If you work in a profession that uses data reporting and analytics in some capacity, then it is very likely that you have heard about SQL before. This programming language allows users to manage relational databases to extract actionable insights and inform important strategic decisions, making it one of the most valued analytics-related skills to this day.
In today’s modern world, data and analytics have been democratized to a wider audience thanks to self-service tools that opened the analytical doors to non-technical users. With these tools, you no longer need advanced analytics or programming knowledge to extract actionable insights from your data.
That said, it’s important to have some basic SQL skills. As it will help streamline your everyday tasks and provide a standard way to communicate with databases. It’s a common language used by most data analysts, data scientists, and database programmers and here we will provide you with a brief introduction to its role in data analysis.
What is SQL?
SQL (Structured Query Language) is a programming language used to store, manipulate and retrieve data in relational databases. It was developed in the 1970s by IBM scientists under the name SEQUEL and is now a standard of both the American National Standards Institute (ANSI) and the International Organization for Standardization (ISO).
Just like Excel, SQL stores data in a table format and uses keywords, identifiers, strings, expressions, and variables to interact with the data. This makes it a popular programming language with an accessible learning curve.
SQL is a very versatile language that can be used to interact with multiple relational databases like MySQL, PostgreSQL, Oracle, Redshift, and many others. Since SQL is a standardized language, analysts don’t need to learn a different language for each database, making it a core part of many database systems, operating systems, coding environments, server environments and embedded systems.
What are the Benefits of SQL?
Businesses use SQL to extract, modify, add to, remove, or otherwise organize data stored in private databases. The value of this programming language lies in the fact that it can extract data from large databases quickly and efficiently within minutes. Plus, SQL queries are reusable and scalable, meaning you can write a query once and use it again even with bigger databases.
One of the benefits of SQL is that it is easy to learn and use. SQL commands use common English phrases making it easier for programmers to interact with the language and understand what they are asking it to do. This makes it possible for professionals with little to no coding background to learn the basics of the language.
The efficiency of SQL in a business context is so valuable today that many tools have found ways to make it more accessible for the average business user as well. For example, datapine’s powerful SQL report builder offers users the possibility to easily generate SQL queries via drag and drop to visualize their most important data in stunning reports.
Many big tech companies, such as Facebook, Instagram, and WhatsApp rely on SQL for data storage, processing, and reporting. SQL tools provide small and bigger companies with the necessary features to manage their data in an efficient and productive manner. Setting the perfect environment to extract actionable insights and boost performance.
What is the Role of SQL for Data Analysis?
When it comes to data analysis and reporting, SQL is one of the most powerful tools available. It is highly customizable, making it a great choice for data analysts and business intelligence consultants who need to interact with large databases.
There are multiple capabilities of SQL that can enhance the data analysis process, some of them include:
- Manipulate data within a database
- Retrieve data from a database
- Change the structure of the data within a database
- Combine datasets within the database
- Generate dashboards and reports
The last point about generating dashboards and reports is arguably the most popular use of SQL in today’s context. With data being the biggest competitive advantage for organizations today, being able to retrieve and display data in sophisticated reports can significantly enhance the way businesses deal with their information. SQL reporting tools enable companies to transform their raw data into actionable insights in real-time.
What are the Limitations of SQL?
Despite SQL’s strengths as a data querying and aggregation language, it can have limitations when used for complex data transformation. This is particularly true when writing code for iterative exploratory analysis, machine learning, complex math, or unstructured data.
SQL is a great tool for simple queries and aggregations. However, when used for more advanced data analysis, it can become a tedious and difficult-to-read programming language. For instance, when a database is not structured it requires a data preparation process to leave it ready for analysis. While SQL is able to perform data preparation, when the data is unstructured it requires a lot more coding to get the database where you want it to be.
All things considered, SQL is a valuable skill that remains at the top of the most successful technologies for business intelligence and analytics. While the processes mutate and data management becomes a less complex process, SQL is still a necessity and basic knowledge of it can make a difference in your analytical efforts.
