet if led well, a governance initiative has the potential to launch a data community that drives innovation and data-driven decision-making for the wider business. (And yes, it can even be fun!). So how do you build a roadmap to success?
This session will gather four governance experts, including Mary Williams, Associate Director, Enterprise Data Governance at Exact Sciences, and Bob Seiner, author of Non-Invasive Data Governance, for a roundtable discussion about the challenges and opportunities of leading a governance initiative that people embrace. Join this webinar to learn:
- How to build an internal case for data governance and a data catalog
- Tips for picking a use case that builds confidence in your program
- How to mature your program and build your data community
#MITXData "How the Data Revolution is Turning the Marketing World Upside Down...MITX
-Michele Goetz, Senior Analyst, Forrester
-Beatriz Santin, Senior Director of Marketing and Product, Experian QAS
Ever wished the data revolution never came and threw your world into chaos? Know that you can't turn back but don't know where to start or how to get there fast? Excited to finally have a seat at the table but anxious about how to deliver against rising expectations?
This session presented by Experian QAS, a part of Experian Marketing Services, and Forrester will explore the sentiments of marketers as we change our day-to-day and look for new avenues to propel business growth. From B2B to B2C, relevance is more important than ever – but how can we leverage data to make our brands stand out amongst all the others? Join to hear case studies and practical advice to guide you in a world where data is there not only for you but also for your customers and your competitors – to analyze and to consume.
Becoming a Data-Driven Organization - Aligning Business & Data StrategyDATAVERSITY
More organizations are aspiring to become ‘data driven businesses’. But all too often this aim fails, as business goals and IT & data realities are misaligned, with IT lagging behind rapidly changing business needs. So how do you get the perfect fit where data strategy is driven by and underpins business strategy? This webinar will show you how by de-mystifying the building blocks of a global data strategy and highlighting a number of real world success stories. Topics include:
•How to align data strategy with business motivation and drivers
•Why business & data strategies often become misaligned & the impact
•Defining the core building blocks of a successful data strategy
•The role of business and IT
•Success stories in implementing global data strategies
Using Lean Principles to Manage the Data Value ChainMario Faria
Creating and managing a data office is not an easy task. The reasons for so many problems in streamlining a data strategy come from lack of data ownership, lack of a data roadmap and the data processes not clearly defined.
Using the Lean Principles that come from the Toyota Production System is one method that has been proved to be quite successful.
This session delivered for the Data Quality Pro Summit explores how it can be done.
The Rise of People Management AnalyticsMario Faria
Data is now as integral to our 21st century economy as oil has been for many decades. With the power of data and analytics, several organizations are rethinking their business strategy completely.
However, when we look at data and analytics from an HR or people management perspective, there are some untapped opportunities to make data-driven decisions. What are some of these opportunities? Does a culture change need to happen to positively impact your company’s bottom-line?
This is the material I used at my session at the Great Place to Work Institute in Canada, on April 2015.
I discussed these questions and share case studies on how some organizations are now using their second most important asset (data) to manage their most important asset (people).
The Chief Data Officer's Quest for Data Quality and Data Governance Mario Faria
Keynote presentation I have delivered at DGIQ 2014 conference in San Diego. Video and audio can be found at http://vimeopro.com/vcube/dgiq2014
Offshore Analytics - material from the Big Data Analytics Conference held by ...Mario Faria
This document provides an overview of offshore analytics from Mario Faria, Chief Data Officer at ServiceSource. It discusses several large companies that perform analytics offshore, such as eBay and Wunderman. It also profiles some startup analytics companies that operate offshore, such as Trendwise Analytics in India and ScaleStation with offices in India and Serbia. Finally, it outlines some lessons learned about managing offshore analytics programs.
The Data Driven Business Attributes 2nd big data summit nov 2013Mario Faria
The document discusses the data driven business and importance of analytics. It notes that while data access is easy, transforming data into useful insights in a timely manner is challenging. The presentation emphasizes that people, processes, organizational change management, and data/technology architecture are key to achieving analytical success, not just tools and data alone. Analytics can help drive business maturity when the whole organization is aligned.
