Top 7 Data Formats for Analytics and Visualization

What are data formats?

How do they help you in your work? Let us take a look at some data format examples. 

XML Data Formats.

XML data formats are quite popular and have become the standard for representing a large amounts of structured data. The XML data format is generally categorized into three varieties: text, utf-8, and binary.

Text Data Format.

This is a basic data format and is either an array of bytes, a character or a single string. For example, the value “123” would be represented as ‘text’ in this format. Text data file formats can be easily converted into any other format such as cyphered character string (CSHTML) or plaintext. Text data file formats can be used extensively for web applications and document management. This format can also be used for storing information and document collections.

Api Data Formats.

This data format allows developers to conveniently access stored entity information. It uses keywords to uniquely identify every entity within the database. The dictionary consists of the class names, roles, and values. There are also a number of features of this format such as searchable by content type and having an identity directory.

Database-Based Data Formats.

In this type of data format, information is stored as tables and related values. One example of a database-based data format is MS Access where all data is stored in tables. Other examples include Java and SQL. The database-based format allows easier access to information compared to text-based data formats.

Tabular Data Formats.

This is one of the types of data formats that are commonly used and has been in use since the early ’80s. It contains rows and columns, although there are no associated complex structures. It is usually used to represent a collection of objects or data.

JavaScript Data Format.

This format is written in JavaScript and can be accessed through a JavaScript application or a browser. One drawback of using this format is that text objects cannot be indexed. In addition, text data formats are not searchable.

Resource Books.

There are many proprietary formats that can be used to provide indexing and navigation of documents in an easily readable format. The major advantage of these data formats is that they do not expose data that is protected by patents or other rights.

Simple Text File Format.

This is a text format that is based on simple text and can be read by computers with a markup language such as HTML. There is no need for programming and a variety of text editing capabilities apart from the required encoding of the document. This file format is simple and easy to learn. It has been in use for decades but is still extensively used in some places.


Hypertext Markup Language is a markup language that creates tables, lists, images, and other types of structured documents. HTML is an open format, which means it is capable of being manipulated by a computer even after the format has been saved into a file. Many websites use this format to add a user-friendly user interface to their websites.

Plain Text.

This is the most basic of the three types of data interchange formats. This is the common format for ordinary text. This is also the easiest to work with as well as being highly flexible for data transformation.

Data visualization software packages.

The data visualizations are often based on matrices, charts, scatter plots, and other graphical representations of data. These packages give an overall view of data that can be analyzed using various techniques. These packages can be downloaded for free. Some data software like the one reviewed at have to be purchased or paid for but they are very useful in increasing the productivity and profitability of any organization using data in business.

Choosing a data format depends entirely on your needs. You need to consider the audience of your data, available file formats, and the complexity of your data manipulation task. Data format conversion tasks can be outsourced to companies offering expertise in converting data files into the data format required by your organization. However, you can choose a data format yourself depending on your own needs and preferences, and technical expertise.