Big Data : A Beginner's Guide In 2022

 

Are you interested in knowing about Big Data? Does the field excite you? If yes, you need to know all about the field and various associated concepts. 

Big data is one of the growing fields in the industry. As the name suggests, it deals with a large amount of data. In this post, we will know all about big data, its benefits, applications, and many more.

Thus, if you wish to learn about big data in one place, continue reading the blog post. 

What Is Big Data?

Big data comprises a collection of a large set of data, management settings, real-time data, and analytics. Big data includes large chunks of heterogeneous data. 

The huge amount of data is measured in terms of terabytes or petabytes. Big data deals with a large amount of data and involves techniques and analytical tools for processing the data and deriving useful conclusions and results from the data.

Example of big data: Live streaming of cricket matches generates a humongous amount of data. The data generated from live streaming is one example of big data in real life.  

Characteristics Of Big Data

Before deep-diving into the types of big data, let's know about its characteristics of big data. Characteristics help in understanding the concepts of big data. 

Big data has the following five characteristics:

Velocity 

Velocity defines the speed with which data is produced through applications. Big data generates at a very high velocity. It also states the speed at which the generated data is processed and moved around the systems. 

Volume

Big data consists of a large amount of data in a fraction of time. The high generation speed poses a challenge in front of the IT sector. 

Many IT companies have large logs of big data but lack the power and system to process and manipulate such a large amount of data. 

Veracity 

Big data is not always accurate. A large amount of big data contains inaccurate or "dirty" data. You will never receive 100% accurate data. Thus, the quality of data varies. 

Variety 

Big data is of different types. You cannot store all categories of big data in one relational database. Thus, one of the necessary parts of dealing with big data is to divide it into appropriate categories.

Value

Deriving the potential value from big data makes it useful. If you cannot derive the value from the captured data, the data is of no use. It requires business processes to capture the desired value from the stored big data. 

Types of Big Data 

Big data has the following three categories:

• Structured Data 
• Unstructured data
• Semi-structured data

Structured Data

You can store structured data in a fixed format in your databases. Structured data can be processed, manipulated, and stored in databases. There are numerous big data techniques and algorithms to process and store data in databases. 

Unstructured Data 

Data is not a fixed format or unknown format is unstructured data. Businesses face challenges in process and derive values from unstructured data. It is comparatively more difficult to process and store unstructured data than structured data. 

Semi-structured Data

Semi-structured data is the combination of structured and unstructured data. It contains structured data but in a format not defined by the databases. 

Conclusion

Big data consists of a large amount of disorganized data. Applications and systems in real-time generate a humungous amount of data every day. Business requires ways to process and derive value from the large logs of data. 

Big data can be of multiple forms and each form has its techniques and algorithms for processing. If you want to learn big data, the first step is to know about its characteristics and types. 

I hope the blog will help you to get started with the journey of learning and mastering big data. I would be happy to hear your thoughts, suggestions, and feedback in the comments below.