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Improvements to machine learning capabilities in SQL Server 2019

Many organizations seek to do more with their data than pump out dashboards and reports. Applying advanced analytical approaches such as machine learning is an essential arena of knowledge for any data professional. While database administrators (DBAs) don't necessarily have ... continue reading

Easier management of PolyBase and relational data through SQL Server 2019

The days when a database administrator (DBA) could specialize solely in a single database technology are rapidly ending. Today, we're much more likely than ever before to be asked to bring together many types of data from diverse sources. Although ... continue reading
Build an intelligent analytics platform with SQL Server 2019 Big Data Clusters

Build an intelligent analytics platform with SQL Server 2019 Big Data Clusters

In the most recent releases, SQL Server went beyond relational data and enabled support for graph data, R, and Python machine learning, while making SQL Server available on Linux and containers in addition to Windows. At the same time, organizations ... continue reading
State of the SQL Server tools

State of the SQL Server tools

This week we're announcing the general availability of SQL Server 2019, a significant milestone for Azure Data and for SQL Server customers. This presents a good moment to give an update on the state of tooling for SQL Server.Since SQL ... continue reading

How to prepare data using wrangling data flows in Azure Data Factory

Gaurav Malhotra joins Scott Hanselman to show how wrangling data flows in Azure Data Factory empower you with a code-free, serverless environment that simplifies data preparation in the cloud and scales to any data size with no infrastructure management required ... continue reading
Unify your data lakes with HDFS tiering in SQL Server Big Data Clusters

Unify your data lakes with HDFS tiering in SQL Server Big Data Clusters

As the volume and variety of data has risen, it has become more common to store the data in disparate and diverse data sources. A challenge many organizations face today is how to gain insights from all of their data ... continue reading
In this image, the three new SA benefits are seen. The first benefit shows free SQL Server instance on-premise for HA , 2nd benefit shows free instance on-premise for DR and 3rd shows free instance in Azure for DR.

New high availability and disaster recovery benefits for SQL Server

Business continuity is a key requirement for planning, designing, and implementing any business-critical system. When you bring data into the mix, business continuity becomes mandatory. It’s an insurance policy that one hopes they never have to make a claim against ... continue reading

How to stream big data with Data Accelerator for Apache Spark

Geoff Staneff joins Donovan Brown to show how Data Accelerator for Apache Spark simplifies everything from onboarding to streaming of big data. It offers a rich, easy-to-use experience for creating, editing, and managing Apache Spark jobs on Azure HDInsight while ... continue reading

How to use Jupyter Notebook and Apache Spark in Azure Cosmos DB

Kirill Gavrylyuk joins Scott Hanselman to show how to run Jupyter Notebook and Apache Spark in Azure Cosmos DB. Now you can use the interactive experience of Jupyter Notebook and analytics powered by Apache Spark with your operational data. Run ... continue reading
An example of the job graph showing stages 0 through 3 for a spark job.

Monitoring on Azure HDInsight part 4: Workload metrics and logs

This is the fourth blog post in a four-part series on monitoring on Azure HDInsight. Monitoring on Azure HDInsight Part 1: An Overview discusses the three main monitoring categories: cluster health and availability, resource utilization and performance, and job status ... continue reading