Enabling digital business with governed data lake
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Digital business is enabled by Artificial intelligence, Machine learning, and data science. Artificial intelligence and machine learning are dependent on right Information architecture and data foundation. Governed data lake infused with governance and data science platform gives you the power to take the organization in the digital transformation and AI journey.
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Enabling digital business with governed data lake
- 1. Enabling Digital business with IBM Governed Data Lake Karan Sachdeva ([email protected]) IBM Big Data Analytics Sales Leader Asia Pacific Connect with me at - https://www.linkedin.com/in/karan20/
- 2. 1.Digital and AI Challenges 2.How IBM Governed Data Lake can help? 3.Industry Use Cases 4.IBM Governed Data Lake Building blocks 1.Collect 2.Govern 3.Analyze (Data Science and ML) 5.How to start your Governed Data Lake journey
- 3. IBM Cloud / © 2018 IBM Corporation Companies are pouring investment into AI and ML AI and ML is basis of Digital Transformation 9.8X $39 Billion+ 83% Increase in demand for ML Engineers over the last 5 years Investment by companies in AI during 2017 – led by tech, finance, and automotive Of companies say AI is strategically important to their business
- 4. IBM Cloud / © 2018 IBM Corporation Why are companies struggling to capture the value of AI and ML for their Digital Transformation projects? AI and ML is basis of Digital Transformation IA and Data is basis of AI and ML 80% Say they do not understand the data needed for AI There is no AI without IA Only 20%Of companies say they have successfully adopted AI
- 5. IBM Cloud / © 2018 IBM Corporation Barriers to successful AI and Digital transformations There is no Artificial Intelligence (AI) without Information Architecture (IA) Data Ecosystem • Data in silos • Difficult to access • No lineage Analytics Tools • Discrete tools • Different preferences • Difficult to manage Workflow • Not integrated • Not governed • Lack dev/prod parity Culture • Not collaborative • Slow provisioning • Lack trust in AI
- 6. 1.Digital and AI Challenges 2.How IBM Governed Data Lake can help? 3.Industry Use Cases 4.IBM Governed Data Lake Building blocks 1.Collect 2.Govern 3.Analyze (Data Science and ML) 5.How to start your Governed Data Lake journey
- 7. Persist Analyze Ingest Deploy Data | Assets | Pipelines | APIs Intelligent governance | Metadata Management What you need is a Integrated Platform based on Open Standards Governed Data Lake Core Tenets 1. Intelligent by Design 2. Based on Open Standards and Extensible 3. Collaborative for data Professionals 4. Self-service access to trusted data 5. Best in class streaming and real-time analytics Collaborate Data steward Data scientistData engineer Developer Find Share
- 8. 1.Digital and AI Challenges 2.How IBM Governed Data Lake can help? 3.Industry Use Cases 4.IBM Governed Data Lake Building blocks 1.Collect 2.Govern 3.Analyze (Data Science and ML) 5.How to start your Governed Data Lake journey
- 9. Industry Use Cases Governed Data Lake Use Cases: Burning Business Problems More Robustly Addressed Financial Services Insurance ••Customer 360 ••Fraud ••Compliance- GDPR, PDPA etc ••Risk Analytics ••Operational Data Store ••Predictive analytics Telco Media Energy & Utilities ••Customer 360 ••Customer Insights ••Network Optimization ••Data Monetization ••EDW Augmentation ••Predictive maintenance Retail Ecommerce ••Personalized Customer offers ••Omni-channel Customer Experience ••Loyalty programs ••Next Best Offer/Action ••Recommendation Engine ••Agile Supply Chain Manufacturing Industrial ••Connected: Car, Plane, Equipment ••Agile Supply Chain ••Predictive Maintenance ••IoT Data enabled “Smart Services” Government Public Sector ••Border Control ••Public Safety / Intelligence ••360 Tax payer ••Tax Optimization ••Cyber Threat ••Citizen Self Service ••Social Services Fraud IBM Governed Data Lake Open Standards | Governance | Machine Learning & Data Science Enterprise data warehouse(EDW) Modernization | EDW Offload | Teradata/Oracle Refresh
