The document provides an overview of leading big data companies in 2021 and the Apache Hadoop stack, including related Apache software and the NIST big data reference architecture. It lists over 50 big data companies, including Accenture, Actian, Aerospike, Alluxio, Amazon Web Services, Cambridge Semantics, Cloudera, Cloudian, Cockroach Labs, Collibra, Couchbase, Databricks, DataKitchen, DataStax, Denodo, Dremio, Franz, Gigaspaces, Google Cloud, GridGain, HPE, HVR, IBM, Immuta, InfluxData, Informatica, IRI, MariaDB, Matillion, Melissa Data
An Overview of All The Different Databases in Google CloudFibonalabs
Google cloud platform (GCP) is a high-performance infrastructure for cloud computing, data analytics, and machine learning. Google Cloud runs on the same infrastructure that Google uses for its end-user products like Google Search, Gmail, Google Drive, Google Photos, etc.
Microsoft Fabric is the next version of Azure Data Factory, Azure Data Explorer, Azure Synapse Analytics, and Power BI. It brings all of these capabilities together into a single unified analytics platform that goes from the data lake to the business user in a SaaS-like environment. Therefore, the vision of Fabric is to be a one-stop shop for all the analytical needs for every enterprise and one platform for everyone from a citizen developer to a data engineer. Fabric will cover the complete spectrum of services including data movement, data lake, data engineering, data integration and data science, observational analytics, and business intelligence. With Fabric, there is no need to stitch together different services from multiple vendors. Instead, the customer enjoys end-to-end, highly integrated, single offering that is easy to understand, onboard, create and operate.
This is a hugely important new product from Microsoft and I will simplify your understanding of it via a presentation and demo.
Agenda:
What is Microsoft Fabric?
Workspaces and capacities
OneLake
Lakehouse
Data Warehouse
ADF
Power BI / DirectLake
Resources
How to Swiftly Operationalize the Data Lake for Advanced Analytics Using a Lo...Denodo
Watch full webinar here: https://bit.ly/3mfFJqb
Presented at Chief Data Officer Live Series 2021, ASEAN (August Edition)
While big data initiatives have become necessary for any business to generate actionable insights, big data fabric has become a necessity for any successful big data initiative. The best-of-breed big data fabrics should deliver actionable insights to the business users with minimal effort, provide end-to-end security to the entire enterprise data platform, and provide real-time data integration while delivering a self-service data platform to business users.
Watch this on-demand session to learn how big data fabric enabled by Data Virtualization:
- Provides lightning fast self-service data access to business users
- Centralizes data security, governance, and data privacy
- Fulfills the promise of data lakes to provide actionable insights
Next Gen Analytics Going Beyond Data WarehouseDenodo
Watch this Fast Data Strategy session with speakers: Maria Thonn, Enterprise BI Development Manager, T-Mobile & Jonathan Wisgerhof, Smart Data Architect, Kadenza: https://goo.gl/J1qiLj
Your company, like most of your peers, is undoubtedly data-aware and data-driven. However, unless you embrace a modern architecture like data virtualization to deliver actionable insights from your enterprise data, the worth of your enterprise data will diminish to a fraction of its potential.
Attend this session to learn how data virtualization:
• Provides a common semantic layer for business intelligence (BI) and analytical applications
• Enables a more agile, flexible logical data warehouse
• Acts as a single virtual catalog for all enterprise data sources including data lakes
SQL Server 2012 Analysis Services introduces a new BI Semantic Model that provides a single data model for building BI solutions. This unified model supports both multidimensional and tabular data models, providing flexibility for users and developers. It also includes tools for designing, developing, and deploying sophisticated BI applications and enables fast analytical performance through features like Proactive Caching.
Product Analysis Oracle BI Applications IntroductionAcevedoApps
This document provides an overview and summary of Oracle Business Intelligence Applications version 1.0 from June 2013. It describes Oracle BI Applications as complete prebuilt BI solutions that deliver role-based intelligence across various data sources. It outlines the product's features such as new visualizations, interfaces, and mobile enhancements. It also describes the product components, including pre-mapped metadata, ETL processes, and pre-built metrics, dashboards and reports. The document discusses data access capabilities such as leveraging Oracle Data Integrator for ETL and various configuration and validation tools. It highlights new capabilities in Oracle Data Integrator and contrasts building a custom BI solution versus using Oracle BI Applications.
Microsoft® SQL Server® 2012 is a cloud-ready information platform that will help organizations unlock breakthrough insights across the organization and quickly build solutions to extend data across on-premises and public cloud, backed by mission critical confidence.
What are the features of SQL server standard editions.pdfDirect Deals, LLC
SQL Server Standard edition delivers core data management and business intelligence database for agencies and small organizations. It can help to process their applications and assists common advanced tools for on-premises and cloud-enabling effective database management with lesser IT resources. Visit Here: - https://www.directdeals.com/
Self service BI with sql server 2008 R2 and microsoft power pivot shortEduardo Castro
In this presentation we summarize BI improvements in SQL Server 2008 R2 and PowerPivot.
Regards,
Dr. Eduardo Castro
http://ecastrom.blogspot.com
http://comunidadwindows.org
This document discusses building cubes in SQL Server Analysis Services (SSAS) and PowerPivot. It covers cubes created manually in SSAS, auto-cubes created in PowerPivot, and cubes in the upcoming Denali release. PowerPivot allows users to analyze massive data volumes with Excel. Reporting Services and SharePoint can be used to publish and share PowerPivot reports. SSAS provides an advanced feature set for scalable cube design. Denali will converge cube technologies with its new BI Semantic Model.
Microsoft Fabric- An Introduction documentShatvikMishra1
Microsoft Fabric is an all-in-one analytics solution from Microsoft that covers data movement, data science, real-time analytics, and business intelligence. It includes several applications like Data Factory, Synapse, Power BI, and Data Activator. Microsoft Fabric has four key pillars: it provides a comprehensive analytics platform, uses a lake-centric and open architecture with its OneLake feature, empowers every business user by integrating with Office apps, and includes AI-powered features like the Copilot assistant.
The document discusses data mesh vs data fabric architectures. It defines data mesh as a decentralized data processing architecture with microservices and event-driven integration of enterprise data assets across multi-cloud environments. The key aspects of data mesh are that it is decentralized, processes data at the edge, uses immutable event logs and streams for integration, and can move all types of data reliably. The document then provides an overview of how data mesh architectures have evolved from hub-and-spoke models to more distributed designs using techniques like kappa architecture and describes some use cases for event streaming and complex event processing.
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...Denodo
Watch full webinar here: https://buff.ly/46pRfV7
This Denodo session explores the power of data virtualization, shedding light on its architecture, customer value, and a diverse range of use cases. Attendees will discover how the Denodo Platform enables seamless connectivity to various data sources while effortlessly combining, cleansing, and delivering data through 5 differentiated use cases.
