Transparent Data Encryption for SQL Server Always

In this 15th article of SQL Server Always On Availability Groups series, we will cover Transparent Data Encryption (TDE) for AG databases.

Introduction

In the previous articles of SQL Server Always On series, we explored the following topics so far.

• Build virtual servers using Oracle VirtualBox
• We configured domain controller, active directory and domain name service (DNS)
• Deployed SQL Server 2019 Availability groups
• Domain-independent AG in Windows Server 2016
• We configured distributed availability groups for the availability group in independent clusters

Suppose, In specific requirements, you might want to protect sensitive data for compliance and security purposes. SQL Server provides **Transparent Data Encryption(TDE) **for encrypting the physical files. In this article, we will explore TDE for a SQL Server Always On Availability Group.

Overview of Transparent Data Encryption (TDE)

The objective of implementing TDE is to secure the data and log files for a SQL database. Suppose you have sensitive customer data in your database. Someone might copy your database files and easily access critical information. This encryption process does not require any changes from the application end. It encrypts the files at the page level before writing the page in the disk. It decrypts the files once a user tries to access a page. Once we implement TDE, we cannot restore or attach a database without an appropriate certificate and key.

The high-level steps for a TDE are as below.

TDE is not straightforward for an availability group database. In the next section, we explore the steps in a two-node SQL Server Always On Availability Group.In this 15th article of SQL Server Always On Availability Groups series, we will cover Transparent Data Encryption (TDE) for AG databases.

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

Introduction

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

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SCHEMAS in SQL Server -MS SQL Server – Zero to Hero Query Master

Introduction

This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,

• MS SQL Server – Zero to Hero Query Master – Part 1
• MS SQL Server – Zero to Hero Query Master – Part 2

A glimpse of previous articles

Part 1

In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.

Part 2

• We learned to create a database and maintain it using SQL statements.
• Best practice methods were also mentioned.

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Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

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Welcome Back the T-SQL Debugger with SQL Complete – SQL Debugger

When you develop large chunks of T-SQL code with the help of the SQL Server Management Studio tool, it is essential to test the “Live” behavior of your code by making sure that each small piece of code works fine and being able to allocate any error message that may cause a failure within that code.

The easiest way to perform that would be to use the T-SQL debugger feature, which used to be built-in over the SQL Server Management Studio tool. But since the T-SQL debugger feature was removed completely from SQL Server Management Studio 18 and later editions, we need a replacement for that feature. This is because we cannot keep using the old versions of SSMS just to support the T-SQL Debugger feature without “enjoying” the new features and bug fixes that are released in the new SSMS versions.

If you plan to wait for SSMS to bring back the T-SQL Debugger feature, vote in the Put Debugger back into SSMS 18 to ask Microsoft to reintroduce it.

As for me, I searched for an alternative tool for a T-SQL Debugger SSMS built-in feature and found that Devart company rolled out a new T-SQL Debugger feature to version 6.4 of SQL – Complete tool. SQL Complete is an add-in for Visual Studio and SSMS that offers scripts autocompletion capabilities, which help develop and debug your SQL database project.

The SQL Debugger feature of SQL Complete allows you to check the execution of your scripts, procedures, functions, and triggers step by step by adding breakpoints to the lines where you plan to start, suspend, evaluate, step through, and then to continue the execution of your script.

You can download SQL Complete from the dbForge Download page and install it on your machine using a straight-forward installation wizard. The wizard will ask you to specify the installation path for the SQL Complete tool and the versions of SSMS and Visual Studio that you plan to install the SQL Complete on, as an add-in, from the versions that are installed on your machine, as shown below:

Once SQL Complete is fully installed on your machine, the dbForge SQL Complete installation wizard will notify you of whether the installation was completed successfully or the wizard faced any specific issue that you can troubleshoot and fix easily. If there are no issues, the wizard will provide you with an option to open the SSMS tool and start using the SQL Complete tool, as displayed below:

When you open SSMS, you will see a new “Debug” tools menu, under which you can navigate the SQL Debugger feature options. Besides, you will see a list of icons that will be used to control the debug mode of the T-SQL query at the leftmost side of the SSMS tool. If you cannot see the list, you can go to View -> Toolbars -> Debugger to make these icons visible.

During the debugging session, the SQL Debugger icons will be as follows:

The functionality of these icons within the SQL Debugger can be summarized as:

• Adding Breakpoints to control the execution pause of the T-SQL script at a specific statement allows you to check the debugging information of the T-SQL statements such as the values for the parameters and the variables.
• Step Into is “navigate” through the script statements one by one, allowing you to check how each statement behaves.
• Step Over is “execute” a specific stored procedure if you are sure that it contains no error.
• Step Out is “return” from the stored procedure, function, or trigger to the main debugging window.
• Continue executing the script until reaching the next breakpoint.
• Stop Debugging is “terminate” the debugging session.
• Restart “stop and start” the current debugging session.

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