AI is everywhere – and now even included in Power BI Desktop.

No matter if you’re a business user, analyst, or data scientist – Power BI has AI capabilities tailored to you.

In this video, learn how to leverage the use of language R, integrate an Azure Machine Learning Service when loading data, and understand what kinds of insights Power BI is capable of delivering automatically. 

To learn more, visit: https://community.powerbi.com

Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs. All of this leverages our limitless Azure Data Lake Storage service for any type of data.

Microsoft Mechanics explains.

Microsoft’s Project Silica aims to show that glass is the future of long-term data storage.

To prove its usefulness outside the lab, Microsoft partnered with Warner Bros. to write the 1978 Superman film into glass with lasers.

To see the whole process and the Superman glass, CNET visited Microsoft’s Research Lab in Cambridge, England and Warner Bros. Studios in Burbank, California.

Here’s a great blog post on SQL Server 2019 Big Data Cluster and how it integrates Microsoft SQL Server and the best of big data open-source solutions.

Our testing demonstrates that the performance scales linearly from 1TB to 100TB datasets seamlessly and the various system resources are effectively utilized. Microsoft SQL Server 2019 Big Data Cluster leverages the high performance of Intel® Xeon® processors and Intel® SSDs to deliver great performance for complex queries. In addition, the benchmark results demonstrate powerful elasticity and performance of the entire platform.

The combination of Microsoft SQL Server 2019 Big Data Cluster and Intel’s Xeon Scalable platform can address many of your Big Data challenges. You can store and analyze data from multiple sources at scale, in various data formats, with scale-out compute for data processing and machine learning, together with the industry-leading experience of SQL Server.

Data Lake Storage Gen 2 is the best storage solution for big data analytics in Azure. With its Hadoop compatible access, it is a perfect fit for existing platforms like Databricks, Cloudera, Hortonworks, Hadoop, HDInsight and many more. Take advantage of both blob storage and data lake in one service!

In this video, Azure 4 Everyone introduces to what Azure Data Lake Storage is, how it works and how can you leverage it in your big data workloads. I will also explain the differences between Blob and ADLS.

Sample code from demo: https://pastebin.com/ee7ULpwx

Next steps for you after watching the video
1. Azure Data Lake Storage documentation
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-introduction
2. Transform data using Databricks and ADLS demo tutorial
– https://docs.microsoft.com/en-us/azure/azure-databricks/databricks-extract-load-sql-data-warehouse
3. More on multi-protocol access
– https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-multi-protocol-access
4. Read more on ACL
– https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-access-control