Architecture: Delve into the core architecture of the Denodo Platform and learn how it empowers organizations to create a unified virtual data layer. Understand how data is accessed, integrated, and delivered in a real-time, agile manner.
Value for the Customer: Explore the tangible benefits that Denodo offers to its customers. From cost savings to improved decision-making, discover how the Denodo Platform helps organizations derive maximum value from their data assets.
Five Different Use Cases: Uncover five real-world use cases where Denodo's data virtualization platform has made a significant impact. From data governance to analytics, Denodo proves its versatility across a variety of domains.
- Logical Data Fabric
- Self Service Analytics
- Data Governance
- 360 degree of Entities
- Hybrid/Multi-Cloud Integration
Watch this illuminating session to gain insights into the transformative capabilities of the Denodo Platform.
IBM Cloud Pak for Data is a unified platform that simplifies data collection, organization, and analysis through an integrated cloud-native architecture. It allows enterprises to turn data into insights by unifying various data sources and providing a catalog of microservices for additional functionality. The platform addresses challenges organizations face in leveraging data due to legacy systems, regulatory constraints, and time spent preparing data. It provides a single interface for data teams to collaborate and access over 45 integrated services to more efficiently gain insights from data.
Analytics and Lakehouse Integration Options for Oracle ApplicationsRay Février
The document discusses various options for extracting data from Oracle Fusion and Oracle EPM Cloud applications for analytics purposes. It outlines using the Business Intelligence Cloud Connector (BICC) to extract data to object storage, which can then be loaded into Oracle Analytics Cloud (OAC) or Autonomous Data Warehouse (ADW) for analysis. For EPM Cloud, it notes using the EPM Automate REST API wrapper or Oracle Data Integrator Marketplace connector. The document provides an overview of tools like OAC, ADW, ODI, and OCI Data Integration that can help transform and model the data for analytics and machine learning.
Data Virtualization: Introduction and Business Value (UK)Denodo
This document provides an overview of a webinar on data virtualization and the Denodo platform. The webinar agenda includes an introduction to adaptive data architectures and data virtualization, benefits of data virtualization, a demo of the Denodo platform, and a question and answer session. Key takeaways are that traditional data integration technologies do not support today's complex, distributed data environments, while data virtualization provides a way to access and integrate data across multiple sources.
Power BI in Microsoft Fabric: Key Benefitsgsachindc
Power BI in Microsoft Fabric is an integration that enhances the capabilities of Power BI by leveraging the comprehensive data and analytics platform provided by Microsoft Fabric. Microsoft Fabric is designed to unify data integration, engineering, warehousing, and real-time analytics. Here are some key features and benefits of using Power BI within Microsoft Fabric:
Unified Data Platform:
Centralized Data Management: Fabric integrates data from various sources into a single platform, making it easier to manage and analyze data.
Seamless Data Integration: It provides tools for data ingestion, transformation, and integration, ensuring that data is consistent and readily available for analysis.
Enhanced Analytics:
Advanced Analytics Tools: Fabric offers advanced analytics capabilities, including machine learning and real-time analytics, which can be utilized directly within Power BI.
Real-Time Data Processing: With Fabric, Power BI can leverage real-time data processing, enabling users to create up-to-date and responsive dashboards.
Scalability and Performance:
Scalable Infrastructure: Fabric is built on a scalable infrastructure that supports large volumes of data and high-performance analytics, ensuring that Power BI reports and dashboards remain fast and responsive even with complex datasets.
Optimized Performance: Fabric's optimized data storage and processing mechanisms enhance the performance of Power BI reports.
Collaborative Environment:
Collaboration Tools: Fabric includes collaborative features that allow teams to work together on data projects, share insights, and build collective intelligence.
Data Governance: It offers robust data governance and security features, ensuring that data is managed and accessed in a controlled and compliant manner.
Integration with Other Microsoft Services:
Seamless Integration: Power BI in Fabric seamlessly integrates with other Microsoft services like Azure, Office 365, and Microsoft Teams, providing a cohesive ecosystem for data and analytics.
AI and Machine Learning Integration: Fabric supports the integration of AI and machine learning models, which can be used within Power BI to enhance data analysis and predictive capabilities.
Key Use Cases
Enterprise Reporting: Large organizations can use Power BI in Fabric to create comprehensive and scalable reporting solutions that aggregate data from multiple sources.
Real-Time Analytics: Businesses requiring real-time insights can leverage Fabric’s real-time data processing to create dynamic Power BI dashboards.
Advanced Data Analysis: Data scientists and analysts can use the integrated advanced analytics tools to perform in-depth analysis and visualize the results in Power BI.
Data-Driven Decision Making: With the integration of AI and machine learning, organizations can build predictive models and visualize their outcomes, aiding in strategic decision-making.
Getting Started
To get started with Power BI in Microsoft Fabric:
Set Up Microsoft Fabric: E
Building IoT and Big Data Solutions on AzureIdo Flatow
This document discusses building IoT and big data solutions on Microsoft Azure. It provides an overview of common data types and challenges in integrating diverse data sources. It then describes several Azure services that can be used to ingest, process, analyze and visualize IoT and other large, diverse datasets. These services include IoT Hub, Event Hubs, Stream Analytics, HDInsight, Data Factory, DocumentDB and others. Examples and demos are provided for how to use these services to build end-to-end IoT and big data solutions on Azure.
NLS Quest - BI Suite is a complete business intelligence solution that facilitates data integration, reporting, analysis, and dashboard setup through easy access to an organization's electronically stored data extracted in real-time. It provides flexible, reliable reporting and extractions through a drag-and-drop interface with high-level security and no modifications to the host database. The main components include N-Bridge for data extraction, reporting and dashboard designers, a data analysis engine, and a report server.
This white paper describes how BlueData enables virtualization of Hadoop and Spark workloads running on Intel architecture.
Even as virtualization has spread throughout the data center, Apache Hadoop continues to be deployed almost exclusively on bare-metal physical servers. Processing overhead and I/O latency typically associated with virtualization have prevented big data architects from virtualizing Hadoop implementations.
As a result, most Hadoop initiatives have been limited in terms of agility, with infrastructure changes such as provisioning a new server for Hadoop often taking weeks or even months. This infrastructure complexity continues to slow down adoption in enterprise deployments. Apache Spark is a relatively new big data technology, but interest is growing rapidly; many of these same deployment challenges apply to on-premises Spark implementations.
The BlueData EPIC software platform addresses these limitations, enabling data center operators to accelerate Hadoop and Spark implementations on Intel architecture-based servers.
