It’s been a really long time now, to be exact it’s been 4 to 5 years we all are quite acquainted with the term “Big Data tutorial”.But the question comes, do we really know what big data is to be exact? and How it’s making footprints on our day-to-day work and why there’s a huge demand for professionals with Big data skills? So, In this tutorial, I will give you a complete sagacity about Big Data.

There’s a list of things we are gonna cover in this whole tutorial. The following things are:

  • What is Big Data?
  • Importance of Big Data
  • Characteristics of Big Data
  • Types of Big Data
  • Challenges of Big Data

1. What is Big Data?

Basically, Big Data Hadoop Certification is a term that describes a bevy of data sets that are bulk and intricate, which is quite hellish to store and process using the available database management tools or by the traditional data operating applications. Big data are just assets that stand in need of new forms of processing to entitle enhanced analysis, insight discovery, and process hikes. It defies the frequent and facile data management methods that were designed and used up until this leap up in data. So, this is the basic knowledge about what big data actually stand for let’s get on the importance.

2. Importance of Big Data


With the rapid growth and increase of apps, social media, people and work moving online, there’s been an immense increase in data. If we have a look at only social media platforms, the interest and allure of millions of users all over the world daily. So, here the question arises, how this huge amount of data is handled and how is it processed and stored. Well, Big data can help organizations to perform multiple operations on a single platform and store Tbs of data. It can also pre-process it, examine all the data, irrespective of the size and type, and visualize it too. So, this is where Big Data plays the game.

3. Characteristics of Big Data

There are a few terms auxiliary with big data that for real make things clearer. These are basically known as Characteristics of Big Data and are termed volume, variety, and velocity. These are popularly known as the 3Vs of Big Data. As there’s continuous development and introduction to new things in the technology, it shouldn’t be shocking if more characteristics are added on, and those are called veracity and value. If we go into detail,

Volume: Organizations have to constantly keep a check on their storage solutions since big data requires a really huge amount of space to be stored.

Variety: Big data comes in a diversity of forms. It could be structured or unstructured, or even in different formats such as text format, videos, images, and many more.

Velocity: Since big data is being spawned every second, organizations need to respond in real-time to manage it.

Veracity: Big data can be huge and may contain wrong data too. Suspicion of data is something organizations have to keep in mind while dealing with big data.

Value:Just accumulating big data and stockpiling it is of no upshot unless the data is verified and a useful output is churned out.

So, these are the characteristics of Big Data, these are things you should have knowledge about before starting it.

4. Types Of Big Data


So, the data plummets into three main categories:

  • Structured Data: Any data that can be accessed and processed in a fixed format is known as structured data. Businesses can get the most out of this type of data by performing investigations. Advanced technologies help sow the seeds of data-driven awato and make better decisions from structured data.
  • Unstructured Data: Any data with an unspecified form of the structure is assorted as unstructured data. In addition to the size being huge, unstructured data creates numerous challenges in terms of its processing for deriving an outcome. A typical example of unstructured data is a heterogeneous data source containing an amalgam of simple text files, images, videos, etc. Nowadays organizations have a wealth of data available to them but unfortunately, they don’t know how to derive advantages out of it since this data is in its underdone form or unstructured format.
  • Semi-structured Data: Semi-structured data can accommodate both forms of data. We can see semi-structured data as structured in configuration but it is actually not defined.

5. Challenges Of Big Data

  • One of the conflicts with Big data is the augmented growth of undone data. The data centers and databases store enormous amounts of data, which is still briskly growing. With the expanding growth of data, organizations often find it hard on their path to correctly store this data.
  • The next provocation is choosing a suitable Big Data tool. There is a variety of Big Data Tool, however picking out the wrong one can result in a squandered effort, time and money too.
  • The next summons of Big Data is securing it. Often organizations are too busy grasping and examining the data, that they kinda ignore the data security for a further stage, and defenseless data ultimately become the nursery for the hackers.

So, we have unraveled the conundrum of Big Data for you.

I believe this article has helped you understand what is Big Data and its pros and cons.

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