Essential Roles for Microsoft Fabric: Build Your Data Dream Team

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In our last Microsoft Fabric blog we gave you an overview of what youcan expect from Fabric tech-wise, and some use cases that might highlight whereyou could use it. At this point, it might be clear that implementing MicrosoftFabric can transform your data management capabilities, but to harness its fullpotential it's crucial to have the right team in place.

This guide aims to highlight the essential data roles your business needs to successfully implement and leverage Microsoft Fabric, along with the tools and use cases foreach role, so you can confidently start a conversation surrounding the expertise you need.

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Data Engineers are traditionally responsible for building and maintaining the infrastructure that allows data to be accessed and processed efficiently. They ensure that data pipelines are robust, scalable, and reliable, enabling seamless data flow across the organization. Microsoft Fabric abstracts connection and setup which makes life a bit easier, especially if you’re fully in the cloud. There is a caveat here: Fabric is, at present, more focused on the Analytics and Business end-user and, not yet, geared towards the traditional capabilities of a Data Engineer. Your engineers might be more accustomed to doing certain processes outside of the Fabric ecosystem that tailor more to their specific needs than Fabric does. That doesn't mean that it cannot be done in Fabric, but they might have a good reason for wanting to go off-platform, we recommend you consult them before making your decision.

If you’re wondering: “Where will they be spending their time in Fabric?”, we hear you. The short answer is “mostly” Synapse Data Engineering. This experience of Fabric allows them to use Spark application Notebooks and job definitions for loading and complex transformations. They’ll also be using Data Factory Pipelines for integrating and transforming data at scale. This should be a familiar data orchestration tool from your Microsoft ecosystem if your engineers are familiar with Azure Synapse Analytics.

A Data Engineer leverages Azure Data Factory to orchestrate robust data pipelines that seamlessly extract, transform, and load (ETL) data from diverse sources into a centralized data warehouse. This process ensures that data remains consistent, up-to-date, and readily available for analytical insights and informed decision-making.

For instance, consider a scenario where a Data Engineer automates the collection of sales data from multiple regional databases. By using Data Factory, they can transform this disparate data into a standardized format, ensuring uniformity and accuracy. The transformed data is then loaded into a centralized data warehouse, creating a single source of truth that analysts and business users can easily access. This streamlined approach not only enhances data reliability but also empowers stakeholders to derive actionable insights and drive business strategies.

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Fabric Analytics Engineers are specialised Data Engineers focused on optimizing the performance and scalability of analytics solutions within Microsoft Fabric. Their expertise ensures that data processing is efficient, cost-effective and aligned with best practices on the platform. This role involves a comprehensive understanding and integration with all components of Microsoft Fabric.

A Fabric Analytics Engineer might optimize the performance of a data pipeline that processes large volumes of transactional data. By fine-tuning the pipeline, they ensure faster data processing and reduced costs. A Fabric Analytics Engineer might identify bottlenecks in a data processing workflow and implement performance improvements such as indexing, partitioning, or parallel processing to enhance the overall efficiency of the system. By adhering to best practices and leveraging the full capabilities of the platform, these engineers play a pivotal role in delivering high-performance analytics solutions that drive informed business decisions.

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What’s the difference between Data Engineer and Fabric Analytics Engineer?

A Data Engineer focuses on designing and maintaining data pipelines, ensuring smooth data flow from various sources into storage systems. They handle data infrastructure, scalability, and reliability.

A Fabric Analytics Engineer specializes in creating enterprise-scale data analytics solutions within the Microsoft Fabric ecosystem. Their responsibilities include transforming data into reusable analytics assets using Fabric components and collaborating with other roles to deliver effective analytics solutions.

Typical candidates for becoming a Fabric Analytics Engineer have a background in data engineering, analytics, and performance optimisation. Microsoft offers various certifications that can help in acquiring the necessary skills, but the primary one you need to look out for is Fabric Analytics Engineer Associate (DP- 600).

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Data Scientists can leverage advanced analytics and machine learning to extract insights and build predictive models, enabling data-driven decisions. With Microsoft Fabric, they can use ML models with Notebooks that contain PySpark (Python), Spark (Scala), Spark SQL or SparkR code. Fabric allows seamless access to Lakehouse data, integration with existing dataframes, streamlined data wrangling and experiments all within a unified platform.

A Data Scientist uses tools available in Microsoft Fabric to analyze customer data and build a predictive model for forecasting customer turnover. By identifying at-risk customers, the business can implement targeted retention strategies to reduce turnover rates. Fabric enables Data Scientists to access enriched data in the data warehouse or raw data in OneLake, wrangle it to suit their investigation, and build, test, and train models—all in one place.

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Data Analyst / BI Professionals analyse data to provide actionable insights and support business decision-making. They turn raw data into meaningful information that drives business strategies and improves operational efficiency. Microsoft Fabric is tailored to integrate Azure Synapse Analytics features closely with Power BI within a single SaaS Platform. While Power BI remains a standalone product, it’s close relationship with Fabric incentivises using them together for enhanced data analytics and visualisation capabilities.

Data Analysts will primarily work in Power BI to create interactive data visualisations and reports from semantic models. Final data preparation and transformations for reports can done in Dataflows Gen2 and Synapse Datawarehouse where they can query data using SQL and create measures for use in Power BI.

A Data Analyst could use Power BI to create a dashboard that visualizes sales performance across different regions. The dashboard helps identify trends and areas needing attention, enabling the business to make informed decisions quickly. For instance, a BI Professional might develop a Power BI report that tracks key metrics such as monthly sales, customer acquisition rates, and product performance, allowing executives to monitor the company's progress in real time and adjust strategies accordingly.

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Finally, Business Users can leverage data insights to drive business strategies and decisions by relying on easy-to-use tools to access and interpret data within Microsoft Fabric. These tools help them make informed choices in their daily operations. While their engagement with data analytics and reports varies based on expertise, all roles—Data Engineers, Data Analysts, BI Professionals, and Business Users—work together to facilitate valuable, data-driven decisions.

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In summary, depending on the scale of your data solution you’ll need a few data professionals to implement Fabric and keep it running well. While much of the content here might not be new to you, we feel better knowing you have a good foundation to start a conversation with.

If you want to have a conversation about roles Calybre can help you fill in your use of Fabric feel free to send us a message through our contact page.

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