For more information, visit intel.com/bigdata and bluedata.com
Unlock the Power of Your Data: A Comprehensive Guide to Microsoft Fabric by K...Data & Analytics Magazin
In the rapidly evolving landscape of data management and analytics, Microsoft Fabric emerges as the first comprehensive platform designed to address all your cloud data needs. Presented by Kratos BI, this guide delves into how Microsoft Fabric empowers organizations to transform raw data into actionable insights through seamless data engineering, analytics, and science workflows.
Microsoft Fabric is not just another tool; it’s a game-changer that integrates data warehousing, lakehouses, pipelines, and advanced analytics in a single, scalable solution. This platform is built to support enterprises of all sizes, combining the best qualities of data lakes and data warehouses to create a unified view of your data. With features like low-code and pro-code environments, Fabric caters to both beginners and advanced users, making it easier than ever to develop data solutions with minimal hand-coding or advanced customization.
A standout feature of Microsoft Fabric is its integration with Copilot, an AI-powered tool that enhances productivity by automating routine tasks and providing intelligent code suggestions. Whether you’re a data engineer, analyst, or scientist, Copilot helps streamline your workflows, allowing you to focus on generating insights rather than managing data.
Kratos BI, under the leadership of Chris Wagner, offers expert guidance through their comprehensive training resources available on platforms like YouTube and Microsoft Learn. Additionally, they foster a vibrant community of data enthusiasts, providing valuable networking opportunities and up-to-date knowledge on the latest in data solutions.
This guide is your key to understanding how Microsoft Fabric can transform your organization’s approach to data, enabling you to harness the full potential of your data assets for transformative success.
Pivotal Big Data Suite is a comprehensive platform that allows companies to modernize their data infrastructure, gain insights through advanced analytics, and build analytic applications at scale. It includes components for data processing, storage, analytics, in-memory processing, and application development. The suite is based on open source software, supports multiple deployment options, and provides an agile approach to help companies transform into data-driven enterprises.
LEGO EMBRACING CHANGE BY COMBINING BI WITH FLEXIBLE INFORMATION SYSTEMmyteratak
Lego implemented SAP's three-tier client-server system with a flexible IT infrastructure to help management better forecast and plan. The system includes a presentation layer, application layer, and database layer. It allows distributed access to the database from different locations. Some key business intelligence features in SAP's suite include tools for consolidating, analyzing, and providing access to vast amounts of data to help users make better decisions. While a distributed architecture with multiple databases improves scalability, fault tolerance, and workload distribution, it also increases security risks, requires more effort to ensure data quality and integrity, and has higher maintenance costs.
How SQL Server Can Streamline Database AdministrationDirect Deals, LLC
In addition to ensuring data integrity, this approach delivers heightened scalability and availability for critical data sets. Also, SQL Server 2022 has a variety of editions, such as SQL Server 2022 Standard and more. Now you must know that, by embracing this solution, businesses can effortlessly scale their operations, accommodating increased workloads and user demands without sacrificing responsiveness.
Read More: - https://www.directdeals.com/how-sql-server-can-streamline-database-administration
The BlueData EPIC™ software platform solves the challenges that can slow down and stall Big Data initiatives. It makes deployment of Big Data infrastructure easier, faster, and more
cost-effective – eliminating complexity as a barrier to adoption.
What Is Microsoft Fabric and Why You Should Care?
Unified Software as a Service (SaaS), offering End-To-End analytics platform
Gives you a bunch of tools all together, Microsoft Fabric OneLake supports seamless integration, enabling collaboration on this unified data analytics platform
Scalable Analytics
Accessibility from anywhere with an internet connection
Streamlines collaboration among data professionals
Empowering low-to-no-code approach
Components of Microsoft Fabric
Fabric provides comprehensive data analytics solutions, encompassing services for data movement and transformation, analysis and actions, and deriving insights and patterns through machine learning. Although Microsoft Fabric includes several components, this article will use three primary experiences: Data Factory, Data Warehouse, and Power BI.
Lake House vs. Warehouse: Which Data Storage Solution is Right for You?
In simple terms, the underlying storage format in both Lake Houses and Warehouses is the Delta format, an enhanced version of the Parquet format.
Usage and Format Support
A Lake House combines the capabilities of a data lake and a data warehouse, supporting unstructured, semi-structured, and structured formats. In contrast, a data Warehouse supports only structured formats.
When your organization needs to process big data characterized by high volume, velocity, and variety, and when you require data loading and transformation using Spark engines via notebooks, a Lake House is recommended. A Lakehouse can process both structured tables and unstructured/semi-structured files, offering managed and external table options. Microsoft Fabric OneLake serves as the foundational layer for storing structured and unstructured data
Notebooks can be used for READ and WRITE operations in a Lakehouse. However, you cannot connect to a Lake House with an SQL client directly, without using SQL endpoints.
On the other hand, a Warehouse excels in processing and storing structured formats, utilizing stored procedures, tables, and views. Processing data in a Warehouse requires only T-SQL knowledge. It functions similarly to a typical RDBMS database but with a different internal storage architecture, as each table’s data is stored in the Delta format within OneLake. Users can access Warehouse data directly using any SQL client or the in-built graphical SQL editor, performing READ and WRITE operations with T-SQL and its elements like stored procedures and views. Notebooks can also connect to the Warehouse, but only for READ operations.
An SQL endpoint is like a special doorway that lets other computer programs talk to a database or storage system using a language called SQL. With this endpoint, you can ask questions (queries) to get information from the database, like searching for specific data or making changes to it. It’s kind of like using a search engine to find things on the internet, but for your data stored in the Fabric system.
Creating a Dataflow in Power BI A Step by Step Guide.pptxSparity1
Learn how to create and manage dataflows in Power BI, from defining new tables to leveraging computed tables, linked tables, and CDM folders for efficient data transformation.
Ad
More Related Content
Similar to Comprehensive Guide for Microsoft Fabric to Master Data Analytics (20)
What are the features of SQL server standard editions.pdfDirect Deals, LLC
SQL Server Standard edition delivers core data management and business intelligence database for agencies and small organizations. It can help to process their applications and assists common advanced tools for on-premises and cloud-enabling effective database management with lesser IT resources. Visit Here: - https://www.directdeals.com/
Self service BI with sql server 2008 R2 and microsoft power pivot shortEduardo Castro
In this presentation we summarize BI improvements in SQL Server 2008 R2 and PowerPivot.
Regards,
Dr. Eduardo Castro
http://ecastrom.blogspot.com
http://comunidadwindows.org
This document discusses building cubes in SQL Server Analysis Services (SSAS) and PowerPivot. It covers cubes created manually in SSAS, auto-cubes created in PowerPivot, and cubes in the upcoming Denali release. PowerPivot allows users to analyze massive data volumes with Excel. Reporting Services and SharePoint can be used to publish and share PowerPivot reports. SSAS provides an advanced feature set for scalable cube design. Denali will converge cube technologies with its new BI Semantic Model.
