We are living in an age of technological data innovations,
transforming every aspect of our existence right from the time we pick our
mobile handsets to know the traffic congestion on our office route or listen to
our favorite music till the time we sleep and put our phones to rest. Every
search on Google, every ‘like’ on a Facebook page, every item we purchase
online, every job search we do on a job portal, is but an addition in the
volume of data. This surge in data has shaken us out of our personal silos and
grouped us all as part of one big collection- Homo sapiens, the makers as well
as users of data.
What is Big Data?
In simple words, Big Data refers to large or hefty volume of data which can be
both, organized and unorganized. This data rather enormous data is later
scrutinized, analyzed, and studied to make meaningful inferences and
predictions which fuel the further growth of business, help in framing policies
and also drive research in fields which need enhancement. Earlier, data was
looked upon only as a supporting domain to the core business but now it has
become a separate entity essential for the sustenance of any business.
Who are Big Data Analysts?
Any data is futile without the proficiency and the expertise to analyze it. The
major question here is not how much data each business has access to, but what
use they put this data to. Hence, arise the need for trained Big Data Analysts
or Data Analysts- people who can analyze or assess data volumes to deduce
pattern, do calculations and use statistical, technical and analytic expertise
to help businesses make real, factual and data backed decisions and formulate
business strategies.
Relationship between Big Data, Data Analytics and Data Science
Big data is a term that refers to the large volumes of data – both structured
and unstructured. Data Analytics is the process of
investigating raw data with the rationale of drawing inferences and patterns
from data sets. Whereas Data Science is an interdisciplinary
domain dealing with tools, techniques and processes of digging out conclusions
and patterns from data. It encompasses all spheres of preparation, cleansing,
and analysis of data. This is best explained by the following diagram.
Advantages
Big Data analytics employs a broad gamut of skills and processes
which help in
• Root cause analysis of failures and problem areas.
• Informed Decision making
• Development of new and better goods and services
• Identifying buying habits of consumers.
• Increasing cost effectiveness
• Reducing turnaround time for events
• Better Risk management
Disadvantages
This exemplary growth in data also brings with it new challenges to shelter data, control it and prevent it from invading our privacy. Unknowingly we can become end users of fabricated data patterns which can be used to control our behavior. Identifying customers buying patterns can trigger an exodus of commercial packages exploiting the customer tendencies without them being aware of it. Big Data is like a double edged tool in the hands of policy makers and businesses that have the freedom to choose which edge to apply on the general masses. Hence, before we move further in our exploit of Big Data resources, it is our responsibility to frame global data monitoring rules and policies.
Nulearn
and IIM-Rohtak’s Certification in Data Analytics
The need to comprehend Big Data has created a need for Data
Analysts. Nulearn, an education technology company has come up with a 4-month
certification course in collaboration with IIM-Rohtak, an institute of
international repute and the only IIM in Delhi-NCR. This is an opportunity for
both fresher and working professionals to equip themselves with a course that will
improve their career prospects. Know
More about the Executive Certification in Data Analytics.
