What is Big Data?

Lately the term ‘Big Data’ has been under the limelight, but not many people know what is big data. Businesses, governmental institutions, HCPs (Health Care Providers), and financial as well as academic institutions, are all leveraging the power of Big Data to enhance business prospects along with improved customer experience.

Simply Stating, What Is Big Data?

Simply stating, big data is a larger, complex set of data acquired from diverse, new, and old sources of data. The data sets are so voluminous that traditional software for data processing cannot manage it. Such massive volumes of data are generally used to address problems in business you might not be able to handle.

IBM maintains that businesses around the world generate nearly 2.5 quintillion bytes of data daily! Almost 90% of the global data has been produced in the last 2 years alone.

So we know for sure that the best way to answer ‘what is big data’ is mentioning that it has penetrated almost every industry today and is a dominant driving force behind the success of enterprises and organizations across the globe. But, at this point, it is important to know what is big data? Lets talk about big data, characteristics of big data, types of big data and a lot more.

What is Big Data? Gartner Definition
According to Gartner, the definition of Big Data –

“Big data” is high-volume, velocity, and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.”

This definition clearly answers the “What is Big Data?” question – Big Data refers to complex and large data sets that have to be processed and analyzed to uncover valuable information that can benefit businesses and organizations.

However, there are certain basic tenets of Big Data that will make it even simpler to answer what is Big Data:

It refers to a massive amount of data that keeps on growing exponentially with time.
It is so voluminous that it cannot be processed or analyzed using conventional data processing techniques.
It includes data mining, data storage, data analysis, data sharing, and data visualization.
The term is an all-comprehensive one including data, data frameworks, along with the tools and techniques used to process and analyze the data.

Types of Big Data
Now that we are on track with what is big data, let’s have a look at the types of big data:

Structured
Structured is one of the types of big data and By structured data, we mean data that can be processed, stored, and retrieved in a fixed format. It refers to highly organized information that can be readily and seamlessly stored and accessed from a database by simple search engine algorithms. For instance, the employee table in a company database will be structured as the employee details, their job positions, their salaries, etc., will be present in an organized manner.

Unstructured
Unstructured data refers to the data that lacks any specific form or structure whatsoever. This makes it very difficult and time-consuming to process and analyze unstructured data. Email is an example of unstructured data. Structured and unstructured are two important types of big data.

Semi-structured
Semi structured is the third type of big data. Semi-structured data pertains to the data containing both the formats mentioned above, that is, structured and unstructured data. To be precise, it refers to the data that although has not been classified under a particular repository (database), yet contains vital information or tags that segregate individual elements within the data. Thus we come to the end of types of data. Lets discuss the characteristics of data.

Back in 2001, Gartner analyst Doug Laney listed the 3 ‘V’s of Big Data – Variety, Velocity, and Volume. Let’s discuss the characteristics of big data.
These characteristics, isolatedly, are enough to know what is big data. Let’s look at them in depth:

1) Variety
Variety of Big Data refers to structured, unstructured, and semistructured data that is gathered from multiple sources. While in the past, data could only be collected from spreadsheets and databases, today data comes in an array of forms such as emails, PDFs, photos, videos, audios, SM posts, and so much more.

Variety is one of the important characteristics of big data. The traditional types of data are structured and also fit well in relational databases. With the rise of big data, the data now comes in the form of new unstructured types. These unstructured, as well as semi-structured data types, need additional pre-processing for deriving meaning and support of metadata.

2) Velocity
Velocity essentially refers to the speed at which data is being created in real-time. In a broader prospect, it comprises the rate of change, linking of incoming data sets at varying speeds, and activity bursts. The speed of data receipt and action is simply known as velocity. The highest velocity for data will stream directly into the memory against being written to the disk. Few internet-based smart products do operate in real-time or around real-time. This mostly requires evaluation as well as in real-time.

3) Volume
Volume is one of the characteristics of big data. We already know that Big Data indicates huge ‘volumes’ of data that is being generated on a daily basis from various sources like social media platforms, business processes, machines, networks, human interactions, etc. Such a large amount of data are stored in data warehouses. Thus comes to the end of characteristics of big data.

The data volume matters when you discuss the big data characteristics. In the context of big data, you will need to process a very high volume of low-density or unstructured data. This will be data related to an unknown value. Example data feeds on Twitter, clickstreams on web pages or mobile apps, or even sensor-based equipment. For a few organizations, it means ten times a few terabytes of data. For some others, it could mean hundreds of times petabytes.

Source: upgrad.com