- 10. Integrate inbound touchpoints -offer the best offer for optimum outcomes Retail Data Governed Data Lake Insight Action Business Outcomes Behavioural - CRM - Store - POS Descriptive - Location - Mobile - Demographic - Weather Interaction - Web clicksteams - Call Center Notes - Emails Attitudes - Social Media Sentiments Continual data feeds - To support real-time decision making at every point of customer interaction Leverage All Data - High volumes Integrate Data - Traditional CRM and POS data - Combined with modern sources Capture and Access all data - Paper-based customer notes - Call center notes Customer identification - Single record of customer detail Text processing - Social media comments - Call center logs Understanding your customer -Helps retailers understand the “why” question and not only the “who/what/where/when” providing you with greater insight into customer behavior and buying patterns. -Real-time analytics to anticipate customer behavior Analytical questioning - Exploration of the data Business user dashboards and visualisation across multiple departments - Upsell/cross sell options - Marketing campaign effectiveness - Product analysis - Comprehensive view of a customer Improve customer segmentation -Advanced customer analytics to better define homogeneous customer clusters Cross-channel delivery of best action to address customer need and enhance long term business revenue Relevant & Timely Marketing Offers - Highly personalized communications and offers - making your customer relationship management more proactive Consistency across all customer interaction points - Web - Mobile - Call Center - Email - Social Media Improve service delivery and customer satisfaction Optimize revenue generating actions such as up sell, cross sell and retention Increase strategic lifetime value and loyalty Example- Governed Data lake vision for Retail Hadoop System Data Federation Data Science Models Streaming Data Hadoop+ BigSQL Info Integration & Governance Entity Matching Predictive Analytics Social Media Analytics Discovery & Exploration Business Intelligence Prescriptive Analytics Prescriptive Analytics IBM Data Science Experience Decision Optimization Social Merchandise -Social data (internal and external), frameworks, models and dashboards Retail Ecommerce •• Personalized Customer offers •• Omni-channel Customer Experience •• Loyalty programs •• Next Best Offer/Action •• Recommendation Engine •• Agile Supply Chain
- 11. Select the entry points to your Governed Data Lake journey Disruptive Competitive Optimized Data & Insight Accessibility Big Data made accessible and simple Data assets made understood, protected and trusted ML,AI, Optimize and Automate Natural Language Visualization and Exploration Collect Govern Data Science Enterprise DW Modernization EDW Augmentation Customer 360 Operational DataStore Machine Learning Anomaly Detection Recommendation Engine Cognitive Text Analytics
- 12. 12 Hybrid Data Management Unified Governance & Integration Data Science Machine Learning Organize AnalyzeCollect Understand customer behavior to make smarter marketing & programming decisions. Billions of records analyzed in seconds, rather than days, increasing on- demand viewing. Provide governed self-service data lake for fraud detection and customer engagement. Disciplined data classification upon entry, managing access, quality, privacy, and retention. Reduce unplanned trucking standstills helping clients better predict maintenance needs Applied statistical and ML techniques to lower diagnostic time 70% and repair time 20% IBM Governed Data Lake Customer Spotlights
- 13. 1.Digital and AI Challenges 2.How IBM Governed Data Lake can help? 3.Industry Use Cases 4.IBM Governed Data Lake Building blocks 1.Collect 2.Govern 3.Analyze (Data Science and ML) 5.How to start your Governed Data Lake journey
