Big data describes a large
volume of data both structured and unstructured which helps a business to move
on a day-to-day basis. Gathering the data is not important, but what the
organizations do with the data that matters most. Big data is analyzed for problem-solving that leads to better decisions and strategical business moves.
Big data surrounds around
the large sets of information that grow at increasing rates. It covers the
volume of information, the velocity or speed at which it is created and
collected at a steady or viable rate, and the variety or scope of the data
points being covered. Big data often comes from various sources and arrives in
multiple formats. The definition of big data is divided into three V's:
Volume: Organizations
collect data from a variety of sources, including transactions, smart devices,
industrial equipment and more. In the past, storing was a problem, but cheaper
storage on platforms like lakes and Hadoop have eased the burden of cost.
Velocity: With the growth
in the IoT, data streams into businesses at an unmatched speed and must be
handled in a timely fashion. sensors and smart meters are driving the need to
deal with these events of data in near-real-time.
Variety: Different type of
data format in today’s world are – from structured data, numeric data in
traditional databases to unstructured text i.e. documents, emails, videos,
audios, stock data, and financial transactions.
The term ‘Big Data’ has
been coined since the early 1990s.
Big Data has been picking
up the pace over the decade. Over the course of centuries and as time rolled
by, we have been trying to use data analysis techniques to ease their
decision-making process. The ancient Egyptians around 300 BC already tried to
capture all existing ‘data’ i.e. information in the library of Alexandria.
Moreover, the Roman Empire used to carefully analyze statistics of their
military to determine the optimal distribution for their armies in the
battlefield to get an upper hand.
However, in the last two
decades, the volume and speed with which data is generated and changed the
world has changed beyond measures of human thinking. Even with the most
advanced technologies today, it is impossible to analyze all this data within
human reach. Big data has brought a revolutionary change in the new world.
Why is Big data important?
Answering important
customer questions.
- What customers want in a day to day basis
- Where they’re missing out on daily conversions
- Who their best customers are
- Why people choose different products keeping their products aside
- Every day, companies gather more useful insights into their sales and marketing questions, so they can begin to adjust their client’s campaigns. The more they learn about their customers, the more competitive company becomes.
Optimising & Understanding Business Process
Big data technologies like
cloud computing and machine learning help’s us to stay ahead of the curve by
identifying inefficiencies and opportunities in company practices.
For instance, big data
analytics can tell us that how our email marketing strategy is working, and
social media profiles aren’t reaching to the right people. On the other hand,
if using big data internally, we can find
out which parts of your company culture are having the right impact, and which
maybe causing a turnover.
Giving us a detailed analysis
Big data-based applications
help’s big data analysts, data scientists, predictive modelers, statisticians
and other analytics professionals to analyze growing volumes of structured
transaction data.
Big data in today’s world
Most organizations use big
data for their business. They understand the need to utilize the data and
extract values from it.
- Machine Learning: the concept is applied to huge quantities of data.
- Health Care & Big Data: big data has a lot of scopes and no other than healthcare can take advantage of it.
In the end, one can say
that industries are on fire with the data eruption. No sectors have remained
untouched from the technology. It has deepened inside each business and become
an essential part of business operations.
Nowadays, businesses are
focusing more on innovative ideas rather than stability. And big data analytics
has allowed us to stay updated with all the changes in business dynamics and give
them a competitive edge by predicting future trends in the market.
Big Data Applications & Examples
Big Data Implementation in the Fast-Food Industry
 |
| Image Credit: ubuntupit |
The farmer enters soil test
results and planting and harvesting data into a database used by the software program. Weather information for the immune growth
cycle of the crop is also entered into the database. The rate of precipitation
and temperatures can be automated.
Banking Sector
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| Image Credit: bigdata-madesimple |
We keep our valuable properties
in the bank for ensuring security for those items but a bank has to go through
a lot of strategies and security protocols to keep your wealth safe and well
maintained. In banks, big data is being used for many years for analysis
purpose, from cash collection to financial management, big data is making banks
more efficient and trustworthy in every sector.
Casino Business
 |
| Image Credit: analyticsinsight |
Casino Business is
profitable once they start operations with proper and security establishments.
It is important to focus on the decoration and interior design to attract the
people, primarily the gamblers. But the most important thing is maximizing
profit where big data can play the most critical role in the analysis.
Restaurants
The restaurant industry is
focusing on using data-based analytics applications more and more to establish
a place in the existing market. If we consider the restaurant business
industry, we can see a lot of competition and struggle that a restaurant has to
face to be there in the market to keep up the pace.
Big Data in Media & Entertainment
Media companies and
entertainment sectors need to drive digital transformation to distribute their
products and contents as fast as possible at the present market to keep up the
competition. The availability of searching and accessing any content anywhere
with any device becomes a huge practice
Conclusion
Author: Suvajit
Bhattacharjee (26300116041)
College: Regent Education
and Research Foundation
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