ECMSHOW 2013 - Construindo uma Organização Gerida por DadosMario Faria
The document discusses building an organization driven by data. It outlines Mario Faria's background and experience in data and analytics. It then covers topics like the increasing availability of data, roles in data-driven organizations, data science, machine learning, analytics, and how to promote business maturity through analytics. The key takeaways are that data is now widely available, humans are social, mobile is more than phones, and companies should start their analytics journey to leverage data and thrive in the future.
O Nascimento do Chief Data Officer - artigo Information Management - Agosto 2013Mario Faria
O documento descreve a carreira de Richard Wang, o primeiro General de Dados do mundo, e como ele inspirou a criação do cargo de Chief Data Officer (CDO). O autor, Mario Faria, foi o primeiro CDO da América Latina. O texto explica que o papel do CDO é trazer uma cultura baseada em dados para as organizações e gerar valor através da melhoria da qualidade e do uso estratégico dos dados.
2nd Big Data Business Forum Nov 13th to 15th, 2013 in San FranciscoMario Faria
The 2nd Big Data Business Forum will happen from November 13th to 15th, 2013 in San Francisco. This is one of the top data and analytics conferences of the year.
A Morte do CIO - artigo Information Management - Maio 2013Mario Faria
O modelo atual de TI das empresas não funciona na realidade atual de mercado. O artigo mostra um caso real onde a área de negócio conseguiu o que precisava pagando menos e com prazo mais realista que utilizando a área de TI da empresa
Página 2 - 4 ideias para usar o “big data” a favor dos seus negócios - Revis...Mario Faria
O documento discute três pontos principais sobre big data: 1) A cultura da empresa, não o orçamento, define se ela usará big data eficazmente; 2) Até empresas de pequeno e médio porte podem obter informações valiosas de big data com plataformas em nuvem; 3) Dados são a matéria-prima para análise, e sua qualidade e confiabilidade são essenciais para produzir informações úteis.
4 ideias para usar o “big data” a favor dos seus negócios - Matéria Exame - p...Mario Faria
O documento fornece 4 ideias para usar big data a favor dos negócios: 1) Análise de dados não faz milagres sem uma equipe qualificada; 2) A análise de dados deve atender às estratégias do negócio e não à tecnologia; 3) Dados podem ajudar a prever comportamentos de clientes; 4) Dados históricos podem melhorar processos e reduzir custos.
Helping Compliance Cross The Data ChasmMario Faria
Helping Compliance Cross the Data Chasm - Webinar for the Compliance Week Magazine, March 27st, 2013
Since 2012, Big Data has become a major topic of discussion, catalyzing attention among the C-Level executives and driving investments and projects inside the enterprise. But what exactly is Big Data from a compliance perspective? And how prepared is compliance to handle this current trend? From what I have learned and experienced, compliance is not adequately prepared and, trust me, the data and analytics people are not making it very easy for you. This presentation will help compliance personnel understand more about Big Data, while providing some real life examples that will help you determine if Big Data is a threat for your job security or a tool to help you thrive.
Speaker:
Mario Faria, Data Strategy Advisor - Boa Vista
Moderator:
Joe McCafferty, Executive Editor, Compliance Week
O Desafio da Integração de TI e Redes SociaisMario Faria
O documento discute os desafios da integração entre TI, redes sociais e marketing, com foco no Big Data. Aborda as 5 ondas da tecnologia, os 3 V's do Big Data, aplicações em diversas áreas e as 6 M's do Big Data. A integração de dados é apontada como essencial para unir marketing e tecnologia no uso de redes sociais, social CRM e análise de Big Data.
Redes Sociales y Tecnología: como el CIO debe estar preparadoMario Faria
Redes Sociales y Tecnología: como el CIO debe estar preparado - presentación hecha en Buenos Aires, SimpoCIO, Nov-2011. ¿ Un protagonista o un empiecillo a lo cambio?
Escalando o Ecommerce em Momentos de Alta DemandaMario Faria
Palestra proferida durante o Ecommerce Brasil, no evento sobre Planejamento para o Natal 2011 em São Paulo, onde abordei como o varejo pode evitar perdas de vendas, desde que utilize processos e requisitos clara para comprar sua infra-estrutura de tecnologia
A apresentação discute a evolução da sociedade de agrícola para industrial e da era da informação, com mudanças nas formas de organização social e econômica. Também aborda como a economia digital alterou paradigmas sobre preços e valor da informação, e como as redes sociais e efeitos de rede transformaram modelos de negócios.
