Types of Data Under Big Data: A Tabular Guide with Examples ⚡

Big data is a term that describes the massive amount of data that is available to organizations and individuals from various sources and devices 📱. This data is so large and complex that traditional data processing tools cannot handle it easily 💥.

But what are the different types of data under big data? How can we classify and organize them in a tabular format? And what are some examples of each type of data? In this article, we will answer these questions and more 🚀.

We will also look at some of the benefits and challenges of each type of data under big data 🔥.

Types of Data Under Big Data 🌈

There are three main types of data under big data: structured, semi-structured, and unstructured data 📄.

Each type of data has its own characteristics, sources, formats, and uses 💯.

Let's look at each type of data in detail and compare them in a tabular format ✨.

Structured Data 💎

Structured data is data that is easily formatted and stored in relational databases, such as numbers, dates, or text. Structured data has a predefined schema and structure that can be queried using SQL (Structured Query Language) 💯.

Structured data is also called relational data because it is split into multiple tables to enhance the integrity of the data by creating a single record to depict an entity. Relationships are enforced by the application of table constraints 🔮.

Structured data is easy to enter, query, and analyze because all of the data follows the same format 💡.

However, structured data has limited flexibility and scalability because any change in the schema or structure requires updating all of the records to adhere to the new rules 🙅‍♂️.

Some examples of structured data are customer records, sales transactions, product inventory, bank accounts, etc. 💰.

Semi-Structured Data 🌟

Semi-structured data is data that is partially formatted and stored in non-relational databases, such as JSON or XML files. Semi-structured data has some elements of structure, such as tags or keys, but does not follow a rigid schema or structure 🔮.

Semi-structured data is also called non-relational or NoSQL data because it does not use tables or SQL to store or query data 💯.

Semi-structured data is more flexible and scalable than structured data because it can accommodate different types and formats of data without changing the schema or structure 💡.

However, semi-structured data is more complex and challenging to query and analyze than structured data because it requires special tools and techniques to handle the variety and variability of data 🙅‍♀️.

Some examples of semi-structured data are web logs, social media posts, email messages, sensor data, etc. 💰.

Unstructured Data 💫

Unstructured data is data that is free-form and less quantifiable, such as text, audio, video, or images. Unstructured data does not have a predefined schema or structure and cannot be easily queried using SQL 🔥.

Unstructured data is also called non-tabular or raw data because it does not use tables or columns to store or query data 💯.

Unstructured data is more diverse and dynamic than structured or semi-structured data because it can capture and represent any kind of information without any constraints 💡.

However, unstructured data is more difficult and expensive to store, process, and analyze than structured or semi-structured data because it requires more storage space, processing power, and advanced analytics techniques 🙅‍♂️.

Some examples of unstructured data are documents, books, articles, podcasts, videos, or photos 💰.

Tabular Comparison of Types of Data Under Big Data 📊

Conclusion 🎉

In this article, we learned about the types of data under big data: structured, semi-structured, and unstructured data 🤔.

We also learned about how to classify and organize them in a tabular format with examples 🚀.

We also learned about some of the benefits and challenges of each type of data under big data 🔥.

I hope you enjoyed this article and learned something new 😊.

If you have any questions or feedback, please feel free to leave a comment below 👇.

Happy learning! 🙌