- 14. - Hortonworks Data Platform - Hortonworks Data Flow - Db2 Big SQL - IBM Big Replicate - Information Governance Catalog - BigIntegrate - BigQuality - BigMatch - CDC for Hadoop § Data Science Experience Local § Decision Optimization § Watson Explorer (v12 +) Under the hood IBM technologies Governed Data Lake Use Cases: Burning Business Problems More Robustly Addressed Collect- Hybrid Data Management Govern- Unified Governance & Integration Analyze- Data Science & Business Analytics Financial Services Insurance ••Customer 360 ••Fraud ••Compliance- GDPR ••Risk ••Operational Data Store ••Predictive analytics Telco Media Energy & Utilities ••Customer 360 ••Customer Insights ••Network Optimization ••Data Monetization ••EDW Augmentation ••Predictive maintenance Retail Ecommerce ••Personalized Customer offers ••Omni-channel Customer Experience ••Loyalty programs ••Next Best Offer/Action ••Recommendation Engine ••Agile Supply Chain Manufacturing Industrial ••Connected: Car, Plane, Equipment ••Agile Supply Chain ••Predictive Maintenance ••IoT Data enabled “Smart Services” Government Public Sector ••Border Control ••Risk / Intelligence ••360 Tax payer ••Tax Optimization ••Cyber Threat ••Fraud prevention Enterprise data warehouse(EDW) Modernization/ EDW Offload/Teradata Takeout/ Capabilities
- 15. IBM Cloud Embedded machine learning and data science Drive more value from your data. Run analytics where the data lives using the tools your data professionals prefer. § Spark and Jupyter notebooks built-in § Integration with model building, BI, and visualization tools Transactional and analytic processing —all in one place Instant insight from real-time operational data for growing revenue, reducing cost and lowering risk. § Simplify IT with transactions and reporting (HTAP) within the same system § Easy, low-risk offload from expensive data warehouse- Teradata or Oracle. Common SQL engine with built-in data virtualization Anchored by a common SQL engine to enable scalable data management solutions with portable analytics. § Application and operational compatibility § Provide transparent access to other data sources Support for on-premises or cloud, NoSQL or SQL Offers flexibility in choosing the form factor that best suits your business, enabling a controlled journey to the cloud. § A platform that fits your data strategy § Bridge data stores for seamless data integration IBM Big SQL for Hadoop- Data Federation across data repositories More intelligent analytics and insights Go at the speed of your business Write once, run anywhere, from any source Deploy your data where you need it
- 16. Governance for Hadoop and Data Lake to drive use cases like GDPR, PDPA… 16IBM Cloud / © 2018 IBM Corporation – Open and extensible platform – Brings structured and unstructured together – Scalability and parallel processing – Smarter metadata drives embedded governance – Pre-built industry data models – Unified platform with adaptive deployment and licensing 16 IBM BigQuality CDC for Hadoop IBM Big MatchIBM BigIntegrate IBM Industry Models Information lifecycle Master data & entity insights Governance, compliance & data protection Integration & replication Enterprise Information Catalog Structured & unstructured data AI & machine learning capabilities Public cloud On- premises Private cloud Know your data. Trust your data. Use your data. Trusted Analytics Foundation IBM Information Governance Catalog Key Offerings
- 17. IBM Cloud / © 2018 IBM Corporation IBM Data Science and Machine Learning Platform Gain deeper insights to see all contributing patterns Watson Explorer Report, monitor and analyze your data with confidence Watson Explorer Optimize plans based on prescriptions Decision Optimization Develop, deploy and manage models Data Science Experience Optimize business decisions Decision Optimization
- 18. Built-in learning to get started or go the distance with advanced tutorials Learn The best of open source and IBM value-add to create state-of-the-art data products Create Community and social features that provide meaningful collaboration Collaborate http://datascience.ibm.com IBM Data Science Experience • Find tutorials and datasets • Connect with Data Scientists • Ask questions • Read articles and papers • Fork and share projects • Watson Machine Learning • SPSS Modeler Canvas • Advanced Visualizations • Projects and Version Control • Managed Spark Service • Code in Scala/Python/R • Jupyter Notebooks • RStudio IDE and Shiny • Apache Spark • Your favorite libraries Predictive Power 100% Capacity Model Builder (CADS) Build model1 Deploy model2 Refresh model3 Import Sources: § DSx Notebooks § DSx Flow UI § External tools Auto-generate model from input data, testing various algorithms for best fit (e.g. CADS) Detect loss of predictive power and refresh model, subject to preferences Model ML Model Lifecycle
