big data -get in startup

We are creating a large amount of data, called big data, every day. How and what is Big data? This is we are going to explore in this blog. We use the internet, social networking websites, e-commerce websites, and many other platforms every day and creating a very huge amount of data. From comments, posts you are posting on the network to the blogs you are writing and buying a product form internet, you are creating it every moment. You may have noticed that you now get similar ads on Facebook and Google related to the product you bought from an e-commerce site. They are able to do this because they can analyze a large amount of data you created (Read here more about the technology used for this). If you are getting confused let’s explore this in details.

               Big data is a term which refers to large volume of data – structured or unstructured – which is so big and complex that it is difficult to handle, store and analyze. This large amount of data is mainly created by new data sources. The biggest source of big data is, of course, internet. As I mentioned above some ways by which you are creating a part of this big data by using internet. But you are not only creating big data, the devices all around the world connected to internet are also creating a big amount of big data every moment( read this blog to know more about Internet of things). The amount of data that is being created and stored now on a global level is almost unimaginable and it is keep growing every day.

But these massive data have big potentials and can be used to address business problems in an incredible way and also for many research purposes. The big data usually includes data sets that are having sizes beyond the ability of commonly and traditionally used software tools to capture, manage and process data fast. It comprises unstructured, semi-structured and structured data, however the main focus is on unstructured data as it is hard to deal with that. The size of data that can be referred as Big data is a changing term and not fixed, as of 2012, ranging from few dozen terabytes (approx 1012 bytes) to many exabyte (approx 1018 bytes) of data.


The big data term has been in use since the 1990s and the act of gathering and storing large data is also not new, but this extended to a new levels after 2000, due to increased use of Internet. This concept gained a momentum in 2000s when industry analyst Doug Laney defined this as the three characteristics- three Vs – velocity, variety and variability.


Volume, size of data is main characteristic defining big data. Big data comprises processing high volumes of unstructured data. For some organizations, this can be tens of terabytes of data and for some it may be hundreds of terabytes.


This refers to the speed at which data is generated and processed. At the global level big data is generating at a very fast rate which is difficult to handle. Many applications and smart products operate on real time and requires real-time evaluation of data and action, or at least fastest possible.


Variety refers to different types of data that are captured. Traditionally we are managing structured data using relational database. With the rise of big data, there is also a big amount of unstructured and semi structured data generated. Such as text, audio and videos, which requires additional processing and technologies to derive meaning and support metadata.

There are also some more additional characteristics joined in this definition over time like Value and Veracity.

big data -get in startup

Challenge and Technologies

Big data had many challenges around it, which includes capturing data, data storage, data analysis, search, query processing, sharing, updating, information privacy etc. Now the term ‘Big data’ is tend to the use of predicative analytics, analyzing user behaviour and some other advance data analytics research. Around 2005, people began to realize that how much data they are generating through Facebook, YouTube and other online services.

Then there are also technologies evolved for handling this Big data. Hadoop is the popular framework developed that same year which is an open-source framework created specially to store and analyze big data. In 2012, more recently Spark which is also a open source framewok is developed. NoSQL is also developed and gaining popularity. The development of these tools was essential for the growth of big data because they make easier and cheaper to work with large amount of data. Also due to the recent technologies inventions it is less expensive to store data and compute. Due to recent growth in IoT, we are generating more data. Cloud computing has also expanded the possibilities of big data further. (Read here more about Cloud Computing).      

Benefits of Big Data

The importance of big data comes from many ways through which we can extract useful information from that large amount of data. We can analyze data and find ways to cost reductions, time reductions, new product development, smart decision making.


With high-power analytics we can accomplish many business-related tasks such as:

  • Determining in real-time the main causes of various failures, issues and defects.
  • Analyzing customer’s buying habits and providing realvent advertisement.
  • Calculating risk portfolios in minutes.
  • Detecting fraudulent behaviour before it affects organization.


Banks are faced with the challenges of managing a big data of users, from the starting. The important goals of bank like customer satisfaction, minimizing risk and fraud can be really helped with big data analysis. They can stay one step ahead of the game with advanced analytics.


Government really deals with a big data and it’s important for that to handle accurately. Big data analytics can also help them in managing utilities, running agencies, dealing with crimes.


By analyzing data, we can identify at-risk students, keep an eye on progress of students and implement better system for evaluation.


It can help in an incredible way in building customer relationship, which is critical to the retail industry. We can find the best way of marketing, effective way to handle transaction and many more.

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