Microsoft Fabric- An Introduction documentShatvikMishra1
Microsoft Fabric is an all-in-one analytics solution from Microsoft that covers data movement, data science, real-time analytics, and business intelligence. It includes several applications like Data Factory, Synapse, Power BI, and Data Activator. Microsoft Fabric has four key pillars: it provides a comprehensive analytics platform, uses a lake-centric and open architecture with its OneLake feature, empowers every business user by integrating with Office apps, and includes AI-powered features like the Copilot assistant.
The document discusses data mesh vs data fabric architectures. It defines data mesh as a decentralized data processing architecture with microservices and event-driven integration of enterprise data assets across multi-cloud environments. The key aspects of data mesh are that it is decentralized, processes data at the edge, uses immutable event logs and streams for integration, and can move all types of data reliably. The document then provides an overview of how data mesh architectures have evolved from hub-and-spoke models to more distributed designs using techniques like kappa architecture and describes some use cases for event streaming and complex event processing.
Denodo Partner Connect: A Review of the Top 5 Differentiated Use Cases for th...Denodo
Watch full webinar here: https://buff.ly/46pRfV7
This Denodo session explores the power of data virtualization, shedding light on its architecture, customer value, and a diverse range of use cases. Attendees will discover how the Denodo Platform enables seamless connectivity to various data sources while effortlessly combining, cleansing, and delivering data through 5 differentiated use cases.
Architecture: Delve into the core architecture of the Denodo Platform and learn how it empowers organizations to create a unified virtual data layer. Understand how data is accessed, integrated, and delivered in a real-time, agile manner.
Value for the Customer: Explore the tangible benefits that Denodo offers to its customers. From cost savings to improved decision-making, discover how the Denodo Platform helps organizations derive maximum value from their data assets.
Five Different Use Cases: Uncover five real-world use cases where Denodo's data virtualization platform has made a significant impact. From data governance to analytics, Denodo proves its versatility across a variety of domains.
- Logical Data Fabric
- Self Service Analytics
- Data Governance
- 360 degree of Entities
- Hybrid/Multi-Cloud Integration
Watch this illuminating session to gain insights into the transformative capabilities of the Denodo Platform.
IBM Cloud Pak for Data is a unified platform that simplifies data collection, organization, and analysis through an integrated cloud-native architecture. It allows enterprises to turn data into insights by unifying various data sources and providing a catalog of microservices for additional functionality. The platform addresses challenges organizations face in leveraging data due to legacy systems, regulatory constraints, and time spent preparing data. It provides a single interface for data teams to collaborate and access over 45 integrated services to more efficiently gain insights from data.
Analytics and Lakehouse Integration Options for Oracle ApplicationsRay Février
The document discusses various options for extracting data from Oracle Fusion and Oracle EPM Cloud applications for analytics purposes. It outlines using the Business Intelligence Cloud Connector (BICC) to extract data to object storage, which can then be loaded into Oracle Analytics Cloud (OAC) or Autonomous Data Warehouse (ADW) for analysis. For EPM Cloud, it notes using the EPM Automate REST API wrapper or Oracle Data Integrator Marketplace connector. The document provides an overview of tools like OAC, ADW, ODI, and OCI Data Integration that can help transform and model the data for analytics and machine learning.
Data Virtualization: Introduction and Business Value (UK)Denodo
This document provides an overview of a webinar on data virtualization and the Denodo platform. The webinar agenda includes an introduction to adaptive data architectures and data virtualization, benefits of data virtualization, a demo of the Denodo platform, and a question and answer session. Key takeaways are that traditional data integration technologies do not support today's complex, distributed data environments, while data virtualization provides a way to access and integrate data across multiple sources.
Power BI in Microsoft Fabric: Key Benefitsgsachindc
Power BI in Microsoft Fabric is an integration that enhances the capabilities of Power BI by leveraging the comprehensive data and analytics platform provided by Microsoft Fabric. Microsoft Fabric is designed to unify data integration, engineering, warehousing, and real-time analytics. Here are some key features and benefits of using Power BI within Microsoft Fabric:
Unified Data Platform:
Centralized Data Management: Fabric integrates data from various sources into a single platform, making it easier to manage and analyze data.
Seamless Data Integration: It provides tools for data ingestion, transformation, and integration, ensuring that data is consistent and readily available for analysis.
Enhanced Analytics:
Advanced Analytics Tools: Fabric offers advanced analytics capabilities, including machine learning and real-time analytics, which can be utilized directly within Power BI.
Real-Time Data Processing: With Fabric, Power BI can leverage real-time data processing, enabling users to create up-to-date and responsive dashboards.
Scalability and Performance:
Scalable Infrastructure: Fabric is built on a scalable infrastructure that supports large volumes of data and high-performance analytics, ensuring that Power BI reports and dashboards remain fast and responsive even with complex datasets.
Optimized Performance: Fabric's optimized data storage and processing mechanisms enhance the performance of Power BI reports.
Collaborative Environment:
Collaboration Tools: Fabric includes collaborative features that allow teams to work together on data projects, share insights, and build collective intelligence.
Data Governance: It offers robust data governance and security features, ensuring that data is managed and accessed in a controlled and compliant manner.
Integration with Other Microsoft Services:
Seamless Integration: Power BI in Fabric seamlessly integrates with other Microsoft services like Azure, Office 365, and Microsoft Teams, providing a cohesive ecosystem for data and analytics.
AI and Machine Learning Integration: Fabric supports the integration of AI and machine learning models, which can be used within Power BI to enhance data analysis and predictive capabilities.
Key Use Cases
Enterprise Reporting: Large organizations can use Power BI in Fabric to create comprehensive and scalable reporting solutions that aggregate data from multiple sources.
Real-Time Analytics: Businesses requiring real-time insights can leverage Fabric’s real-time data processing to create dynamic Power BI dashboards.
Advanced Data Analysis: Data scientists and analysts can use the integrated advanced analytics tools to perform in-depth analysis and visualize the results in Power BI.
Data-Driven Decision Making: With the integration of AI and machine learning, organizations can build predictive models and visualize their outcomes, aiding in strategic decision-making.
Getting Started
To get started with Power BI in Microsoft Fabric:
Set Up Microsoft Fabric: E
Building IoT and Big Data Solutions on AzureIdo Flatow
This document discusses building IoT and big data solutions on Microsoft Azure. It provides an overview of common data types and challenges in integrating diverse data sources. It then describes several Azure services that can be used to ingest, process, analyze and visualize IoT and other large, diverse datasets. These services include IoT Hub, Event Hubs, Stream Analytics, HDInsight, Data Factory, DocumentDB and others. Examples and demos are provided for how to use these services to build end-to-end IoT and big data solutions on Azure.
