About Microsoft Fabric
Synapse Data Science – in MS Fabric
Read more: Synapse Data Science – in MS FabricData Science is where the buzz and the headlines in the world of data are concentrated. Here you build your own Machine Learning models, and start to uncover the benefits of AI
Synapse Data Warehouse – in MS Fabric
Read more: Synapse Data Warehouse – in MS FabricThe Synapse Data Warehouse is one of the 7 Experiences in Fabric, allowing teams to leverage their traditional SQL Server skills.
Synapse Data Engineering – in MS Fabric
Read more: Synapse Data Engineering – in MS FabricOnce your data has arrived in its “Lakehouse”, Engineering provides a set of tools for Data Engineers to get the data cleaned, enriched, validated, and ready for live use. Its main tools are Opensource Apache “Spark” jobs, which can run many processes in parallel for big data applications, and which allow you to further refine…
Data Factory – integration and data pipelines in Fabric
Read more: Data Factory – integration and data pipelines in FabricData Factory is the first experience within Fabric. It allows you to pull data from any source into the OneLake, build your own “Lake House” for a project, and automate and control the flow of fresh data into your environment. Data Factory contains two main artefacts: Between the above your data should be automatically in…
Why would Microsoft Fabric matter to you?
Read more: Why would Microsoft Fabric matter to you?Fabric is Microsoft’s new data and reporting platform, and the place they intend us all to get to grips with big data, reporting and AI. But what does this mean for your business? Here we look at some very common shared problems in the world of data, and how Fabric is set up to resolve…
Microsoft Fabric and Power BI
Read more: Microsoft Fabric and Power BIIntroduction to Microsoft Fabric Microsoft Power BI has been leading the BI and reporting market, since its introduction in 2017 and become something of an Industry standard. However like any desktop application it sometimes suffers from fragmented use, with lots of people in an Organization preparing and storing their own data, and creating similar but…
