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Introduction

In today’s data-driven world, businesses are increasingly turning to business intelligence (BI) solutions to gain insight from their data. BI solutions can help businesses improve their decision-making, optimize their operations, and gain a competitive edge.

Microsoft Fabric is an all-in-one cloud-based analytics platform that provides a unified environment for data professionals and business users to collaborate on data solutions. It is a powerful analytics platform that helps businesses automate workflows, improve productivity, and gain insight from their data.

What to expect

This newsletter will take you on a journey to discover the transformative power of Microsoft Fabric for business intelligence solutions. You will explore the various workloads and experiences that Microsoft Fabric offers, gaining a comprehensive understanding of its capabilities. You will also uncover the benefits that Microsoft Fabric brings to data-driven decision-making, enabling you to make informed choices that propel your business forward. Finally, you will delve into the potential that Microsoft Fabric holds for enhancing business intelligence solutions, empowering you to unlock new levels of insight and decision-making capabilities.

To dive even deeper, watch the webinar recording about this topic for free. Click here to register.

What is Microsoft Fabric?

Microsoft Fabric is an all-in-one cloud-based analytics platform that provides a unified environment for data professionals and business users to collaborate on data solutions. Fabric offers a suite of integrated services that enable you to collect, store, process, and analyze data in a single platform, which is built on a foundation of Software-as-a-Service (SaaS).

Microsoft Fabric provides tools for people with all levels of data expertise and connects with the tools businesses use to make decisions.
Fabric itself is an umbrella for the following Microsoft cloud-based services that constitute Microsoft Analytics Portfolio:

  • Azure Data Factory
  • Azure Event Hubs
  • Azure Data Explorer
  • Azure Artificial Intelligence
  • Azure Databricks
  • Azure Synapse Spark Pools
  • Azure Synapse Analytics
  • and Microsoft Power BI

The above items have been re-tooled and taken to the next level inside the Microsoft Fabric.

Workloads of Microsoft Fabric

Fabric includes the following workloads or experiences:

  • Data integration
  • Data engineering
  • Data warehousing
  • Data Science
  • Real-time analytics
  • Business intelligence
  • Insight to action

The foundation of these experiences in Fabric is the data lake, which is known as OneLake. The below picture illustrates the concept of Microsoft Fabric.

Let’s review every component of Fabric in a bit more detail.

Data Integration

Microsoft Fabric’s data integration workload, called Data Factory, brings data movement capabilities to both dataflows and data pipelines.

  • Dataflows offer flexible and user-friendly ways to transform data with over 300 transformations. It is built on the familiar Power Query experience, which is available in several Microsoft products and services, such as Excel, Power BI, Power Platform, and others.
  • Data pipelines let you create flexible data workflows to meet your organizational goals. You can use the built-in data orchestration features to refresh your dataflows, process large datasets, and define complex control flow pipelines.

Data Engineering

Data Engineering experience or Synapse Data Engineering offers a top-tier Spark platform, fostering rich authoring experiences. This empowers data engineers to conduct extensive data transformations and facilitate widespread access to data via the lakehouse.

Microsoft Fabric provides various data engineering capabilities to ensure that your data is easily accessible, well-organized, and of high-quality. From the data engineering homepage, you have the following options:

  • Lakehouse
    Create and manage Lakehouse. Lakehouse is a logical location in OneLake where you store and manage structured and unstructured data using various tools and frameworks. You can even mount an external storage account into your Lakehouse with the Shortcut feature.
    You can use the SQL Endpoint to query Lakehouse tables, but only read-only queries are supported.
  • Notebook
    Write and run code in popular programming languages, like Python, R, and Scala. Leverage notebooks for data ingestion, transformation, analysis, and other data processing tasks.
  • Environment
    Within an environment, you have the flexibility to choose from a variety of Spark runtimes, configure your computational resources, and incorporate libraries – either from public repositories or by uploading locally-built custom libraries. Attaching these environments to your notebooks and Spark job definitions is a seamless process.
  • Spark Job Definition
    Define, schedule, and manage Spark jobs to process big data in your lakehouse, apply transformation logic to the data, and more.
  • Data pipeline
    Design and orchestrate pipelines to copy data into your lakehouse, schedule Spark jobs and notebooks to process high-volume data, and automate data workflows via integration with Data Factory.

Data Warehousing

Data warehouse or Synapse Data Warehouse is a lake-centric repository for storing and analyzing structured data built on a distributed processing engine. Data warehousing workload benefits from the rich capabilities of the SQL engine over an open Delta Lake format, which are parquet files published as Delta Lake Logs and stored in OneLake. Delta Lake Logs enable ACID transactions. A warehouse can contain only structured data. Here you can not only read data with SQL but also execute inserts and updates.

Data Science

The Data Science experience, or Synapse Data Science, allows for the creation, deployment, and operationalization of machine learning models. Data scientists are empowered to enrich organizational data with predictions and allow business analysts to integrate those predictions into their BI reports. Data Science in Fabric provides you with the following options:

  • ML model
    Leverage machine learning models to forecast results and identify irregularities within datasets.
  • Experiment
    Engage in the experimentation phase by generating, executing, and monitoring the evolution of various models for validating hypotheses.
  • Notebook
    Utilize the Notebook feature to delve into data exploration and construct machine learning solutions through Apache Spark applications.
  • Environment
    This option has the same purpose as in Data Engineering experience.