NLS Quest - BI Suite is a complete business intelligence solution that facilitates data integration, reporting, analysis, and dashboard setup through easy access to an organization's electronically stored data extracted in real-time. It provides flexible, reliable reporting and extractions through a drag-and-drop interface with high-level security and no modifications to the host database. The main components include N-Bridge for data extraction, reporting and dashboard designers, a data analysis engine, and a report server.
This white paper describes how BlueData enables virtualization of Hadoop and Spark workloads running on Intel architecture.
Even as virtualization has spread throughout the data center, Apache Hadoop continues to be deployed almost exclusively on bare-metal physical servers. Processing overhead and I/O latency typically associated with virtualization have prevented big data architects from virtualizing Hadoop implementations.
As a result, most Hadoop initiatives have been limited in terms of agility, with infrastructure changes such as provisioning a new server for Hadoop often taking weeks or even months. This infrastructure complexity continues to slow down adoption in enterprise deployments. Apache Spark is a relatively new big data technology, but interest is growing rapidly; many of these same deployment challenges apply to on-premises Spark implementations.
The BlueData EPIC software platform addresses these limitations, enabling data center operators to accelerate Hadoop and Spark implementations on Intel architecture-based servers.
For more information, visit intel.com/bigdata and bluedata.com
Unlock the Power of Your Data: A Comprehensive Guide to Microsoft Fabric by K...Data & Analytics Magazin
In the rapidly evolving landscape of data management and analytics, Microsoft Fabric emerges as the first comprehensive platform designed to address all your cloud data needs. Presented by Kratos BI, this guide delves into how Microsoft Fabric empowers organizations to transform raw data into actionable insights through seamless data engineering, analytics, and science workflows.
Microsoft Fabric is not just another tool; it’s a game-changer that integrates data warehousing, lakehouses, pipelines, and advanced analytics in a single, scalable solution. This platform is built to support enterprises of all sizes, combining the best qualities of data lakes and data warehouses to create a unified view of your data. With features like low-code and pro-code environments, Fabric caters to both beginners and advanced users, making it easier than ever to develop data solutions with minimal hand-coding or advanced customization.
A standout feature of Microsoft Fabric is its integration with Copilot, an AI-powered tool that enhances productivity by automating routine tasks and providing intelligent code suggestions. Whether you’re a data engineer, analyst, or scientist, Copilot helps streamline your workflows, allowing you to focus on generating insights rather than managing data.
Kratos BI, under the leadership of Chris Wagner, offers expert guidance through their comprehensive training resources available on platforms like YouTube and Microsoft Learn. Additionally, they foster a vibrant community of data enthusiasts, providing valuable networking opportunities and up-to-date knowledge on the latest in data solutions.
This guide is your key to understanding how Microsoft Fabric can transform your organization’s approach to data, enabling you to harness the full potential of your data assets for transformative success.
Pivotal Big Data Suite is a comprehensive platform that allows companies to modernize their data infrastructure, gain insights through advanced analytics, and build analytic applications at scale. It includes components for data processing, storage, analytics, in-memory processing, and application development. The suite is based on open source software, supports multiple deployment options, and provides an agile approach to help companies transform into data-driven enterprises.
LEGO EMBRACING CHANGE BY COMBINING BI WITH FLEXIBLE INFORMATION SYSTEMmyteratak
Lego implemented SAP's three-tier client-server system with a flexible IT infrastructure to help management better forecast and plan. The system includes a presentation layer, application layer, and database layer. It allows distributed access to the database from different locations. Some key business intelligence features in SAP's suite include tools for consolidating, analyzing, and providing access to vast amounts of data to help users make better decisions. While a distributed architecture with multiple databases improves scalability, fault tolerance, and workload distribution, it also increases security risks, requires more effort to ensure data quality and integrity, and has higher maintenance costs.
How SQL Server Can Streamline Database AdministrationDirect Deals, LLC
In addition to ensuring data integrity, this approach delivers heightened scalability and availability for critical data sets. Also, SQL Server 2022 has a variety of editions, such as SQL Server 2022 Standard and more. Now you must know that, by embracing this solution, businesses can effortlessly scale their operations, accommodating increased workloads and user demands without sacrificing responsiveness.
Read More: - https://www.directdeals.com/how-sql-server-can-streamline-database-administration
The BlueData EPIC™ software platform solves the challenges that can slow down and stall Big Data initiatives. It makes deployment of Big Data infrastructure easier, faster, and more
cost-effective – eliminating complexity as a barrier to adoption.
What Is Microsoft Fabric and Why You Should Care?
Unified Software as a Service (SaaS), offering End-To-End analytics platform
Gives you a bunch of tools all together, Microsoft Fabric OneLake supports seamless integration, enabling collaboration on this unified data analytics platform
Scalable Analytics
Accessibility from anywhere with an internet connection
Streamlines collaboration among data professionals
Empowering low-to-no-code approach
Components of Microsoft Fabric
Fabric provides comprehensive data analytics solutions, encompassing services for data movement and transformation, analysis and actions, and deriving insights and patterns through machine learning. Although Microsoft Fabric includes several components, this article will use three primary experiences: Data Factory, Data Warehouse, and Power BI.
Lake House vs. Warehouse: Which Data Storage Solution is Right for You?
In simple terms, the underlying storage format in both Lake Houses and Warehouses is the Delta format, an enhanced version of the Parquet format.
Usage and Format Support
A Lake House combines the capabilities of a data lake and a data warehouse, supporting unstructured, semi-structured, and structured formats. In contrast, a data Warehouse supports only structured formats.
When your organization needs to process big data characterized by high volume, velocity, and variety, and when you require data loading and transformation using Spark engines via notebooks, a Lake House is recommended. A Lakehouse can process both structured tables and unstructured/semi-structured files, offering managed and external table options. Microsoft Fabric OneLake serves as the foundational layer for storing structured and unstructured data
Notebooks can be used for READ and WRITE operations in a Lakehouse. However, you cannot connect to a Lake House with an SQL client directly, without using SQL endpoints.
On the other hand, a Warehouse excels in processing and storing structured formats, utilizing stored procedures, tables, and views. Processing data in a Warehouse requires only T-SQL knowledge. It functions similarly to a typical RDBMS database but with a different internal storage architecture, as each table’s data is stored in the Delta format within OneLake. Users can access Warehouse data directly using any SQL client or the in-built graphical SQL editor, performing READ and WRITE operations with T-SQL and its elements like stored procedures and views. Notebooks can also connect to the Warehouse, but only for READ operations.
An SQL endpoint is like a special doorway that lets other computer programs talk to a database or storage system using a language called SQL. With this endpoint, you can ask questions (queries) to get information from the database, like searching for specific data or making changes to it. It’s kind of like using a search engine to find things on the internet, but for your data stored in the Fabric system.
