Do you, too, ever feel like something is holding back your business from becoming data-driven?
It might simply be your fragmented data ecosystem.
What if we told you one tool can handle your data science, data engineering, reporting, and real-time analytics? Microsoft Fabric can bring about a monumental shift in unifying every stage of your data analytics lifecycle.
But of course, why would you choose this particular tool over the dozen others floating around the market?
For starters, the global data fabric market size is forecast to grow from USD 2.29 billion in 2023 to USD 12.91 billion by 2032 at a staggering CAGR of 21.2%.
Additionally, Ms Fabric is among the most trusted names for data protection. It’s indispensable for companies adopting more secure data management tools.
Let’s tap into some key answers around this platform, beginning with one: ‘What is Microsoft Fabric?’ and moving to its features, benefits, working process, and more.
Microsoft Fabric is a unified data analytics platform that’s completely enterprise-ready. It unifies data movement, processing, transformation, ingestion, report building, and real-time event routing. It supports these capabilities through various integrated services. The purpose is to enable data and business professionals to tap into the unprecedented potential for the evolving Artificial intelligence (AI) era.
The global data fabric market size is forecast to grow from USD 2.29 billion in 2023 to USD 12.91 billion by 2032 at a staggering CAGR of 21.2%.
Microsoft Fabric is among the most trusted names for data protection. It has become indispensable for companies adopting more secure data management tools. This article covers some key answers, beginning with one: ‘What is Microsoft Fabric?’
TL;DR
- Microsoft Fabric is an all-in-one, SaaS-oriented analytics solution that unifies various services—data lake, data engineering, real-time analytics, and business intelligence—under a simplified platform.
- OneLake is the core of Microsoft Fabric. It is the single, logical data lake for unified storage, breaking down data silos, reducing duplication, and simplifying management across the organization.
- The key features of Ms Fabric include a 360-degree analytics platform, deep integration with AI/Copilot for code generation, a lake-centric approach, and robust security and governance via Microsoft Purview.
- Its architecture consolidates specialized workloads like Data Factory (for pipelines), Synapse Data Engineering (for Spark transformations), Synapse Data Warehouse (for SQL scalability), and Power BI (for visualization).
- The platform is used to simplify the data ecosystem and drive specific business outcomes across industries, such as enabling real-time analytics in retail, financial risk analysis, and predictive maintenance in manufacturing.
What is Microsoft Fabric?
Microsoft Fabric pertains to an all-in-one SaaS-oriented (Software-as-a-Service) analytics solution that amalgamates a 360-degree suite of services. Its list of services includes data lake, data integration, data engineering, real-time analytics, business intelligence, and data science—all under the same roof.
It is built atop three central services and tools in MS, namely Azure Synapse Analytics, Power BI, and Azure Data Factory. Giants, including EY, KPMG, and Hitachi, have already incorporated Microsoft Fabric into their operations and are reaping the benefits.
OneLake: The Core of Microsoft Fabric
To truly understand Microsoft Fabric, let’s see what lies at its core – OneLake.
OneLake is a single, logical data lake for unified storage, utilizing Azure Data Lake Storage Gen2 (ADLS Gen2) to store information in Delta Parquet format. The data stored on this lake is accessible through Windows Explorer, URIs, or APIs in the Fabric tenant.
Organizations often have separate teams for these services that maintain platforms and analytics solutions. The process is hectic and chaotic.
But not with Microsoft Fabric’s OneLake.
OneLake breaks down data silos by unifying everything into a single platform, reducing duplication, simplifying management, and minimizing costs.
Data engineers, administrators, and developers break free from having to work with multiple tools.
It results in accelerated productivity and higher time to value while making it easier to bring AI to data.
Key Features of OneLake
Organizational data enters distributed ownership for easier sharing, without having to fret about duplication. Here are its key features:
• Shortcuts
Your teams can efficiently share data with other users and applications without duplication.
• Open at all Levels
Since it is built on ADLS Gen2, it supports all file types. Every architectural component of this platform automatically stores its data here.
• Data Mesh & Domains
Your business groups can access data for logical and efficient management.