Real-Time Analytics

Real-Time Analytics in Fabric or Synapse Real-Time Analytics is a fully-managed big data analytics platform optimized for streaming and time-series data. It utilizes a Kusto Query Language (KQL) — an engine with exceptional performance for searching structured, semi-structured, and unstructured data. Real-Time Analytics is fully integrated with the entire suite of Fabric products for data loading, data transformation, and advanced visualization scenarios. There are three components of the Real-Time Analytics in Fabric:

  • KQL Database — the place to store streaming data. It uses OneLake as the underlying storage system.
  • KQL Queryset — run queries on your data to produce shareable tables and visuals. Save, manage, export, and share KQL queries. KQL Queryset is an analog of SSMS for a SQL Database.
  • Eventstream — capture, transform, and route real-time event stream to various destinations in desired format with no-code experience. It is a hub of streaming data, where multiple sources (including Event Hub) and various destinations (including KQL database) can be set.

Business Intelligence

From the BI side, Fabric has Power BI, one of the world’s leading Business Intelligence platforms. It represents a set of services, tools, and connectors that turn your data into interactive visual reports and dashboards. In Fabric, there are some new features and enhancements to work with Fabric objects and experiences. Among these are:

  • Direct Lake mode connection that is based on loading parquet-formatted files directly from a data lake without the need to import the data into a data set.
  • Integration with Synapse Real-Time Analytics to produce real- or near-real-time reports.
  • Semantic link that allows loading data from Power BI data sets into Data Science experience and others.

Insight to Action

Insight to action in Fabric offers Data Activator, which is an experience for automatically triggering actions when certain conditions are met in the incoming data. It works with Eventstreams for real-time data and Power BI for batch data. There are three possible actions that can be configured after the conditions are detected:

  • Email — get notified by email.
  • Teams message — send notification to an individual or a channel in Teams.
  • Custom action — perform a custom action to call Power Automate workflow.

Data Lake

OneLake is the central component of all Fabric services. It is a built-in, unified data lake that stores all organizational data and is used by all Fabric experiences. OneLake uses ADLS Gen2 as its underlying storage.

To simplify management across the organization, OneLake is organized hierarchically. Each tenant has only one OneLake instance, which provides a single namespace that extends over users, regions, and even clouds. For easy handling, data in OneLake is divided into manageable containers.

Similar to Microsoft OneDrive, any developer or business unit in the tenant can create their own workspaces in OneLake. They can ingest data into their own lakehouses, start processing, analyzing, and collaborating on the data. All Fabric experiences are bound to and operate on top of OneLake.

So What Are the Potentials?

Microsoft Fabric has the potential to revolutionize the way that businesses build and deploy business intelligence solutions. Here are some of the key potentials:

  • Unified data platform: Microsoft Fabric provides a unified data platform for storing and analyzing all types of data, including structured, semi-structured, and unstructured data. This means that businesses can use a single set of tools and services to manage all aspects of their data pipeline, from data ingestion and preparation to data analysis and visualization. This can help to reduce complexity and improve efficiency.
  • End-to-end analytics: Microsoft Fabric provides a complete set of capabilities for building and deploying end-to-end analytics solutions. This includes data engineering, data science, data warehousing, and business intelligence. This simplifies the development and deployment of analytics solutions and reduces the need for specialized expertise.
  • AI-powered insights: Microsoft Fabric embeds AI and machine learning capabilities throughout the platform. This can be used to automate tasks, generate insights, and improve the accuracy of predictions. This can help businesses to make better decisions faster.
  • A unified platform accommodating diverse expertise: Data professionals with varying backgrounds can leverage their skill sets to collaborate on a singular data solution. This inclusive environment allows individuals from different disciplines and proficiency levels to contribute their expertise to a common data project.
  • Reduced data silos: It eliminates the need to to move data between various systems, making it easier to get a complete view of your business.
  • Reduced costs: Microsoft Fabric can help businesses reduce the costs associated with building and deploying business intelligence solutions. This is because it eliminates the need to purchase and maintain multiple systems and it provides a number of features that can automate tasks and improve efficiency.

In essence, Microsoft Fabric holds the promise of simplifying and rendering the development and deployment of robust business intelligence solutions more accessible and cost-effective for businesses, regardless of their scale or size.

Conclusion

Microsoft Fabric represents a paradigm shift in the realm of business intelligence solutions. With its unified data platform, end-to-end analytics capabilities, and AI-driven insights, Fabric streamlines data management from collection to visualization. The platform’s ability to cater to diverse skill sets and backgrounds, reducing data silos, and automating tasks illustrates a remarkable potential to revolutionize the industry.

Through its components, such as Data Factory, Data Engineering, Data Warehousing, Data Science, Real-Time Analytics, Power BI, Data Activator, and the robust foundation of OneLake, Microsoft Fabric promises a future where businesses can efficiently harness the power of data to make informed decisions and drive innovation. Ultimately, it has the potential to democratize powerful business intelligence solutions, making them more accessible and cost-effective for enterprises of all scales.

 

– Dmytro Polishchuk (Scalefree)

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To support the creation of Visual Data Vault drawings in Microsoft Visio, a stencil is implemented that can be used to draw Data Vault models. The stencil is available at www.visualdatavault.com.

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