About Big Data & Big Data Analytics:
To start with
Big Data Analytics, we must know what Big Data is as compared to our real world.
Practically, Big Data is something that we frequently face in our day to day
life. If a data has outgrown the storage and processing capabilities of a
single host, then such data is considered as a Big Data .As the name indicates, Data with an enormous size and high complexity that is difficult to store and
process is a Big Data.
Challenges faced
with Big Data and Big Data Analytics
Functionally Big
Data is similar to ‘small data’ , but bigger in size. Bigger data requires
different approaches in terms of techniques , tools and architecture.
Fundamental challenges involve are : How
to store and How to work with
voluminous data sizes. Most importantly is how to understand data and turn into a competitive challenge.
Let’s figure out
where we are lacking behind in this field that become a root cause for such
mass trouble. Below mentioned is the statistics about growth and technology
changes in past few years in terms of CPU speeds, RAM memory , Disk Capacity
and Disk Latency
The above data
clearly shows that we had made adequate contribution towards factors like CPU
Speeds, RAM etc. but we are still lagging behind in terms of Disk Latency.
The key
responsibility is to introduce specialized algorithms that will enhance the
processing speed and capabilities of our systems which can understand more
complex data well enough to process them.
Big Data
Analytics is the modern day subject that takes birth as a remedy tool for Big
Data. It includes specialized techniques that are different from our
traditional techniques for handling data. Away from only database and
programming skills, multiple skill sets are required in this field. It’s a
combination of statistics, programming and database skills.
Business Impacts
through Big Data
As already
discussed Big Data is something that causes malfunctioning of our data
management systems. On the other hand it’s the part of the day to day general
data and nobody wants to lose even a single piece of data. Each and every data
is important in terms of business. Hence rather than skipping such data they
require to store them which stands very costly and difficult to process. Every
firm now-a- days are in a very urge need of Big Data Analytics.
Tools to handle
Big Data
Modern
frameworks are introduced to handle Big Data like HADOOP, SPARK etc.
These
technologies use a different approach to analyse and process data. Instead of
using physical data base they use virtual database that reduces the storage
cost and processing time up to a great extent. Unlike traditional systems ,
Hadoop implements multiple individual processes iteratively instead of one
single batch process that makes it lot efficient and faster for processing and
storing data .Below diagrams shows the difference.
Scope of Big Data & Data Analytics:
A McKinsey
Global Institute study states that the US will face a shortage of about 190,000
data scientists and 1.5 million managers and analysts who can understand and
make decisions using Big Data by 2018.For people interested in this field, it
will be a job assurance field with higher salary packages and perks.
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