Things you need to know about Big Data

With the advent of increasing digital technology companies have to collect huge amount of data. It is difficult to manage such huge amounts of data with normal analytical tools. This has given rise to some stronger analytical tools which are capable of making sense out of this pile of data. It has resulted in the  birth of big data analytics, which has emerged as a necessary tool requiring specialized skills.

Big Data is getting more popular by the second. Its annual Growth rate is predicted to be US$ 32.4 billion in 2017. Some reports also suggest that a whole lot of data considered as big data will be shifted to the cloud which will change the old datacenter revenue for storage. Big data is not a neat, organized data to look at as it is full of raw data coming from a variety of sources formatted differently.

Data is pulled from all types of medium-external as well as internal sources. It adds value to itself when varieties of data sources are able to overlay to see the bigger picture that comes out of those data sets. From individual data, the information that it withholds cannot be understood. So the related data needs to be seen to understand the information allowing a user to run his business effectively. Big data is not of any value till the time Data Scientists decipher, analyze and explore the data.

Big data is not a common practice in the market yet. A number of companies are in the race to exploit its uses, but it is more an initiative than a revolution. It also requires human input to work effectively. Data scientists need to check the data before it can be of any use. It is not found feasible to waste more human resource on data preparation.

With ever changing times demand for data will change and to analyze it, new tools are required. Big data even provides details that may not be of use for IT back end purposes but provides insights on other fields.

Big Data Technologies

Under the big data technology we have:

• Apache Software Foundations
• Java Based Hadoop
• MapReduce
• HiveQL

Challenges

• It is a challenge for the company to identify the right data and to use it effectively
• Big Data is a new technology so it is hard to find trained manpower to analyze the data
• Data connectivity is a hurdle in itself. Still a lot of data points are not connected among themselves leading to data that makes no sense
• With evolving data, the user needs higher technical tools to analyze it. So big data technology needs to adapt to the fast-changing times
• Security is the main concern, this makes companies take a step back and reassess how they exploit the technology

Advantages

• In present times, the consumer likes to have a one-on-one dialogue before making a purchase. Big data helps to profile customers and makes it easy to have a dialogue 
• Big data helps to revamp a product as per the market trend or consumers’ sentiments. Due to the large volume data, it helps the user to try on variations of designs and restyle as per the requirement
• Predictive analytics that run on big data runs the information about an enterprise from all sources and keeps it up-to-date, which helps the company prepare themselves for challenges
• The data collected by the analyzing tool can be sold to major companies for revenue
• The maintenance cost of big data is quite low. It can be easily replaced with an upgraded version

This is just the Beginning

Big data has started to expand so much that it is breaking the norms of traditional systems. With the increasing digitalization and the use of open source technology, massive amount of data analytics will be needed in future. So it can safely be said that Big Data is here for the Big Picture.

About the Author:

Vaishnavi Agrawal loves pursuing excellence through writing and have a passion for technology. She has successfully managed and run personal technology magazines and websites. She is based out of Bangalore and has an experience of 5 years in the field of content writing and blogging. Her work has been published on various sites related to Hadoop, Big Data, Business Intelligence, Cloud Computing, IT, SAP, Project Management and more.

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