The Role of SQL and Python in Data Analytics

Introduction:

In the age of information, understanding the intricacies of data analytics is paramount. This article provides a comprehensive overview for budding data analysts, software developers, and tech enthusiasts. We’ll unravel the significance of SQL and Python in the realm of data analytics, covering the basics, applications, and the best resources for learning.

What is Data and How is it Collected?

Data is the lifeblood of organisations. Data is the plural of the word datum which simply means “a piece of information”. Two or more pieces of information are data. Organisations collect data through different ways and means. To illustrate this, when you fill out a paper-based form for a new bank account, you are providing the bank with your data. The data could be transformed from its current paper-based form to digital data through a scanner or by simply typing the data collected into the system and saving them to the digital database.

What is Data Analytics?

Data analytics is a comprehensive approach that involves the use of various techniques and tools to scrutinise, refine, and transform raw data into meaningful insights. It encompasses the entire process of collecting, processing and analysing data to identify patterns, trends, and relationships that can be used to make informed decisions. By leveraging data analytics, organisations can gain a deeper understanding of their operations, customers, and market trends, which can help them optimise their strategies and achieve their goals more effectively.

What is SQL and What Role Does it Play?

As we mentioned before, data collected by organisations are typically stored in databases. A relational database is a type of database that stores and provides access to data which are related to one another.

Relational Databases

Going back to the previous example about opening an account with a bank, once you submit your form, the bank staff will use the form to enter your information into their system. If the bank is using a relational database (which is highly likely), your data will be stored in the “customers” table in the database. When your account is created and they issue you an account number, the account details will be stored in the “accounts” table (or its equivalent) in the database, and depending on the relationship the bank allows in their database, you may be permitted to have only one account or more than one accounts.

An Example of an Entity Relationship Diagram (ERD) of a Bank’s Database (Source: [semanticscholar.org]([https://www.semanticscholar.org/)).](https://prod-files-secure.s3.us-west-2.amazonaws.com/e47c7918-e631-4008-a7cc-31d4e79679e6/0dca9c86-5780-48c1-b7bb-d22102831261/Untitled.png )

An Example of an Entity Relationship Diagram (ERD) of a Bank’s Database (Source: semanticscholar.org).

SQL

Structured Query Language (SQL) is a widely used programming language that is specifically designed to manage and manipulate relational databases. It provides a powerful set of tools for creating, modifying, and querying databases, making it an essential tool for data analysts, developers, and database administrators. With SQL, you can easily retrieve, sort, filter, and aggregate data from large datasets, and use the data to make informed decisions and gain valuable insights. However, it is important to note that SQL is not designed for cleaning or analysing data. This is where Python or R programming languages come in handy.

What is Python Programming Language?

Python is a high-level, interpreted programming language that is widely used in various fields such as web development, scientific computing, data analysis, artificial intelligence, and more. It was created by Guido van Rossum in 1991 and has since become one of the most popular programming languages in the world.

One of the key features of Python is its readability, which makes it easy to learn and understand. Its syntax is straightforward, making it an ideal language for beginners. Additionally, Python is highly versatile and can be used for a wide range of applications.

Why are Python and SQL Important in Data Analytics?

The synergy between Python and SQL is pivotal in data analytics. While SQL is very useful for pulling out data from the database, Python is a valuable tool for data cleaning and visualisation. Its libraries, such as NumPy, Pandas, and Matplotlib, provide powerful data analysis and visualisation capabilities. With Python, analysts can easily manipulate and analyse large datasets, and create powerful visualisations to help communicate their findings.

Conclusion:

In conclusion, mastering SQL and Python is not merely about learning languages; it’s about gaining a competitive edge in the dynamic field of data analytics. By combining SQL and Python skills, you can perform complex data analysis tasks, such as predictive modelling and data mining, which can help businesses make informed decisions and gain a competitive edge.