Skip to main content

Microsoft Fabric – A one-stop-shop data analytics platform

 
Microsoft unveiled a unified analytics platform called Microsoft Fabric at the Build 2023 event. However, Fabric is not a brand-new product but a repackaging of Microsoft’s best-of-breed data and analytics tools. Why would Microsoft do that? How will Fabric make a difference for businesses?

Microsoft Fabric — A one-stop-shop data analytics platform — Saxon AI

Solving the overlooked problem — Complexity

A successful data project requires seamless collaboration among data integration, data engineering, data warehousing, data visualization, and data governance platforms. These come from different vendors with their own licensing plans. For example, Microsoft alone offers over 30 products. Including other major vendors like Amazon and SAP will take the number up to 100.

“Numerous data and analytics products are available now. Weighing these products, learning about them, and integrating them together is a challenging job. Also, the integration costs are high, taking up budget estimations and project execution to a different complexity,” says Radhika, Solution architect at Saxon.

The data and analytics market are more mature than it was a decade ago. Businesses have been harnessing data in decision-making by extracting actionable insights. C-suites are happy with the value added by their data teams. However, data teams are spending sleepless nights integrating data sources and platforms without compromising on security to get things done. Vendors of data and analytics products have been heads down, shaping up their offerings. Individually, each product comes with its own USPs, adding value to users. But simplicity is missing in the whole process.

How Microsoft Fabric makes a difference

Microsoft has been envisioning its offerings with a lens of unified access and superior data discoverability across different portfolios. In its latest build conference, Microsoft addressed the big elephant in the room — IT complexities in data analytics. So, it has taken the tried-and-tested umbrella approach.

For the uninitiated, back in 2015, Microsoft stitched together Power Query, Power View, and Power Pivot to create Power BI. For the simplicity it offers, Power BI is widely adopted and went on to be a leader in Gartner’s Magic Quadrant. Microsoft wants to take the game one step further by creating an umbrella over Power BI and other best-of-breed data and analytics products. The result is Microsoft Fabric — a unified lake-centric SaaS platform for end-to-end data analytics needs.

Microsoft Fabric comes with seven core workloads, including Azure Data Factory, Synapse Data Engineering, Synapse Data Warehousing, Synapse Real-time Analytics, Power BI, Data Activator, and Purview for data governance. All these services are connected to one single data lake called OneLake. So, your data team doesn’t have to maintain different copies of data for each service. OneLake in Fabric is akin to what OneDrive for Microsoft 365 applications. With OneLake being the single source of truth, Microsoft Fabric will give more accurate analytics for businesses.

In a statement, Microsoft said, “With this all-inclusive approach, customers can create solutions that leverage all workloads freely without any friction in their experience.

“Fabric eliminates the hurdles of integrating different tools for different workloads. Without worrying about licensing and integration costs, we can focus on what really matters to us — results,” says Radhika.

While offering unified data, experience, and governance, Microsoft Fabric will also offer the following benefits for enterprises:

AI-powered analytics platform:

We are living in the AI era. Microsoft is leading the game with ChatGPT. We have already discussed how Copilot helps small and medium scale enterprises drive digital transformation through the Microsoft Power Platform. Microsoft enables businesses to unlock the full potential of data by integrating Copilot with Fabric.

Driving data culture:

Companies are doubling down on creating data culture more than ever. To help companies foster their data culture, Microsoft deeply integrates Fabric with Microsoft 365 applications. So, businesses can access and analyze data in OneLake from any Microsoft 365 application with a few clicks and unlock insights. Unified data in OneLake also eliminates data duplications and data sprawl, enhancing data quality and enabling businesses to be agile and adaptive to market changes.

Reduced costs:

Microsoft Fabric simplifies purchasing and managing data analytics products by unifying all the data and analytics products on a single platform. You don’t have to buy different licenses for different products. You can access all the services with one Fabric license.

Faster time to analytics:

Fabric eliminates the need for disparate services by unifying its existing offerings. By cutting down the time spent on setting up the tech stack, Fabric enables businesses to start quickly on their data initiatives. Also, the unified UI of Fabric eliminates the need for switching between applications, enabling businesses to gain faster insights in real-time.

“There are so many different PaaS services across the board that when it comes to modernization efforts for many developers, Fabric helps simplify that. We can now spend less time building infrastructure and more time adding value to our business,” says Aon’s data services lead, Boby Azarbod. Aon is one of the early users of Fabric.

Looking forward:

Microsoft is addressing the tech stack complexity challenge, which other vendors failed to see (or at least failed to address first). Given the growing importance of business intelligence and the competition in this space, we are eager to see how other vendors like Amazon will try to catch up.

Originally published at https://saxon.ai on May 26, 2023.

Comments

Popular posts from this blog

Can Agentic AI Make Customer Service Truly Real-Time?

  For years, enterprises have tried to make customer service faster — automating workflows, tightening SLAs, launching 24/7 chatbots. Yet customers still wait — not only for responses, but for reassurance that someone understands. Speed alone doesn’t feel like care anymore. Because real-time isn’t defined by seconds — it’s defined by intelligence that understands intent and acts with empathy. That’s the new frontier of customer experience emerging through Agentic   AI for customer service  — a system of intelligent agents that doesn’t just respond instantly but reasons, learns, and collaborates with humans to make service truly real-time. Are We Solving Problems or Just Replying Faster? Most customer service journeys still begin the same way they did a decade ago — a ticket raised, a call logged, an email sent. Every step that follows is a reaction. Agentic AI for customer service redefines that flow. Instead of waiting for a customer to report an issue, intelligent agent...

Harnessing the power of Generative AI in Customer Service

  If you asked any customer service professional to sum up their experience of the last couple of years, they would likely respond that it was intense! The budgets have been fluctuating, customer expectations are skyrocketing, and service teams are locked in a perpetual quest: How to achieve more with limited resources? Implementing   Artificial Intelligence in customer service  is the right thing to do. With the buzz around   generative AI models   built on pre-trained, large language models that generate human-like, unique content based on prompts, it is no wonder that this technology will be game-changing in customer service.  Meeting the soaring customer expectations   The landscape of customer service has gone through a seismic shift since the onset of the pandemic. Customers’ expectations have soared to unprecedented heights;  72% of customers  choose businesses offering swift customer service. However, customer service agents are constantly swamped with w...

Advanced AI Capabilities in Azure AI Services – 14 questions every CIO should ask

  Recently, Microsoft announced new features in Azure AI Services at the   Ignite 2023   event. As a Microsoft partner, we are following these updates closely and exploring how the new features will unlock more value for enterprises.  The slew of updates is more focused on empowering businesses with enterprise-grade generative AI applications – from leveraging cutting-edge foundation models to building AI applications to enhancing user experiences on those AI applications.   Developing generative AI applications that work exclusively on your enterprise data, for your enterprise is a complex process. You need powerful GPUs to finetune large language models (LLMs). Making this process easier for enterprises, Microsoft launched  Model as a Service  (MaaS) in the Azure AI model catalog. Using MaaS, you can finetune LLMs and build generative AI applications using inference APIs. You will be charged for the number of tokens used as part of the pay-as-yo...