Analytics Vidhya
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Analytics Vidhya

Renovate your Business Intelligence (BI) platform with Azure Synapse Analytics and Power BI Premium

In my previous blog, I discussed the concept of modern business intelligence (BI) architecture. Let us now discuss how we can use Azure Synapse and Power BI premium to renovate your enterprise BI platform.

In this competitive digital world, technology has been advancing very rapidly and it is very essential for companies to be constantly aware of these technological advancements and modernize their IT platforms to withstand in the market for long. ( we have many examples where companies failed to innovate and resulting in Kodak, Nokia..etc)

so are you ready to renovate your data platform????????????????

Let's see what Azure Synapse and Power BI offers to renovate the traditional Business Intelligence (BI)platforms

As we all know Azure Synapse Analytics is a unified platform that brings data integration, enterprise data warehousing, and big data analytics together to give a unified experience to ingest, explore, prepare, manage, and serve data for immediate BI and machine learning needs.

On the other hand Power BI Premium provides the richest set of capabilities for both self-service and enterprise BI solutions.

The above architecture diagram shows the various stages and respective azure synapse ad power bi services that are involved in modernizing the enterprise BI solution. Let's look at them individually

Source: At the time of writing this Article, Azure Synapse supports 90+ data sources and the list keeps on growing.

Ingest: Azure Synapse is capable of processing massive volumes of relational (structured) and non-relational data ( semi-structured and unstructured). It comes integrated with an identical data integration engine as in the Azure Data Factory which allows us to create rich at-scale extract-transform-load (ETL) pipelines without leaving the Azure Synapse workspace. Orchestrate notebooks, spark jobs, stored procedures as well as SQL scripts. Create data-driven workflows for orchestrating and automating data movement and transformation

Data Integration Pipeline

Stage Store: Azure Data Lake is used to stage the source data, It's designed from the start to service multiple petabytes of information while sustaining hundreds of gigabits of throughput, Data Lake Storage allows you to easily manage massive amounts of data, Ingest them, perform analytics using SQL, and create visual representations.

Also, easily query files in the data lake with the same service used to build data warehousing solutions.

Polybase is a technology that accesses external data stored in Azure Data Lake Store using the Transact-SQL language. This is the most scalable and fastest way of loading data into an Azure Synapse SQL Pool. Data need not be copied into SQL Pool in order to access it

Target Store: Dedicated SQL Pool (SQL DWH )is the target repository where the data stores in relational tables with columnar storage. As we all know columnar storage is a very efficient way of storing data to reduces data storage costs and improves query performance. Once data is stored, you can run analytics on a massive scale. Compared to traditional database systems, analysis queries finish in seconds instead of minutes or hours instead of days.

Dedicated SQL Pool

Analysis: Power BI Premium provides the richest set of capabilities for both self-service and enterprise BI solutions. (Azure Analysis Services is also an option for enterprise BI solutions)

Power BI Premium is the focus for enterprise BI and will provide a superset of the capabilities when compared to Azure Analysis Services. So consider using Power BI Premium for your enterprise models

Ref: Power BI Blog

Visualize: Power BI transforms the data into rich visuals so you can focus on what matters to you. Stay in the know, spot trends as they happen, and push your business further.

I hope you enjoyed reading this article see you in my next article until then stay safe and healthy.



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