Microsoft SQL Server has been one of the most powerful and widely used relational database systems for over 20 years now. Along with Oracle and MySQL, SQL Server is one of the most widely used enterprise database management systems. Learning how to use any relational database system can help boost almost any career, but if you work in a Microsoft dominant IT shop, SQL Server is a must-learn skill. Let’s take a look at some of the important database skills you will acquire from Microsoft SQL training and break them down further into beginning, intermediate, and advanced categories.

Data Storage Design

Learning how to structure data tables within a database to make input and output of data more efficient is a valuable skill to possess. The ability to quickly design tables and their relationships is the primary building block of any data-driven information system. Thankfully, SQL Server is one of the easiest to use database management systems out there, and if you are well versed in the tenants of database design, it can also be one of the most powerful tools you can wield.


  1.     Database, login, and user creation to build a solid and secure foundation and a method for communicating with the database.
  2.     Grant rights to the new user with the GRANT command so that they have permission to work with the database tables.
  3.     Create tables that are correctly structured so that the data can be stored in logical, scalable design.


  1.     Create primary and foreign keys and normalize the tables to make sure their relationships are clearly defined.
  2.     Create indexes on the tables for frequently used columns to optimize query performance.
  3.     Create data views to display columns from multiple tables in a format that provides informational value to data users.
  4.     Implement a methodology for handling nulls by either specifying default values for null columns or handling them correctly in queries, views, functions, and stored procedures.


  1.     Implement capacity planning strategies. If you will need to return millions of rows of data for queries and dashboards, implement strategies upfront that can handle high volumes of data.
  2.     Implement strategies for storing images files and other documents that will be stored in the database. Byte array data might need to be compressed.
  3.   Implement strategies for storing non-standard types of data such as entire JSON documents or other large data columns. Security might also be a concern since these data types could contain sensitive data. Encryption may be in play to prevent data personnel from viewing sensitive data.

Querying Data

After you design your database and start filling it with data, you’ll then want to be able to query it. Being able to pull knowledge from data is a powerful skill. Data by itself is just a bunch of 0’s and 1’s stored in a file. However, if you know how your data relationships are structured and how to get specific data out and present it so that it is meaningful to users, then you have the beginnings of valuable applications and reports. Data by itself is only valuable if you have someone with the knowledge of how to extract it and make it easily usable for resources who wish to use it for a specific purpose.


  1.     Create queries, functions, and stored procedures to facilitate CRUD operations. A good mastery of the SELECT, UPDATE, INSERT and DELETE commands are a good starting point.
  2.     Optimize queries utilizing the correct joins and methods to return only the data needed as quickly as possible. Join commands such as UNION, INNER JOIN, and LEFT and RIGHT OUTER JOINS will be needed.
  3.     A mastery of the WHERE and ORDER BY clause will be necessary to provide only the data a user is requesting and to sort it by specific fields so that it makes sense.


  1.     Develop advanced queries using subqueries and conditional formatting to provide requested data to consumers in a clear and concise format. The OR, AND, IN, BETWEEN, GETDATE, GROUP BY, and HAVING keywords will be needed.
  2.     Mathematical keywords such as COUNT, AVG, MIN, and MAX can be used to return data for statistics and calculations.


  1.     Using table triggers to fire functionality based on rows being inserted or updated in specific tables.
  2.     Develop cursors to be able to loop through data and provide results and build temporary data tables on the fly.
  3.     Develop the ability to performance tune and optimize all of these query commands by developing execution plans.

Application Development

If you know how to create and structure your data storage as well as how to run queries against it to turn it into useful information, then you can begin to develop applications. Most applications are tools used by various types of users to input data into the database and then update and extract it in various ways.

Applications provide tools that users can take advantage of in various ways. This converts the data into a living entity because it is continuously changing and being updated to reflect current information. You have probably heard the statement that “information is power.” Well, the building blocks of that powerful information are raw data, and having the necessary skills to manage it is priceless.


  1.     The ability to connect code to a database. Several examples of database connection technologies are ODBC, ADO.NET, PHP web services, Azure or AWS web services.
  2.     Be able to map data returned from a database server to objects or containers in application code to be used in input and output scenarios. Entity relationships and object relationship methodologies will need to be employed.
  3.     Determine whether it will be more efficient to process data in code or if the database would be better suited to perform the processing and simply return it to the application code.


  1.     Develop code to facilitate CRUD (CREATE, READ, UPDATE, DELETE) calls to the database using precompiled stored procedures, inline queries, or database functions.
  2.     Object-oriented programming concepts is a plus since objects will be modeled from SQL tables that contain the data in a logical format.


  1.     Developing advanced methods for passing data. One example would be passing an entire object or table as a parameter to a stored procedure so that the database can handle CRUD operations.
  2.     Network performance tuning for large datasets. Develop the ability to analyze large amounts of data being passed between the database and application server to optimize performance between the two layers.
  3.     Utilize the security and encryption practices and methodologies to make sure that the data is safe in case of attacks from outside or inside the organization.


After developing applications to input, update, and maintain your data, you will want to display it in a meaningful way. That is where reporting comes in. You can use various tools to extract information from your data and present it to decision-makers to help them make more accurate and informed decisions. This is the point where your users can use that information for multiple purposes. For example, you can use that data to relay sales information or to pinpoint demographic and regional information.

There is no limit to the information you can gather as long as you are acquiring the right data. You can present various visualizations as well as different creative charts, graphics, and graphical representations to easily convey the information you have built with your data. Reporting is the end goal of all your data gathering efforts because it gives decision-makers the information they need to manage processes effectively and efficiently.


  1.     Reporting should be considered from the beginning of the design. The true power of data is the information that can be extracted from it. Purposeful database and application design with backend reporting in mind is key.
  2.     Knowing how different data sources are related and how they can be connected to present a cohesive dataset for dashboards and reports is very important.
  3.     Data cleaning and preparation is an important skill. Sometimes data might be coming from a data source lacking proper design, such as spreadsheets and databases designed by non-technical personnel, and it will need to be cleaned and refactored.


  1.     Data analysis to answer business questions. Taking a requirement and turning it into results is essential. Finding patterns and ways to link data together is at the heart of good analysis.
  2.     Knowledge of statistics and how to visually represent different types of statistical tools.
  3.     Building data visualizations and finding the right type of chart or graph that will most effectively represent the data.


  1.     Data mining to be able to sift through large amounts of data and find emerging patterns.
  2.     Big data and data warehousing techniques for analyzing large amounts of unstructured data.
  3.     Predictive analysis principles help to build visualizations that help to define trends and patterns that emerge over time.

Possessing even some of the data skills outlined above can open tons of potential opportunities. Data analysts, developers, and administrators are always in high demand in the software industry. Reporting specialists are employed in business, technology, education, and anywhere data needs to be collected, transformed, and presented to decision-makers. Data science professionals are always in high demand at companies that provide big data analysis and data warehousing. Statistical data analysis is important in science and technology fields. 

The sky’s the limit for someone who can gather, manipulate, and present data in an informational format. The best way to obtain and grow those data skills is by getting professional Microsoft SQL Server training from expert trainers.  

Contact us today to find out how you can start developing your professional Microsoft SQL skills.

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