• Scalable
It works well with humongous data sets that are ever-scaling. It thus leads to efficient machine learning and data analysis.
Choose Aegis Softtech’s Microsoft Fabric consulting services to stay ahead by strategically using your data for the most impactful business decisions.
Microsoft Fabric Features
Microsoft Fabric is built to simplify your entire data ecosystem. It empowers all your teams with the tools they need to achieve value from data.
But how exactly does it do this? Its extensive list of features holds the answer.
Here’s a look at some of the features that make it stand out:
1. A 360-Degree Analytics Platform
Traditionally, a data pipeline utilizes various tools for distinct analytics phases, including ingestion, storage, transformation, analysis, and visualization. Fabric, however, works on the raw data it extracts to integrate all these functions into a single platform for a 360-degree analysis.
2. Artificial Intelligence
Microsoft Fabric is integrated with the latest AI functionality, Azure OpenAI, and GitHub Copilot. Developers also utilize this integration to apply the wonders of generative AI to client data for better user productivity and interactions. Built-in AI assistants enable higher engagement through natural language.
Since Copilot is heavily integrated into all Fabric data experiences, users can easily use conversational language to build ML models and generate code and functions. It can visualize findings while developing dataflows and pipelines.
3. Lake-Centric
Its lake-centric approach addresses some of the key issues around data fragmentation. OneLake, its unified SaaS data lake, supports its various tools and works as a single storage location.
Your teams can manage their data through this repository. Thus, making data easily discoverable, shareable, and highly collaborative.
4. Integrated Services
Fabric works around workloads, which are deeply connected for diverse data analytics capabilities. You no longer have to work with separate tools for every data task, eliminating the complicated ETL (extract, transform, load) processes.
Workloads also share compute and other resources for optimized cost and efficiency.
5. Empowers Business Users
Explore and analyze your data seamlessly with its deep integration with Microsoft Office, Power BI, and other applications without moving or duplicating data. It has given a new meaning to data monitoring, especially in real-time and from multiple sources, including Synapse, lakes, and Power BI.
6. Security and Governance
Fabric and Microsoft Purview integration ensures that security policies protect your data from ingestion to visualization. Governance is at the center of this platform, reflected in its column-level security and role-based access, so the right user can access the right data.
Microsoft Fabric Architecture – Key Components
Built on a SaaS platform, Microsoft Fabric impeccably unifies existing and new components from Azure Synapse Analytics, Power BI, Azure Data Factory, and many others into a single environment. Each workload is tailored for different user roles, serving an exclusive purpose.
Let’s understand the key components of Microsoft Fabric architecture for a more detailed view.
1. Data Factory
The Data Factory workload is the best of Azure Data Factory and low-code experience in Power Query. The goal is to set up data pipelines/flow as a part of data engineering.
It has 150+ connectors that aid in integrating data from many different on-premise and cloud sources (like on-premises data warehouses, SaaS applications data, cloud data lakes, etc.). It streamlines data pipeline orchestration and automates data transformation.
2. Synapse Data Engineering
The data engineering workload transforms data through Apache Spark, which scales distributed data processing, while supporting leading programming languages like SQL, Python, and others.
It fosters an interactive development environment for team members to share code in a collaborative space.
3. Synapse Data Warehouse
The data warehouse (DWH) workload offers unprecedented SQL scalability and performance. It segregates storage and computing in a structured format for independent scaling.
If your workload often requires detailed historical analysis and data exploration, this workload will be highly useful.
4. Synapse Real-Time Analytics
The data category is growing at a faster rate. In this situation, Synapse real-time analytics is a brilliant engine to evaluate observational data from sources, including telemetry, logs, and IoT devices.
With Kusto Query Language (KQL) as its foundation, analyzing gigantic volumes of semi-structured data becomes much easier.
5. Synapse Data Science
The data science workload proves its worth when building, operationalizing, and deploying ML models in the Fabric sphere. It works in line with Azure machine learning for built-in model registry and experiment tracking.
Data scientists use the secured data prepared earlier by the data engineering teams. It comes with built-in ML tools, supports the R language, and supports MLFlow.
