Loma  Baumbach

Loma Baumbach


New Azure SQL Learning Tools help reduce the global technology skills gap

Microsoft’s learning solutions pave the way toward data-centric jobs of the future

"It’s been forecasted 800 million people need to learn new skills for their jobs by 2030. In this time of change, people are hungry to learn, gain new skills, and grow their economic opportunity.”—Satya Nadella, CEO, Microsoft

Across Microsoft, we are helping a new generation of technology workers develop the right level of skills. Recently, Microsoft announced the availability of new virtual learning programs. These programs, focused on technical topics, are already helping people enhance their digital expertise and, for some, are providing a foundation for success in a new career path.

Building upon this goal, we’re excited to announce the Azure Data team’s latest additions to these educational programs.

Our all-new content will help beginners being introduced to Azure as well as SQL experts learn how to understand the benefits of Azure SQL. Since SQL Server and Azure SQL share the same engine, these new set of tools builds upon familiar content. This means SQL Server professionals can become Azure SQL professionals with just a little bit of help, such as:

Microsoft Learn learning path: This six-course Azure SQL fundamentals learning path provides a built-in lab environment for you to learn at your own pace without a subscription.

YouTube/Channel9 series: We offer more than 60 videos to help beginners learn more about Azure SQL. Viewers can experience on-demand training through Microsoft Developer and Azure SQL playlists on YouTube and Channel9.

GitHub content: Learners and educators can dig into open-source code in a scenario-driven GitHub workshop, where forking and redelivering is encouraged. You can access this content by visiting the SQL Server workshops page and selecting “Workshop: Azure SQL”.

Learn Live in the Azure SQL Bootcamp: In this four-day series of live sessions, Microsoft SQL experts Anna Hoffman and Bob Ward will help you get ramped up and support you as you learn. You can sign up for Azure SQL Bootcamp here to join us.

Azure SQL’s rapid adoption creates new opportunities

Azure SQL adoption is accelerating at a dramatic growth rate and will continue on this trajectory for the foreseeable future. Azure SQL unlocks new opportunities for our customers to optimize costs, build resiliency, and promote agility with AI-based features, rapid scaling capability, and much more.

A few weeks ago, a Morgan Stanley report noted, “The key insight of [the] 2nd edition of our New Stack monthly is that the relational database, commonly viewed as outdated for the digital era, is not only not dead but is seeing a resurgence reflecting strong growth in cloud. MSFT is a key beneficiary with the top share in cloud and overall".

It’s a terrific time to join the Azure SQL community and fine-tune your technical skills. If you have questions about the benefits, opportunities, or process of making a move from SQL on-premises to SQL in the Cloud, we can lend a hand to guide you. Our new learning materials answer these questions and go into greater technical depth. On Twitter, you can follow us @AzureSQL and get more involved in the community with the #AzureSQL.


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New Azure SQL Learning Tools help reduce the global technology skills gap
Cayla  Erdman

Cayla Erdman


Introduction to Structured Query Language SQL pdf

SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.

Models for SQL exist. In any case, the SQL that can be utilized on every last one of the major RDBMS today is in various flavors. This is because of two reasons:

1. The SQL order standard is genuinely intricate, and it isn’t handy to actualize the whole standard.

2. Every database seller needs an approach to separate its item from others.

Right now, contrasts are noted where fitting.

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Ruthie  Bugala

Ruthie Bugala


How to set up Azure Data Sync between Azure SQL databases and on-premises SQL Server

In this article, you learn how to set up Azure Data Sync services. In addition, you will also learn how to create and set up a data sync group between Azure SQL database and on-premises SQL Server.

In this article, you will see:

  • Overview of Azure SQL Data Sync feature
  • Discuss key components
  • Comparison between Azure SQL Data sync with the other Azure Data option
  • Setup Azure SQL Data Sync
  • More…

Azure Data Sync

Azure Data Sync —a synchronization service set up on an Azure SQL Database. This service synchronizes the data across multiple SQL databases. You can set up bi-directional data synchronization where data ingest and egest process happens between the SQL databases—It can be between Azure SQL database and on-premises and/or within the cloud Azure SQL database. At this moment, the only limitation is that it will not support Azure SQL Managed Instance.

#azure #sql azure #azure sql #azure data sync #azure sql #sql server

Creating and Cataloging SQL pools in Azure SQL Server

This article will walk you through creating a new SQL pool within an existing Azure SQL Server as well as catalog the same using the Azure Purview service.


Data is generated by transactional systems and typically stored in relational data repositories. This data is generally used by live applications and for operational reporting. As this data volume grows, this data is often required by other analytical repositories and data warehouses where it can be used for referential purposes and adding more context to other data from across the organization. Transactional systems (also known as Online Transaction Processing (OLTP) systems) usually need a relational database engine, while analytical systems (also known as Online Analytical Processing (OLAP) systems) usually need analytical data processing engines. On Azure cloud, it is usually known that for OLTP requirements, SQL Server or Azure SQL Database can be employed, and for analytical data processing needs, Azure Synapse and other similar services can be employed. SQL Pools in Azure Synapse host the data on an SQL Server environment that can process the data in a massively parallel processing model, and the address of this environment is generally the name of the Azure Synapse workspace environment. At times, when one has already an Azure SQL Server in production or in use, the need is to have these SQL Pools on an existing Azure SQL Server instance, so data in these SQL pools can be processed per the requirements on an OLAP system as well as the data can be co-located with data generated by OLTP systems. This can be done by creating SQL Pools within the Azure SQL Server instance itself. In this article, we will learn to create a new SQL Pool within an existing Azure SQL Server followed by cataloging the same using the Azure Purview service.


As we intend to create a new SQL Pool in an existing Azure SQL Server instance, we need to have an instance of Azure SQL in place. Navigate to Azure Portal, search for Azure SQL and create a new instance of it. We can create an instance with the most basic configuration for demonstration purposes. Once the instance is created, we can navigate to the dashboard page of the instance and it would look as shown below.

As we are going to catalog the data in the dedicated SQL Pool hosted on Azure SQL instance, we also need to create an instance of Azure Purview. We would be using the Azure Purview studio from the dashboard of this instance, tonregister this SQL Pool as the source and catalog the instance.

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Ray  Patel

Ray Patel


Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services


When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

  • revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
  • microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
  • Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

Karlee  Will

Karlee Will


Top 7 Reasons to Start Learning SQL Today | Why Learn SQL?

Whoever was born before after the 1970s must have heard of SQL. It is so old!

Since the Internet boom of the last century, it has been a crucial part of the computer world.

“But then, why should I learn SQL – such an ancient language – when there are so many recent languages, such as Python and R, that have become more dominant?” is a question that stumps many developers and programmers!

Structured Query Language – SQL – was built to interact with different databases. So, any computer programmer whose job requires them to work on databases needs to be well-versed with SQL.

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