Introduction to Big Data

The term “Big Data” have been around for few years only, but there is a buzz all around about Big Data. It has become an essential part of our daily life, just like the Internet. Big Data has always been behind the scene, from an internet search to video on demand and online shopping to social media.

In this article, we will have an introduction to Big Data with some common concepts. Also, we will have a detailed overview of characteristics, types and jobs titles under this umbrella term.

What is Big Data?

There is no rule to nail down exactly what size of data can be considered as Big Data. Instead, what really define Big Data are all data management challenges that – due to increased volume, velocity and variety of data – cannot be exercised using traditional database systems. In order to use Big Data, we need a large number of physical and virtual machines connected together and processing all of the data in short span of time.

It is an efficient way to use multiple machines, and each machine will know which part of data to process and after the completion from each component, they will put together the results from all machines to make sense of that large set of data.

Big Data can be in three different forms i.e. Structured, Unstructured, and Semi-Structured. Let’s find out how one form of data is different from other.


The data that can be stored and processed in a fixed format which is in the form of a table is known as structured data. Structured data are stored in relational database management system and SQL is used to manage that kind of data. A table for student marks in a database is an example of structured data.


The data which cannot be stored and processed by traditional database unless it is transformed into a structured format is known as unstructured data. Unstructured data is heterogeneous in nature which contains texts, audios, videos, images and it is growing at a greater pace.


Semi-Structured can be defined as the form of data that does not have any formal structure which means it cannot be stored and processed in the form of table in a relational database management system. Example of semi-structured data is XML files and JSON documents.

Characteristics of Big Data

The characteristics of Big Data can be defined through 5 V’s. These V’s are for the terms Volume, Velocity, Variety, Veracity, and Value. Let’s understand these characteristics of Big Data in detail.


Volume directly refers to the amount of data, which contains enormous sets of data. It is one of the main characteristics that make data “big”. The large quantity of data that businesses are trying to harness will help them in decision making and give them future insight.


Velocity is defined as the speed at which new data is generated from the internet, sensors, and different machines and then processed in order to meet the demands. The flow of data is now in the real time, so the update window has been reduced to the fraction of the time. This real-time transaction of data has led businesses to develop Big Data solutions which can handle real-time processing and provide insights.


Variety is defined as different types of data and data resources. The type of data which is generated can be structured, semi-structured or unstructured in nature. In earlier times, the data was only found in the form of excel sheets and databases. But now the time has changed and the data is coming in the form of images, audios, videos etc.


Veracity can be defined as the uncertainty with the data. Whether the data is coming from the credible source or not? As the data is coming in different forms, it gets difficult to trust the data source in terms of the data quality and accuracy.


This is another V which has been recently added to the list and very important to talk about. Value can be defined as the economic value. When the data is big, the most important thing is to extract valuable information from that data that can be beneficial for the organization in any form.

Big Data Job Titles

After understanding the importance of Big Data, you have definitely gained some interest in Big Data career. There are a number of career options in Big Data with different job titles, such as big data engineer, data architect, data scientist, and business intelligence analyst. So, it’s the right time to understand these Big Data job titles to build your career in Big Data.

Big Data Engineer

The job responsibilities of Big Data engineers may vary from time to time. They have to manage the organization’s analytics programs and often used to work with the data architects, analysts, and data scientists to gain actionable insights from the data sets. Big Data engineers also have to do some troubleshooting to optimize systems and software involved in data pipelines.

Data Architect

Data architect is the big data career that requires business mind as well as technical skills. They need to understand the requirements of businesses from available data, and then design and deploy the databases, data warehouses, and data lakes which can be used to analyze big data.

Data Scientist

Data Scientists are the master statistician. They are responsible for the overall process of cleaning, transforming data, building models, applying algorithms, and creating a visualisation that helps organizations to gain insights from that data.

Business Intelligence Analyst

The main job of Business Intelligence Analyst is to use business intelligence, analytics, and reporting software to gain insights that shall help businesses in the decision-making process. They need to understand the management work as well as need to have good technical grasp so that they can handle analytics software well.

Data Visualization Developer

Big Data is complex in nature and tough to understand. Data Visualization Developer uses the business data to develop visual interfaces and custom visualization, so it will be easier for non-analysts and the leaders to understand and this will help them in decision making.

Bottom Line

Big data is a broad term that is growing and evolving rapidly. The organizations are adopting big data to analyze large datasets and make effective business decisions. Also, the IT professionals are moving towards Big Data to have a bright career by grabbing the available opportunities.

Big Data has been creating a new opportunity for both the organizations and professionals. The most important thing is that how you take benefit from that. So, start learning Big Data and enter into the world of opportunities and success!

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