Big Data
You obviously must have heard of this term. It keeps on ringing around these days, as a very common yet fancy term. Quite clear by its name, Big Data actually does have relevance to Big Data. I was recently assigned to big data team in the company I work for. So I googled a lot about it and found some very interesting things about and in Big Data.
You can simply define big data as enormous amount of data, coming in at high speed in variety of forms. It is the data generated by social networking sites, search engine searches, video streaming and possibly any internet resource that you use.
Single Jet engine can generate 10+terabytes of data in 30 minutes of a flight time. With many thousand flights per day, generation of data reaches up to many Petabytes.
Big data can be analyzed for insights that lead to better decisions and strategic business moves. So the suggestions that you see while buying something online are not mere guesses.
Big data’s big potential
The amount of data that’s being created and stored on a global level is almost inconceivable, and it just keeps growing. That means there’s even more potential to glean key insights from business information – yet only a small percentage of data is actually analyzed.
Why Is Big Data Important? (source : www.sas.com)
The importance of big data doesn’t revolve around how much data you have, but what you do with it. You can take data from any source and analyze it to find answers that enable 1) cost reductions, 2) time reductions, 3) new product development and optimized offerings, and 4) smart decision making. When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:
Determining root causes of failures, issues and defects in near-real time.
Generating coupons at the point of sale based on the customer’s buying habits.
Recalculating entire risk portfolios in minutes.
Detecting fraudulent behavior before it affects your organization
Thus there is a big possible future in this field as the rate at which the data is being produced will only increase with every passing day. Data storage experts and Data analyst will be in great demand in the coming future.
Many applications have been developed to tackle the Big Data challenges. The entire Hadoop Ecosystem focuses on solving this problem.
Ranging from reading a Big Data file to storing it on the file system and performing various analysis operations on it, everything can be done with all the applications of this ecosystem. Every application has its significance of its own.
If you really want to step into this field, then don't hesitate. Get started with some of these fancy terms:
Hdfs
Sqoop
Hive
HBase
Spark
In case of any query do comment. Do follow and upvote if you like it
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