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Understanding Types of Data in Modern Software Development


By Avalith Editorial Team ♦ 1 min read



When we talk about data, we’re talking about different types of information that’s transmitted, stored, and formatted in a particular way. In modern development, data science software is used to analyze and extract knowledge from structured and unstructured data, and the findings are used in myriad ways. Different types of data are attributes associated with a piece of data that allows a system to analyze and interpret the information. 

Why are they important? Because they ensure that data is collected in the correct format and that you get the values you’re looking for. Different programming languages use different data types for a variety of purposes. If you need to keep your data safe, it is always a good idea to count with a team of experts who can look after your data correctly. Now, what are some common data types? 

  • Integer (int): a numeric data type used for whole numbers

  • Floating point (float): a numeric type for numbers with fractions

  • Character (char): a single letter, punctuation mark, digit, symbol or a space

  • String (str or text): a sequence that is always treated as text

  • Boolean (bool): values that are true or false

  • Enumerated type (enum): numerical or text-based predefined unique values 

  • Array: list that includes elements in a specific order (usually of the same type) 

  • Date: YYYY-MM-DD format

  • Time: hh:mm:ss format

  • Datetime: both date and time in the YYYY-MM-DD and hh:mm:ss format

  • Timestamp: number of seconds that have elapsed since midnight (00:00:00 UTC), 1st January 1970 (Unix time)

Data Types in Python

Python is a versatile programming language for application development. One of the best things about Python is its enormous collection of data types, which lets you easily implement a wide array of applications. There are several Python data types with specific built-in functions, and knowing what they are and how they work will let you make the most out of your experience with the Python language. 

Some of the data types in Python include: 

  • Numeric: all data that has a numeric value 

  • Sequence Type: collections of different or similar data types

  • Set: an unordered and undefined collection of data types that consist of various elements 

  • Dictionary: an unordered collection of data values created with a sequence of elements 

  • Binary Types: bytes, bytearray and memoryview, used to handle binary data, binary files, network communication and low-level data 

Data Types in Java

Java is a programming language that is statically typed, meaning that all of the variables have to be declared before its use (specifying type and name). All data is thus predefined, and the different constants or variables for any given program have to be described with one of the data types. In Java, data types have different sizes and values that can be stored in the variable. 

Data types in Java are divided into two categories: primitive (single values with no capabilities) and non-primitive (strings, arrays, etc.). Primitive data types include boolean and numeric. The latter can be broken down into characters and integrals, with integrals including integers and floating points. Integers include byte, short, int, and long, while floating points include float and double. 


SQL, or Structured Query Language, is a computer language used to interact with a relational database. In a nutshell, it’s used to organize, manage and retrieve information from a database. In SQL, developers work with databases. It’s key to understand what type of data will be stored in each, and the different data types are generally classified into the following categories: 

  • Numeric Data Types

  • Date and Time Database

  • String Database

The previous categories include different data types, and these may vary across databases, but understanding the different SQL data types is important when creating tables and working with information within these databases because it directly affects how that data is both stored and processed. 


PostgreSQL Data Types

PostgreSQL is a very advanced general-purpose, object-relational, open-source database management system. It’s backed by over 20 years of community development, which makes it super resilient and maintains its high levels of correctness. It’s used as a data hub for multiple web, mobile, and analytics applications, among others. 

The different data types available in PostgreSQL include: 

  • Boolean

  • Character Types

  • Numeric Types

  • Temporal Types

  • UUID

  • Array

  • JSON

  • hstore

  • Special Types


Data Software 

Handling, managing, processing and simply using data in general is done by using different available data software options. This software is essentially the tool that helps you sift through and utilize all of this information however you need to. With so many different data software options available, let’s look at some of the main types: 

  • Qualitative data analysis software: this is used to analyze patterns or relationships in a specific dataset and can be used to process data and extract information or insights for more analysis. 

  • Loss prevention software: this software is used to look for and detect data breaches, unauthorized access to data, and can also be used to block access to sensitive data if it’s being stored in a database or shared in any way. 

  • Data entry software: this software helps automate manual data entry processes, making it more efficient and faster. It replaces analog data storage (paper) by storing data in a more user-friendly format, like a digital database, helping to also make it more accessible. 

  • Data migration software: used to move data from one source to the next, essentially moving data to a different location, file format, storage system, etc. 

  • Big data software: as its name suggests, this software is used for managing and processing big data (some data sets are too large or complex, so normal or traditional systems aren’t able to accommodate them). 

  • Analytics: these tools help data analysts carry out their processes, with the common goal of assisting companies in making better, more informed business decisions. 

  • Data recovery software: these are tools that help you recover data that’s been lost or deleted quickly and easily. 

  • Data management software: these software options provide users with tools that help ensure that their data is ready for analysis and accurate, consistent, secure and compliant. 

  • Data backup software: you can use these tools to help copy and save your data to external sources like a drive, a server, a larger data center, or the cloud. These can be installed on any of your devices and systems. 

  • Software for customer data: these tools help streamline customer and prospect communication and engagement across different touchpoints in the consumer journey. These are often a part of systems like CRMs or customer relationship softwares already. 

Modern software development encompasses different types of data, and these vary across programming languages. Understanding common data types and how they function across different systems will help you analyze correctly and interpret the results in the best way possible for the right purpose. At Avalith, our experts can handle and solve your doubts while boosting your website's performance. Learn more about us here!