Learn About The Sneak Peek Feature At The Microsoft Azure Sql Datastor

👉Fresh from last week's Build developer conference in San Francisco, Microsoft executives appeared at the company's first-ever Ignite conference in Chicago and provided more details about the company's new Azure SQL Data Warehouse.

⭐️You can see more at the link at the end of the article. Thank you for your interest in the blog, if you find it interesting, please give me a like, comment and share with everyone. Thanks! ❤️

#azure #sql #azuresql 


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Learn About The Sneak Peek Feature At The Microsoft Azure Sql Datastor
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

Migrating SQL workloads to Microsoft Azure: Planning the jump

In this article, we will discuss several points that should be considered when planning to migrate the on-premises SQL workload to Microsoft Azure cloud services. This article is the first step in a series of articles that discuss how to perform the SQL and No-SQL workload migration smoothly to the cloud.

Why migrate?

Data is one of the most precious “assets” in each company that drives business success. And as a proactive Data Engineer in an international company, you will always think how to secure your data at rest and in transit, and use the most optimal data platform technologies to serve the data to the application clients from any point in the earth as fast as possible with the minimum downtime or data loss possibilities.

With the growth of the company business, it is your responsibility to keep track of the data storage and retrieval speed in order not to lose your clients. Put yourself in the shoes of a client who is trying to submit an online order to buy from your online store, but the site is taking a long time to refresh the content and submit the order. For me, I will close the site and buy it from the nearest store!


If the Infrastructure administrator starts complaining about the limitation in the remaining resources in the current hosting machine, or the delay in receiving the new purchased resources, it is the suitable time to discuss with the management the choice to move your SQL workload to Microsoft Azure.

SQL Cloud

Initial Study

Before you think to send a meeting request to your management to discuss your idea about migrating the current SQL workload to Microsoft Azure, you need to take into consideration that it is not only one word that you need to mention to the management or a step by step tutorial that you can follow to perform the migration process. You should be prepared and ready for any question by preparing a comprehensive study that includes the current site problems and limitations, a plan for the design and implementation phases of the migration process, and the benefits that the company will gain from moving that workload to Azure from all performance, business growth handling and cost.

The initial study for the migration process should include, but may extend:

  • The current SQL and No-SQL workload types in your company, such as OLTP and OLAP workloads
  • The database administration and monitoring tools that you are using in the on-prems site
  • The list of on-prems database engine types, versions, and locations
  • The current database resources size and the expected resources growth ratio for each database
  • The dependencies between the databases. This helps in selecting the list of candidate databases that will participate in the first migration wave and the database consolidation possibilities to reduce the cloud hosting cost
  • The dependencies between the databases and the applications and how these applications interact with the databases. This will end up grouping the databases based on its dependencies. It is better to have a discussion with the development team to identify the criticality of each database for the business and see if it is possible to migrate the database applications to Microsoft Azure
  • The different security and encryption requirements for each database
  • The backup strategy and tools used for each database
  • The list of all additional components that are involved in the data models, such as SSIS, SSAS, and SSRS that should be migrated
  • The list of issues that you are facing in the current site, such as performance or availability
  • The limitations in the current site, such as hardware upgrade limitation or unsupported features
  • The Availability requirements for your databases
  • The confirmed Restore Time Objective (RTO) and Restore Point Objective (RPO) for your databases and how they are met in the current site

Cloud Considerations

After checking the current situation, you should have a look at the cloud solutions that can be used to replace the current on-premises site. This includes learning the features available in each service and the pros and cons of each service in order to identify which service meets your requirements. With the different available cloud providers, I will concentrate on the Microsoft Azure database services in my articles, such as SQL on Azure VM, Azure SQL Database, Azure SQL Managed Instance, and Azure SQL Data Warehouse, and how to use it as a replacement for the on-premises ones.

Migrate to Cloud

Once you review the Microsoft Azure database-related services, your need to take into consideration the following points in your migration plan that may extend:

  • Choose the suitable target data platform in the cloud, Infrastructure as a Services (IaaS) or Platform as a Service (PaaS), based on your technical requirements, and cost plan. This choice specifies what Azure services can be used and the control level on these services
  • The Microsoft Azure services that can be used as a replacement for every single feature, component, or functionality in the on-prems site to serve your workloads
  • The proper size for the Microsoft Azure services to fit the current site growth ratio with the minimal possible cost. Scaling up/down plans or scaling out/in plans at that stage will be a great step ahead
  • The suitable region(s) to host each database that provides the lowest latency, based on the applications and client’s locations
  • The Availability solution that should be used in Microsoft Azure, based on the selected Azure service, to meet your database availability requirements
  • The cloud services configurations and features that can be used to meet the confirmed Restore Time Objective (RTO) and Restore Point Objective (RPO)
  • The ability to achieve the security and privacy compliance and regulatory requirements of your organization using the cloud services
  • The changes that should be performed on the current workload to be compatible with the target data platform technologies in Microsoft Azure and what transformation tools can be used to achieve that
  • The new features in the cloud that can be used to optimize the current workload
  • The administration and monitoring tools that can be used to replace the on-prems tools
  • The ability to perform the security and encryption requirements for each database
  • The backup and recovery cloud solutions can be used to design and automate the database backup strategy
  • Any potential blockers for the migration process
  • The tools that will be used to migrate the current workload to the cloud with minimal possible downtime and data loss
  • Validation test strategy by migrating sample workload and how to measure the gains and compare it with the on-premises site
  • The breaking fixes that should be performed after the migration process
  • The rollback plan in case of any single possible failure

Now you can send the invitation to your management and discuss with them if migrating the current on-premises workload to the cloud is feasible, or you need to move with upgrading the current on-premises data center to handle the workload growth, serving the clients with highest possible availability and minimal data loss, without losing the company clients or having them frustrated from the company services.

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