Creating a Dataflow in Power BI A Step by Step Guide.pptxSparity1
Learn how to create and manage dataflows in Power BI, from defining new tables to leveraging computed tables, linked tables, and CDM folders for efficient data transformation.
Which cloud service model is best suited for lift and shift migration.pptxSparity1
The Infrastructure as a Service (IaaS) model is best suited for lift and shift migration. It provides virtualized computing resources over the internet.
Magento 2.4.7 Version Upgrade Best Practices 2 (1).pptxSparity1
Best practices for magento version upgrade ! Ensure seamless transitions, enhanced security, and optimized performance. Let our guide lead you through the process.
Apparel Brand’s eCommerce Success with Magento Migration.pptxSparity1
Sparity empowered a spiritwear company with Magento migration for e commerce client with Navision ERP integration, boosting sales, and customer satisfaction.
Discover why Wi-Fi 7 is set to transform wireless networking and how Router Architects is leading the way with next-gen router designs built for speed, reliability, and innovation.
PDF Reader Pro Crack Latest Version FREE Download 2025mu394968
🌍📱👉COPY LINK & PASTE ON GOOGLE https://dr-kain-geera.info/👈🌍
PDF Reader Pro is a software application, often referred to as an AI-powered PDF editor and converter, designed for viewing, editing, annotating, and managing PDF files. It supports various PDF functionalities like merging, splitting, converting, and protecting PDFs. Additionally, it can handle tasks such as creating fillable forms, adding digital signatures, and performing optical character recognition (OCR).
Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev
If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic?
Trick question, b/c most can’t. They treat retrieval as nearest-neighbor search.
Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval.
GraphRAG builds a knowledge graph from source documents, allowing for a deeper understanding of the data + higher accuracy.
Exploring Wayland: A Modern Display Server for the FutureICS
Wayland is revolutionizing the way we interact with graphical interfaces, offering a modern alternative to the X Window System. In this webinar, we’ll delve into the architecture and benefits of Wayland, including its streamlined design, enhanced performance, and improved security features.
Explaining GitHub Actions Failures with Large Language Models Challenges, In...ssuserb14185
GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise.
https://arxiv.org/abs/2501.16495
Proactive Vulnerability Detection in Source Code Using Graph Neural Networks:...Ranjan Baisak
As software complexity grows, traditional static analysis tools struggle to detect vulnerabilities with both precision and context—often triggering high false positive rates and developer fatigue. This article explores how Graph Neural Networks (GNNs), when applied to source code representations like Abstract Syntax Trees (ASTs), Control Flow Graphs (CFGs), and Data Flow Graphs (DFGs), can revolutionize vulnerability detection. We break down how GNNs model code semantics more effectively than flat token sequences, and how techniques like attention mechanisms, hybrid graph construction, and feedback loops significantly reduce false positives. With insights from real-world datasets and recent research, this guide shows how to build more reliable, proactive, and interpretable vulnerability detection systems using GNNs.
This presentation explores code comprehension challenges in scientific programming based on a survey of 57 research scientists. It reveals that 57.9% of scientists have no formal training in writing readable code. Key findings highlight a "documentation paradox" where documentation is both the most common readability practice and the biggest challenge scientists face. The study identifies critical issues with naming conventions and code organization, noting that 100% of scientists agree readable code is essential for reproducible research. The research concludes with four key recommendations: expanding programming education for scientists, conducting targeted research on scientific code quality, developing specialized tools, and establishing clearer documentation guidelines for scientific software.
Presented at: The 33rd International Conference on Program Comprehension (ICPC '25)
Date of Conference: April 2025
Conference Location: Ottawa, Ontario, Canada
Preprint: https://arxiv.org/abs/2501.10037
AgentExchange is Salesforce’s latest innovation, expanding upon the foundation of AppExchange by offering a centralized marketplace for AI-powered digital labor. Designed for Agentblazers, developers, and Salesforce admins, this platform enables the rapid development and deployment of AI agents across industries.
Email: [email protected]
Phone: +1(630) 349 2411
Website: https://www.fexle.com/blogs/agentexchange-an-ultimate-guide-for-salesforce-consultants-businesses/?utm_source=slideshare&utm_medium=pptNg
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora
Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.
Adobe Lightroom Classic Crack FREE Latest link 2025kashifyounis067
🌍📱👉COPY LINK & PASTE ON GOOGLE http://drfiles.net/ 👈🌍
Adobe Lightroom Classic is a desktop-based software application for editing and managing digital photos. It focuses on providing users with a powerful and comprehensive set of tools for organizing, editing, and processing their images on their computer. Unlike the newer Lightroom, which is cloud-based, Lightroom Classic stores photos locally on your computer and offers a more traditional workflow for professional photographers.
Here's a more detailed breakdown:
Key Features and Functions:
Organization:
Lightroom Classic provides robust tools for organizing your photos, including creating collections, using keywords, flags, and color labels.
Editing:
It offers a wide range of editing tools for making adjustments to color, tone, and more.
Processing:
Lightroom Classic can process RAW files, allowing for significant adjustments and fine-tuning of images.
Desktop-Focused:
The application is designed to be used on a computer, with the original photos stored locally on the hard drive.
Non-Destructive Editing:
Edits are applied to the original photos in a non-destructive way, meaning the original files remain untouched.
Key Differences from Lightroom (Cloud-Based):
Storage Location:
Lightroom Classic stores photos locally on your computer, while Lightroom stores them in the cloud.
Workflow:
Lightroom Classic is designed for a desktop workflow, while Lightroom is designed for a cloud-based workflow.
Connectivity:
Lightroom Classic can be used offline, while Lightroom requires an internet connection to sync and access photos.
Organization:
Lightroom Classic offers more advanced organization features like Collections and Keywords.
Who is it for?
Professional Photographers:
PCMag notes that Lightroom Classic is a popular choice among professional photographers who need the flexibility and control of a desktop-based application.
Users with Large Collections:
Those with extensive photo collections may prefer Lightroom Classic's local storage and robust organization features.
Users who prefer a traditional workflow:
Users who prefer a more traditional desktop workflow, with their original photos stored on their computer, will find Lightroom Classic a good fit.
Adobe Master Collection CC Crack Advance Version 2025kashifyounis067
🌍📱👉COPY LINK & PASTE ON GOOGLE http://drfiles.net/ 👈🌍
Adobe Master Collection CC (Creative Cloud) is a comprehensive subscription-based package that bundles virtually all of Adobe's creative software applications. It provides access to a wide range of tools for graphic design, video editing, web development, photography, and more. Essentially, it's a one-stop-shop for creatives needing a broad set of professional tools.
Key Features and Benefits:
All-in-one access:
The Master Collection includes apps like Photoshop, Illustrator, InDesign, Premiere Pro, After Effects, Audition, and many others.