6 passos iniciais para que seu projeto de Social CRM tenha sucessoMario Faria
O documento fornece seis passos para o sucesso de um projeto de Social CRM: 1) definir objetivos claros e mensuráveis; 2) conhecer as capacidades atuais da empresa; 3) criar um plano de curto, médio e longo prazo; 4) analisar soluções de tecnologia; 5) estabelecer métricas de sucesso financeiras; 6) mapear riscos que podem levar ao insucesso.
6 passos iniciais para que seu projeto de Social CRM tenha sucessoMario Faria
O documento fornece seis passos para o sucesso de um projeto de Social CRM: 1) definir objetivos claros e mensuráveis; 2) conhecer as capacidades atuais da empresa; 3) criar um plano de curto, médio e longo prazo; 4) analisar soluções de tecnologia; 5) estabelecer métricas de sucesso financeiras; 6) mapear riscos que podem levar ao insucesso.
computer organization and assembly language : its about types of programming language along with variable and array description..https://www.nfciet.edu.pk/
How iCode cybertech Helped Me Recover My Lost Fundsireneschmid345
I was devastated when I realized that I had fallen victim to an online fraud, losing a significant amount of money in the process. After countless hours of searching for a solution, I came across iCode cybertech. From the moment I reached out to their team, I felt a sense of hope that I can recommend iCode Cybertech enough for anyone who has faced similar challenges. Their commitment to helping clients and their exceptional service truly set them apart. Thank you, iCode cybertech, for turning my situation around!
[email protected]
Mieke Jans is a Manager at Deloitte Analytics Belgium. She learned about process mining from her PhD supervisor while she was collaborating with a large SAP-using company for her dissertation.
Mieke extended her research topic to investigate the data availability of process mining data in SAP and the new analysis possibilities that emerge from it. It took her 8-9 months to find the right data and prepare it for her process mining analysis. She needed insights from both process owners and IT experts. For example, one person knew exactly how the procurement process took place at the front end of SAP, and another person helped her with the structure of the SAP-tables. She then combined the knowledge of these different persons.
This comprehensive Data Science course is designed to equip learners with the essential skills and knowledge required to analyze, interpret, and visualize complex data. Covering both theoretical concepts and practical applications, the course introduces tools and techniques used in the data science field, such as Python programming, data wrangling, statistical analysis, machine learning, and data visualization.
AI Competitor Analysis: How to Monitor and Outperform Your CompetitorsContify
AI competitor analysis helps businesses watch and understand what their competitors are doing. Using smart competitor intelligence tools, you can track their moves, learn from their strategies, and find ways to do better. Stay smart, act fast, and grow your business with the power of AI insights.
For more information please visit here https://www.contify.com/
3. Participants
Vik Manchanda
Chief Infor mation Officer
Mario Faria
Chief Data Officer
Mike Jennings
Senior Director
Enterprise Data Architecture
4. mario.faria@cdo-‐‑inc.com
@mariofaria
h0p://www.cdo-‐‑inc.com
• One of the first Chief Data Officers in the world
leading teams focused in Analytics, Data
Monetization, Data Quality, Data Governance,
Operations and Business Architecture
• Currently he is the head of CDO, Inc., advising
companies on how to cross the “data & analytics
chasm”
• Worked as a CDO for ServiceSource and Boa
Vista (Equifax)
• Worked for IBM, Accenture and Microsoft,
leading projects related to BI, DW, CRM, Supply
Chain, Web Development and Management
Consulting
• His motto is : "If you do not treat people,
technology and data as economic assets, they will
become liabilities“
Mario Faria
Chief Da ta Officer
8. Mario Faria
8
How to transform data
assets into competitive
insights, that will drive
business decisions and
actions, using people,
processes and
technologies ?
