Microsoft Power BI

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Focus on Direct Lake storage Mode: Using Power BI to Transform Data Analytics

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Power BI's Traditional Storage Mode Limitation

The Power BI engine queries the data at the source while using Direct Query mode, which can be slower than import mode but spares the data from needing to be copied. The query results instantly reflect any changes made at the data source.

However, the import mode can offer superior speed since it caches and optimizes the data for DAX and MDX report queries, eliminating the need to convert and send SQL or other query types to the data source.

What is Direct Lake storage mode?

In Power BI, Direct Lake mode is a semantic model feature that allows for the analysis of extremely large amounts of data. The foundation of Direct Lake is the ability to load parquet-formatted files straight out of a data lake without the need to import or duplicate data into a Power BI model or query a Lakehouse or warehouse endpoint.

Using Direct Lake is a fast approach to load data from the lake straight into the Power BI engine for analysis. The comparison between the Direct Lake mode and the classic import and Direct Query modes is depicted in the following diagram.

image source: Microsoft

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Using Direct Lake storage mode with Power BI

Direct Lake support is restricted to Microsoft Fabric (F) SKUs. Current clients may continue to use Direct Lake with Premium (P) SKUs; however, it is recommended that they migrate to a Fabric capacity SKU.

You must set up a Lakehouse (or warehouse) with one or more Delta tables in a workspace hosted at Microsoft Fabric capacity before you can utilize Direct Lake. Your parquet-formatted files in OneLake will be stored in the Lakehouse, which is why it is necessary.

First, create a new semantic model by selecting existing delta tables from Lakehouse or the warehouse and saving them in the same workspace. Then open this semantic model with the option Open data model to open the Web modeling experience where you can add table relationships and DAX measures.

Once relationships and DAX measures are included, you may build a composite model, generate reports, and query the model using XMLA endpoints in a manner similar to that of any other model.

Advantages of Direct Lake mode

Advantages:

  1. By combining the efficiency and speed of the Import mode with real-time data access, Direct Lake strikes a balance.
  2. Direct Lake improves data governance and management by using OneLake to simplify the difficulties of managing several data sources.
  3. Direct Lake is a godsend for large-scale data analytics since it excels at handling massive datasets and loads data into memory as needed.

Conclusion

With Direct Lake, Power BI has advanced significantly by combining efficient large-scale data handling with real-time data access. As it develops further, Direct Lake has the potential to completely change how businesses handle intricate, data-intensive projects. Keep checking back for further analysis and in-depth looks at the rapidly changing field of data analytics and the tools that support it.

 

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Established in 2012, CloudThat is a leading Cloud Training and Cloud Consulting services provider in India, USA, Asia, Europe, and Africa. Being a pioneer in the cloud domain, CloudThat has special expertise in catering to mid-market and enterprise clients from all the major cloud service providers like AWS, Microsoft, GCP, VMware, Databricks, HP, and more. Uniquely positioned to be a single source for both training and consulting for cloud technologies like Cloud Migration, Data Platforms, Microsoft Dynamics 365, DevOps, IoT, and the latest technologies like AI/ML, it is a top-tier partner with AWS and Microsoft, winning more than 8 awards combined in 11 years. Recently, it was recognized as the ‘Think Big’ partner from AWS and won the Microsoft Superstars FY 2023 award in Asia & India. Leveraging its position as a leader in the market, CloudThat has trained 650k+ professionals in 500+ cloud certifications and delivered 300+ consulting projects for 100+ corporates in 28+ countries.

WRITTEN BY Seema Mandlik

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