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| Data Science |
At the age of smart technology, everyone though not well-cognizant,
but has some length of knowledge about data science.
For big businesses, data science has immensely transformed
the way we used to see the business operations a few years back. With
ever-changing and increasing technology, businesses are highly reliant upon these
technological advancements. And big data helps increase as much as 60% of
operational efficiency in the retail sphere right across the globe.
The same technology could save European Government up to $149
billion per year on their operating expenses.
The margin shows how data science can be so useful and
critical for the growth of any business.
But before we advance, let us know about data science.
Data Science
Data means information, and it is available over the web. The
available data is categorized and sorted out using scientific technology based
on the user preference.
Data scientists are those who use various lengths of
algorithms and expertise to categorize information, and mold them for the users.
It is not that only big companies are financially capable to
use data science. But, the growth of block chain has made it possible for small
and medium sized companies to churn out information from data science too with various
available tools.
Data
Science revolutionizes the Business
Industries ranging from the manufacturing to retail and financial
service to travel have perked up their growth and performance efficiency by leveraging
data science.
Businesses see their growth through various algorithms of data
science that helps harness customer behavior and yield revenue opportunities.
Manufacturing
Industry
Data science offers insight-driven solutions for businesses,
especially for the manufacturing industry.
The automotive giant Ford turned around and emerged as a
leader despite facing the largest financial loss worth of $12.6 billion in
2007, and it was all for forward thinking innovation-data science. In 2009, they came out as a winner for selling
2.3 million cars, more than any other car maker to sell above 2 million cars in
a single year. Alongside, they launched as many as 25 new cars in the next two
years.
Ford relied upon the Smart
Inventory Management System or SIMs
to improve the driving experience with the right engine and features, so no
cars remain left behind at the dealership once the customer comes in. SIMs
harnesses the largest ocean of data necessary to analyze different algorithms, including
what specifications customer search on the company website, data on sales and
manufacturing type, data on customer preference of models in respect of other models
in the inventory and data on employment rates and housing prices within the
dealership territory.
And SIMs data optimizes stocks in the inventory and car
features to meet consumer preferences. SIMs gauges every tiniest detail of
consumers’ preferences on interiors, car floor and roof heights and wheels too.
So, it is easier to collect millions of data on consumer behavior and fine-tune
them to produce a unique product.
Another algorithm used by Ford is text-mining. They harness social data from social media posts to gauge
insights into customer behavior related to their models. This type of data is
far more advanced and efficient from market research that offers a real-time analysis
about decision making. Based on this prediction and data mining, Ford was to
choose between a flip-glass system and an improved power liftgate equipped with
sensors for their previous model Ford Escape. And the data mining helped them choose
liftgate for their customers. This helped them reduce financial risks as well
as manufacturing complexity.
Transforming
The Commuting
We cannot deny that Uber has transformed the transportation scope
by introducing the traveling freedom at riders’ demand a few years back. They
too leveraged data science to build this type of infrastructure for the masses,
and have been providing them with the freedom to choose a lot of options to meet
their demands.
Uber has their own machine learning program known as Data
Science Workbench, helping them in day-to-day operations.
One of the issues for the rider is waiting for the car to
arrive at the pick-up location. An Uber-partner driver cannot move due to the
traffic, building the anticipation of the rider for not getting any response
from the end receiver. This has been one
of the most challenging problems for Uber as it led to cancellation of the
trips. Uber introduced smart reply systems called one-click chat (OCC), using natural
language processing or NLP and machine learning. UberChat has this inbuilt feature to let driver-partner
get in an instant conversation with relevant replies to the rider.
OCC is developed on Uber’s Michelangelo platform to enable NLP
based replies on rider chat messages. Once it receives messages from a rider,
it allows the driver-partner to choose from a list of options to detect intent
of the message. The system has four reply options and the driver-partner can
choose any of the relevant responses to ease the confusion of the rider.
Besides this, Michelangelo helps Uber solve a range of other issues
such as fraud, financial and marketplace forecasting that could hinder their
operations and impede their growth. Leveraging Data Science for each of their
business processes, including UberEats and Uber Freight is significant and
relevant.
Data science is dynamic that transforms not only businesses
but also human life and enriches their experiences.
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