6. Data Activator
Data Activator workload is a no-code product for observing and monitoring data in real-time. It detects conditions to automate action triggers according to the data changes. It connects seamlessly with multiple data sources to continuously monitor incoming data.
Different actions automatically get triggered when the outlined conditions are met, saving time and resources.
7. Power BI
Power BI sits at the core of MS Fabric’s BI workload. Users can easily connect to different data sources, share their findings, and visualize necessary insights. Its intuitive interface helps create interactive data visualizations for clear and easy understanding of the insights for technical and non-technical audiences.
The Microsoft Fabric architecture and its components come together to allow organizations to unlock new possibilities.
What is Microsoft Fabric Used for?
Fabric can simply be conceptualized by understanding its purpose—simplicity.
Organizations use this tool to accumulate data from multiple sources into a single environment. It paves the path for diverting focus on outcomes instead of the tools and technologies employed.
Here are a few aspects explaining what Microsoft Fabric is used for and its capabilities:
1. Real-time Analytics for Retail
Retailers use this tool for analyzing sales, customer engagement, and real-time inventory data. Companies can collate data from multiple sources, like online sales, customer behavior, and POS systems.
2. Financial Risk Analysis
Financial institutions use Fabric’s data processing and artificial intelligence tools for assessing risk. They do so by analyzing humongous datasets from market conditions, external economic factors, and even customer portfolios. The outcome is faster and way more accurate risk models, along with portfolio optimization.
3. Predictive Maintenance in Manufacturing
Manufacturers collect data from various IoT devices and machinery sensors for predictive maintenance. Its machine learning features help such companies forecast equipment failures and optimize maintenance schedules.
4. Supply Chain Optimization
The tool centralizes data from suppliers, distributors, and logistics partners. The data is then analyzed for forecasting demand, monitoring supplier performance, and optimizing delivery routes in real-time. It is a big help in optimizing the supply chain for organizations.
5. Personalized Customer Experiences
Telecommunications and online services providers are heavily using Fabric for analyzing their customer interaction data. This analysis leads to personalized customer journeys. AI models are helpful when optimizing content delivery, improving engagement across channels, and predicting customer preferences.
6. Patient Data Analysis in Healthcare
Healthcare organizations accurately analyze their patient data and manage medical research. With all the data in one place, they can strengthen patient care and clinical outcomes to make better decisions.
Patient records are flagged as sensitive information and require a certain level of security. Fabric’s OneLake is the right place to secure this information.
Benefits of Microsoft Fabric
An organization that understands the ‘why’ behind something always stays ahead in the competition. To effectively utilize your data, you must first understand the benefits of Microsoft Fabric.
Here are the top ones to know about:
1. Streamlined Data Management
While data management traditionally encompassed using various tools and platforms, Fabric drastically simplifies the process. It takes a streamlined approach through its centralized platform, improving efficiency manifold while bringing down the associated cost.
2. Shorter Time to Insights
Data, nowadays, is valid only for very short periods, and decisions should be made faster. Fabric automates data pipelines for quick integration. Even non-technical users can independently generate basic reports.
3. Highly Flexible
Every user or team within an organization plans on using the data differently, even though for the same outcome. Fabric’s user-friendly interfaces add to its openness and interoperability.
4. Scalable & Resilient
No amount of surges or failures in demand can shake the smooth undertaking of operations. The unified SaaS platform practically and intelligently distributes workloads throughout the nodes for the best outcomes in all situations.
5. Hybrid Cloud Deployment
There is simply no confinement to any single environment. Organizations can deploy their apps on the Azure cloud, on-premises, or just about any other cloud provider.
Top Microsoft Fabric Alternatives
When it comes to looking for alternatives, the cost of Microsoft Fabric becomes an influencing factor for the decision makers, especially in SMBs and startups.
Your evolving data needs require a supportive platform, and if Fabric doesn’t suit those for any reason whatsoever, there are some other options as well.
Let’s explore the top alternatives to Microsoft Fabric.