Subscription-based:
You pay a recurring fee for access to the latest versions of all the software, including new features and updates.
Comprehensive suite:
It offers tools for a wide variety of creative tasks, from photo editing and illustration to video editing and web development.
Cloud integration:
Creative Cloud provides cloud storage, asset sharing, and collaboration features.
Comparison to CS6:
While Adobe Creative Suite 6 (CS6) was a one-time purchase version of the software, Adobe Creative Cloud (CC) is a subscription service. CC offers access to the latest versions, regular updates, and cloud integration, while CS6 is no longer updated.
Examples of included software:
Adobe Photoshop: For image editing and manipulation.
Adobe Illustrator: For vector graphics and illustration.
Adobe InDesign: For page layout and desktop publishing.
Adobe Premiere Pro: For video editing and post-production.
Adobe After Effects: For visual effects and motion graphics.
Adobe Audition: For audio editing and mixing.
Designing AI-Powered APIs on Azure: Best Practices& ConsiderationsDinusha Kumarasiri
AI is transforming APIs, enabling smarter automation, enhanced decision-making, and seamless integrations. This presentation explores key design principles for AI-infused APIs on Azure, covering performance optimization, security best practices, scalability strategies, and responsible AI governance. Learn how to leverage Azure API Management, machine learning models, and cloud-native architectures to build robust, efficient, and intelligent API solutions
Who Watches the Watchmen (SciFiDevCon 2025)Allon Mureinik
Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe.
We often trust them with the safety of our codebase, but how do we know that we should? How do we know that this trust is well-deserved?
Enter mutation testing – by intentionally injecting harmful mutations into our code and seeing if they are caught by the tests, we can evaluate the quality of the safety net they provide. By watching the watchmen, we can make sure our tests really protect us, and we aren’t just green-washing our IDEs to a false sense of security.
Talk from SciFiDevCon 2025
https://www.scifidevcon.com/courses/2025-scifidevcon/contents/680efa43ae4f5
Interactive Odoo Dashboard for various business needs can provide users with dynamic, visually appealing dashboards tailored to their specific requirements. such a module that could support multiple dashboards for different aspects of a business
✅Visit And Buy Now : https://bit.ly/3VojWza
✅This Interactive Odoo dashboard module allow user to create their own odoo interactive dashboards for various purpose.
App download now :
Odoo 18 : https://bit.ly/3VojWza
Odoo 17 : https://bit.ly/4h9Z47G
Odoo 16 : https://bit.ly/3FJTEA4
Odoo 15 : https://bit.ly/3W7tsEB
Odoo 14 : https://bit.ly/3BqZDHg
Odoo 13 : https://bit.ly/3uNMF2t
Try Our website appointment booking odoo app : https://bit.ly/3SvNvgU
👉Want a Demo ?📧 [email protected]
➡️Contact us for Odoo ERP Set up : 091066 49361
👉Explore more apps: https://bit.ly/3oFIOCF
👉Want to know more : 🌐 https://www.axistechnolabs.com/
#odoo #odoo18 #odoo17 #odoo16 #odoo15 #odooapps #dashboards #dashboardsoftware #odooerp #odooimplementation #odoodashboardapp #bestodoodashboard #dashboardapp #odoodashboard #dashboardmodule #interactivedashboard #bestdashboard #dashboard #odootag #odooservices #odoonewfeatures #newappfeatures #odoodashboardapp #dynamicdashboard #odooapp #odooappstore #TopOdooApps #odooapp #odooexperience #odoodevelopment #businessdashboard #allinonedashboard #odooproducts
Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot
Towards a fairer, inclusive and sustainable AI that works for everybody.
Reviewing the state of the art on these challenges and what we're doing at LIST to test current LLMs and help you select the one that works best for you
Microsoft AI Nonprofit Use Cases and Live Demo_2025.04.30.pdfTechSoup
In this webinar we will dive into the essentials of generative AI, address key AI concerns, and demonstrate how nonprofits can benefit from using Microsoft’s AI assistant, Copilot, to achieve their goals.
This event series to help nonprofits obtain Copilot skills is made possible by generous support from Microsoft.
What You’ll Learn in Part 2:
Explore real-world nonprofit use cases and success stories.
Participate in live demonstrations and a hands-on activity to see how you can use Microsoft 365 Copilot in your own work!
Solidworks Crack 2025 latest new + license codeaneelaramzan63
Copy & Paste On Google >>> https://dr-up-community.info/
The two main methods for installing standalone licenses of SOLIDWORKS are clean installation and parallel installation (the process is different ...
Disable your internet connection to prevent the software from performing online checks during installation
Douwan Crack 2025 new verson+ License codeaneelaramzan63
Copy & Paste On Google >>> https://dr-up-community.info/
Douwan Preactivated Crack Douwan Crack Free Download. Douwan is a comprehensive software solution designed for data management and analysis.
Douwan Crack 2025 new verson+ License codeaneelaramzan63
Ad
Comprehensive Guide for Microsoft Fabric to Master Data Analytics
1. Sparity Soft Technologies
www.sparity.com
Comprehensive Guide for Microsoft Fabric to Master Data Analy in 2024
Introduction
Microsoft Fabric serves as a comprehensive analytics solution tailored for enterprises,
encompassing a wide spectrum from data movement and data science to real-time analytics
and business intelligence. This blog offers insight into what Microsoft Fabric entails and how
we can use it to enhance our data needs.
What is Microsoft Fabric and What’s in it??
Microsoft Fabric is an integrated analytics solution for enterprises, offering data movement,
science, real-time analytics, and business intelligence in a unified platform. Built on a
Software as a Service (SaaS) foundation, it amalgamates components from Power BI, Azure
Synapse, and Azure Data Factory, providing shared experiences, centralized administration,
and a unified data lake. Fabric includes components like Data Engineering, Data Factory,
Data Science, Data Warehouse, Real-Time Analytics, and Power BI. The platform is
structured around OneLake, a data lake built on Azure Data Lake Storage Gen2, eliminating
silos and enabling easy data sharing. It caters to ISVs with integration paths ranging from
basic connections to custom workload creation on the Fabric platform.
How to Enable Microsoft Fabric?
To enable Microsoft Fabric in Power BI for your organization, ensure prerequisites like
having admin roles such as Microsoft 365 Global admin, Power Platform admin, or Fabric
admin. Enable Microsoft Fabric for your entire tenant or a specific capacity through the
admin portal, allowing users to create Fabric items based on selected configurations. Security
groups can be utilized to control access. Consider that capacity admins can override tenant
settings. Disabling it restricts item creation but allows viewing permissions. Users without
Fabric access can still view items and icons in shared workspaces or capacities. Be mindful of
regional availability restrictions for Microsoft Fabric. Regularly check and manage settings
through the admin portal for optimal configuration.