- 19. Open source is a powerful engine, but as with any engine, it needs the full system to accomplish any work § Security – SSO and code hardening to reduce security gaps § Version Currency – We keep up-to-date as open source quickly iterates § Data Connectivity – Connect to data sources § Scalability – Makes tools designed for desktops scalable to enterprise workloads § Enterprise IBM Support- World Class support by SMEs We provide:
- 20. 1.Digital and AI Challenges 2.How IBM Governed Data Lake can help? 3.Industry Use Cases 4.IBM Governed Data Lake Building blocks 1.Collect 2.Govern 3.Analyze (Data Science and ML) 5.How to start your Governed Data Lake journey
- 21. Data Science Sandbox Quick Start Solution 1. Receive best practices for your organizations to get started with governed data lake 2. Achieve faster time-to- value with pre-built accelerators 3. Leverage world-class data scientists and engineers with proven results at most mature big data and Data Science customers 12 Nodes of best in class Open Source Hadoop- IBM Hortonworks Data Platform 5 Users for IBM Data Science Experience 1 weeks of partner services engagement _________ = 75K USD* *Commercials for services from third party Partner Services *Commercials focused on Data Science environment for Governed Data Lake *Commercials may vary from local conditions and countries to countries *Offer valid till 31st March 2018 + +
- 22. Governed Data Lake – Quick Start Solutions
- 23. IBM is the industry leader in Open Source and Data Science platforms 23 40,000+ Clients in 160 countries, training 70,000+ client employees 43% Improvement in Client Satisfaction IBM Leadership - Total Portfolio 80% of reports, 60% of Forrester IBM Consensus Leader in Data Science & Business Analytics General Excellence reddot award Interface Design NPS 2017 Apache Committers Top 20 OPEN SOURCE
- 24. IBM Cloud Call To Action: • Identify the use case for your business Involve us for free Discovery workshop for Governed Data Lake. • Read, learn and Contribute at- • www.ibmbigdatahub.com • Write to us- [email protected]
- 25. Persist Analyze Ingest Deploy Projects | Data | Assets | Pipelines | APIs Intelligent governance | Policy enforcement What you need is a Integrated Platform based on Open Standards Our Core Tenets 1. Intelligent by Design 2. Collaborative for data Professionals 3. Self-service access to trusted data 4. Best in class streaming and real-time analytics 5. Open and Extensible Collaborate Data steward Data scientistData engineer Developer Find Share
- 26. IBM Big SQL Query Federation = virtualized data access Transparent § Appears to be one source § Programmers don’t need to know how / where data is stored Heterogeneous § Accesses data from diverse sources High Function § Full query support against all data § Capabilities of sources as well Autonomous § Non-disruptive to data sources, existing applications, systems. High Performance § Optimization of distributed queries SQL tools, applications Data sources Virtualized data
- 27. Use Case- Social Programs Organizations Need to Be Able to Turn Their Data into Actionable Information Gain a comprehensive view of a family’s ongoing needs and program results Match citizen’s needs to the right program or service Maximizing a limited budget Am I managing my resources effectively? 2. Outcomes Focused 3. Integrated Service Delivery 1. Citizen/ focused information
- 28. Governed Data Lake Reference Architecture Low Latency Data Feeds Reports, dashboards, apps Real Time Data Flow Kafka Apache NiFi Governance CDC for Hadoop Data Processing MapReduce Spark Analyze Big SQL Watson Explorer Ingest Sqoop Flume IBM Information Governance Catalog HDFS Atlas DSX Big Integrate Big Quality Big Match Yarn Streaming Data Text Data Applications Data Time Series Geo Spatial Relational Social Network Video & Image New / Enhanced Applications Automated Process Use cases Analytic Applications Watson Cloud Services ISV Solutions Alerts All Data Sources
- 29. Top 5 Best Practices to set up Governed Data Lake 2. Metadata management and Data Lineage 3. Cognitive Search in Natural Language 4. People: Data Engineers, Data Scientists, CDO and LOB Executives 5. Continuous Learning Incorporation with Feedback Loops 1. Use Case Generation and Prioritization: Make innovation central to business vision, strategy, and execution Five Key Recommendations to Innovate with Machine Learning and Big Data