• Databricks Lakehouse Platform
Databricks is a popular data analytics platform that unifies the capabilities of data warehouses and data lakes into a lakehouse architecture. Organizations can benefit from its collaborative environment to process huge data quantities for high scalability and performance.
Differences between Fabric and Databricks have been a debate for many organizations. Databricks offer benefits, such as auto-scaling and high performance with huge datasets. However, setting it up is not an easy task, which means more technical guidance and increased costs.
• Snowflake
Snowflake is a cloud-based data platform with a decoupled architecture, segregating the compute and storage layers. It can impressively handle gigantic data workloads, making it an asset for large organizations.
There are various differences between Snowflake and Microsoft Fabric, especially in their architecture and features. While Snowflake is highly secure and focuses intently on data sharing, your costs can snowball quickly with high storage and data processing needs.
• Amazon Redshift
The biggest strength of Amazon Redshift is in its unprecedented integration with the AWS ecosystem, including SageMaker and S3. It connects with AWS services, such as AWS Lake Formation, to create a data platform that holds strong governance capabilities.
An organization that has already invested heavily in the AWS infrastructure will benefit from it. That said, there might be certain flexibility constraints due to single-cloud deployment.
Challenges with Microsoft Fabric
While adopting Fabric is transformative, it does not come without specific disputes. Let’s break down a few key challenges you may face with Ms Fabric.
| Challenge | Problem | Partner Solution |
| Complexity & Learning Curve | Fabric integrates various advanced tools under a single platform, which your internal team might not have the right expertise for. | Aegis Softtech has seasoned experts who have years of hands-on knowledge about the platform. |
| Maturity & Stability | The platform is rapidly developing and thus rolling out frequent features. | Our team members hold deep product knowledge, helping you stabilize architecture through proven patterns. |
| Integration & Flexibility | Integrating OneLake with your existing legacy databases and specialized business applications is a technical challenge. Improper execution may lead to data silos. | Expertise in data mesh pipelines and Azure Data Factory is a booster when building secure data pipelines. |
| Operational & Data Issues | Inefficient code or poor data modeling may negatively affect data processing jobs. | Performance optimization and proven data quality strategies help define clear data quality metrics. |
These problems can easily be tackled with the right implementation partner.
Leveraging Microsoft Fabric for Growth with Aegis Softtech
Microsoft Fabric holds the potential to revolutionize your data strategies by unifying governance, analytics, and AI-powered insights within a single platform. You can utilize this platform to eliminate data silos and unveil new growth opportunities.
Using its adaptability and enterprise-grade capabilities, you can produce insight-driven strategies. Thus, getting an answer to ‘what is Microsoft Fabric’ becomes an interesting choice.
At Aegis Softtech, we craft and implement data solutions that align with your long-term intent. Our experts design sapid Microsoft Fabric ecosystems, optimize your data pipelines, and integrate analytics into all your business operations. The result is maximum impact for maximum value.
We partner with you at every step, ensuring faster adoption and a data strategy that fuels innovation and measurable ROI.
Now is the time to get ahead of your competition. Contact us to learn how our expertise can satiate your needs.
FAQs
Q1. What is OneLake?
OneLake is a unified and logical data lake that supports all of your Fabric workloads.
Q2. What is the difference between Microsoft Azure and Fabric?
They are different platforms with different focal points. Azure is a cloud computing platform with a plethora of services, including storage, networking, and compute. Fabric, on the contrary, is a unified analytics platform known for integrating different tools into a single environment.
Q3. What is Microsoft Fabric pricing?
Microsoft Fabric’s pricing model is segregated into two types. One is a pay-as-you-go model, and the other is a reserved instance. Businesses can pick either depending on their usage.
Q4. What is Microsoft Fabric used for?
Microsoft Fabric helps organizations manage and gain insights from their data by simplifying data processes like ingestion, preparation, storage, analysis, and visualization.
Q5. Is Microsoft Fabric a data warehouse?
Microsoft Fabric is not a data warehouse (DWH) but includes one, which is referred to as Fabric Data Warehouse. It supports open data formats and integrates Fabric’s analytics components into a unified platform.