Components of Power BI
A business intelligence tool by Microsoft called Power BI combines a multitude of data
services and connectors to produce an integrated set of visual insights from several data
sources. Along with Power BI Desktop for Windows and the Power BI online service, it also
includes mobile apps for iOS, Android, and Windows. Additional components include Power
BI Report Builder and Power BI Report Server. Depending on what they do, users access
different Power BI components. The workflows include connecting to Power BI Desktop data
sources, generating reports, and publishing them to the Power BI service for shared viewing.
Power BI Report Server allows deployment behind firewalls and supports on-premises report
administration.
2. Integration of OneLake in Fabric
OneLake, integrated with Microsoft Fabric, is a unified data lake designed for organizational
analytics, offering a single repository for diverse data types. Governed by default within
tenant boundaries, it supports collaborative distributed ownership through workspaces. Built
on Azure Data Lake Storage (ADLS) Gen2, OneLake is open and compatible with existing
applications and APIs. The OneLake file explorer for Windows simplifies data lake
interaction. Emphasizing one copy of data, it facilitates cross-domain data connections
through shortcuts, eliminating unnecessary duplication. Multiple analytical engines, such as
T-SQL and Spark, operate on data stored in Delta Parquet format, ensuring flexibility and
efficiency without data movement. Users can use Power BI's Direct Lake mode for seamless
reporting.
Data Features and Data Flows in Data Factory
Data Factory provides a modern data integration experience, allowing users to ingest,
prepare, and transform data from various sources. Fast Copy facilitates quick data movement,
which is crucial for bringing data to the Lakehouse and Data Warehouse in Microsoft Fabric.
The two primary features are dataflows and pipelines. Dataflows offer a low-code interface
with over 300 transformations, supporting easy data ingestion and transformation. Built on
the Power Query experience, it empowers users from citizens to professional data integrators.
Data pipelines enable cloud-scale workflow capabilities, allowing the creation of complex
ETL workflows with control flow logic. The configuration-driven copy activity and support
for various data tasks make it a versatile tool for end-to-end ETL data pipelines.
Maintaining Infrastructure with Data Engineering
Data Engineering empowers users to construct and maintain infrastructures for efficient data
collection, storage, processing, and analysis. Key components include lakehouses for unified
structured and unstructured data management, Apache Spark job definitions facilitating
batch/streaming job execution on Spark clusters, interactive notebooks for code creation and
sharing in various languages, and data pipelines crucial for reliable and scalable data
movement and transformation. This comprehensive suite ensures accessible, organized, and
high-quality data, with lakehouses supporting SQL-based queries, analytics, machine
learning, and advanced analytics techniques.
Structure of Data Science
Microsoft Fabric in Data Science streamlines end-to-end workflows, enabling users to
explore, clean, and model data for enriched insights. It facilitates seamless collaboration
between business analysts and data scientists. In problem formulation, collaboration is
enhanced, while data discovery involves OneLake integration for efficient data interaction.
The exploration phase utilizes tools like Apache Spark and Python, with Data Wrangler for
cleansing. Experimentation leverages PySpark, MLflow, and SynapseML for scalable
machine learning. Notebooks handle batch scoring, with results easily shared through Power
BI reports. The preview feature, Semantic Link, bridges the gap between Power BI semantics
and Synapse Data Science, fostering collaboration and accelerating productivity.
3. Data Warehouse for Greater Control
Microsoft Fabric offers a lake-centric data warehouse in two distinct experiences: the SQL
analytics endpoint and the Warehouse. The SQL analytics endpoint is a read-only,
automatically generated warehouse for T-SQL querying, supporting views and procedures. It
is part of the Lakehouse, facilitating data engineering and Spark usage. In contrast, the
Warehouse is a traditional data warehouse with full T-SQL capabilities, supporting
transactions, DDL, and DML queries. Both leverage open data formats, such as Delta, and
offer autonomous workload management. Virtual warehouses with cross-database querying
enable seamless integration of diverse data sources. The Warehouse provides greater control
and flexibility, while the SQL analytics endpoint offers simplicity and ease of use.
Streamlining Real Time Analytics
Real-Time Analytics in Microsoft Fabric simplifies data integration, enabling scalable
analytics for diverse users. It offers quick insights through automatic streaming, indexing,
and on-demand visualizations. Its unique features include real-time event capture, versatile
data structure support, and seamless Fabric integration. Industries like finance and
transportation benefit across various applications. Users leverage it for high-freshness data,
transforming streaming data, and querying large datasets with low latency. Integration with
Eventstream, KQL database, and Power BI facilitates end-to-end analysis.
Automated actions through Data Activator
Data Activator, currently in preview on Microsoft Fabric, offers a no-code experience for
automated actions based on changing data patterns. It monitors Power BI reports and
Eventstreams, triggering actions like alerts or Power Automate workflows on specified
thresholds or patterns. Users can create a digital nervous system without relying on IT or
developers, addressing issues like declining sales, proactive logistics management, and
customer retention. Core concepts include Events (data streams), Objects (monitored
entities), Triggers (conditions for actions), and Properties (reuseable logic). This empowers
business users to self-serve, reducing dependence on costly internal teams for monitoring and
alerting solutions.
Copilot Generative AI’s Capabilities
Microsoft Fabric's Copilot in preview offers AI-enhanced tools for data science, data
engineering, and Power BI. It facilitates code completion, automates tasks, and provides
templates for data professionals. Copilot follows responsible AI standards, storing customer
data for 30 days on Azure OAI. Admins must enable Copilot, and users should review
outputs for accuracy. It currently performs best in English, with potential limitations in other
languages. Prebuilt AI services are available in specific Azure regions. Check out our
comprehensive guide to Copilot in Power BI.
Fabric’s Retail Data Solutions
Microsoft Fabric's Retail Data Solutions empower retailers to enhance operational efficiency
and customer satisfaction by addressing challenges such as managing vast data volumes,
overcoming application silos, and ensuring real-time responsiveness. Through a standardized
data model, connectors, and business intelligence capabilities, retailers can unify and analyze
4. diverse data sources, driving insights for inventory optimization, customer segmentation, and
dynamic pricing. Additional features include a retail industry data model, Copilot template
for personalized shopping, Sitecore OrderCloud connector, and frequently bought together
recommendations, enabling retailers to make strategic decisions and deliver exceptional value
in a competitive market.
Conclusion
As Microsoft Fabric already hits the market, businesses can leverage its capabilities for all
their data requirements. While Fabric makes our work easy, we cannot perform every single
task with Copilot; you need an expert team of data engineers who are skilled in Fabric and
Power BI. Sparity will be your perfect partner who is an expert in data science, data
engineering, and data visualization, leveraging Power BI with our expert Power BI team.
Contact us today for all your data requirements.