9. Mario Faria
9
On data and analytics
• Many problems with streamlining a data strategy
• Major concerns with data management
• How you can overcome the issues
• What we have learned from the data journey
10. The Manifesto for Agile Software Development
Mario Faria
10
• Individuals and interactions over
processes and tools
• Working software over
comprehensive documentation
• Customer collaboration over
contract negotiation
• Responding to change over
following a plan
11. Mario Faria
11
Source : Leading Strategic Initiatives (www.leadingstrategicinitiatives.com)
17. Implementing
Data Management
Best Practices based on
the Lean Principles
that came from the
Toyota Manufacturing
Process
18. The Chief Data / Analytics / Digital Officer roles
Mario Faria
18
Chief Data Officer
(focused on data
management)
Chief Analytics Officer
(focused on decision
Chief Digital Officer
(focused on digital
transformation)
management
initiatives)
The ultimate leader who
creates and executes digital,
data and analytics strategies
to drive business value Copyright: Mario Faria 2014
19. How
did
some
organiza/ons
change
to
a
data
driven
culture
?
34. SAVE THE DATE!
CDO EXECUTIVE FORUM 2014
NOVEMBER 12, 2014 - NEW YORK, NEW YORKER HOTEL
CUTTING-EDGE RECOMMENDATIONS ON HOW TO:
• Mobilize your C-suite and prepare your organization for a new data-driven culture
• Translate your enterprise data assets into intelligence by reconsidering your approach to
information management processes
• Reach the consensus between the IT and business units to attain organizational efficiency
and eliminate the dangers of siloed data
• Get a granular view of your data: use analytics to separate clutter from meaningful
information and boost your company’s profitability
• Deliver highly actionable data through enhanced data management and analytics
initiatives
Find out more at:
http://www.datadrivenbiz.com/cdoforum/index.php
Call 201-204-1674 or email [email protected]
Register today with discount code WEBINAR0819 and save additional $100
35. Vik Manchanda
Chief Information Officer
RUTGERS UNIVERSITY, NJ
B.A. – Computer Science
COLUMBIA UNIVERSITY, NY
CTA Diploma
UCLA, CA
Executive IT & Business Integration
Coaching
AIG Life and A&H Houston, 2012 – Present
Senior Vice President, Chief Information Officer
AIG Advisor Group Houston, 2009 – 2010
Sr. Consultant
ACE Group, LTD. Houston, 2008 – 2009
Executive Vice President, Chief Architect & Data Officer
AIG Global Services New York, 2005 – 2008
Vice President, Chief Strategy & Administration Officer
AAIG Retirement Services Los Angeles, 2001 – 2005
Vice President, Senior Information Officer
AIG Domestic Brokerage Group New York & INDIA, 1996 – 2001
Assistant Vice President, Information Services Group
Bear Stearns, Inc.; New York, 1989 – 1996
Lehman Brothers; Citi Group;
Suburban Propane; AT&T
Affiliations:
• SIPA
• TiE
• No Kid Goes Hungry
• American Cancer Society
36. • Get Facts @ the right
36
time and the right place."
• Use Facts everytime
making crucial business
decisions."
• Preserve Facts."
Winning with Data!
37. Big Data Practice
37
Our approach reverse that
ratio offering maximum
business value in Revenue
generation, Operational
efficiency and Compliance
Business
Intelligence
Data Mining
OAP
Benchmarking BPR
Data
Warehousing
Analytics
Reporting
Traditionally 75% of
effort spent in data
aggregation and
transformation yields
25% in benefits
Big
Data
38. Three Good Winning Examples:
ü At AIG, we use data gathered from physical exam and blood results and pass
38
them through a model jointly created along with John Hopkins University to
predict mortality rates and based upon that we underwrite insured, resulting in
significant reduction in claims & increase in net profits.
ü At Ace, we created a model to apply to the insured to predict their risk level
and accordingly either underwrote them with appropriate rate class or denied
coverage. Same model was used to detect fraudulent claims.
ü At AIG, we are using a combination of mobile and data strategy to converge
distribution channels such that each agent is able to offer multiple lines of
businesses to the customers, as opposed to traditionally just creating leads for
the other lines of business. Further we are creating incentives for cross-selling
and upselling that are visibly working.
39. Incent The Right Behavior
• Link Compensation to Targets"
• Create Commission
39
Transparency"
• Allow Margin Control at Point
of Sale"
• Stricter Compliance and
Governance"
• Yield Higher Revenues"
"