In the Digital age
today, world has become smaller and faster.
Global audio & video calls which were
available only in corporate offices, are now available to common man on the
smartphone.
Consumers have more
information of the products and comparison than the manufactures at any time,
any place, and any device.
Gone are the days, when
organizations used to load data in their data warehouse overnight and take
decision based on BI, next day. Today organizations need actionable insights
faster than ever before to stay competitive, reduce risks, meet customer
expectations, and capitalize on time-sensitive opportunities – Real-time, near
real-time.
Real-time is often
defined in microseconds, milliseconds, or seconds, while near real-time in
seconds, minutes.
With real-time
analytics, the main goal is to solve problems quickly as they happen, or even
better, before they happen. Real-time recommendations create a hyper-personal
shopping experience for each and every customer.
The Internet of Things
(IoT) is revolutionizing real-time analytics. Now, with sensor devices and the
data streams they generate, companies have more insight into their assets than
ever before.
Several industries are
using this streaming data & putting real-time analytics.
·
Churn
prediction in Telecom
·
Intelligent
traffic management in smart cities
·
Real-time
surveillance analytics to reduce crime
·
Impact
of weather and other external factors on stock markets to take trading
decisions
·
Real-time
staff optimization in Hospitals based on patients
·
Energy
generation and distribution based on smart grids
·
Credit scoring and fraud detection in financial & medical sector
Here are some real
world examples of real-time analytics:
·
City
of Chicago collects data from 911 calls, bus & train locations, 311
complaint calls & tweets to create a real-time geospatial map to cut crimes
and respond to emergencies
·
The
New York Times pays attention to their reader behavior using real-time
analytics so they know what’s being read at any time. This helps them decide
which position a story is placed and for how long it’s placed there
·
Telefonica
the largest telecommunications company in Spain can now make split-second
recommendations to television viewers and can create audience segments for new
campaigns in real-time
·
Invoca,
the call intelligence company, is embedding IBM Watson cognitive computing
technology into its Voice Marketing Cloud to help marketers analyze and act on
voice data in real-time.
·
Verizon
now enables artificial intelligence and machine learning, predicting the
customer intent by mining unstructured data and correlations
·
Ferrari,
Honda & Red Bull use data generated by over 100 sensors in their Formula
One cars and apply real-time analytics, giving drivers and their crews the
information they need to make better decisions about pit stops, tire pressures,
speed adjustments and fuel efficiency.
Real-Time analytics helps getting the
right products in front of the people looking for them, or offering the right
promotions to the people most likely to buy. For gaming companies, it helps in understanding which types of individuals are playing which game, and crafting
an individualized approach to reach them.
As the pace of data
generation and the value of analytics accelerate, real-time analytics is the top most choice to ride on this tsunami of information.
More and more tools such
as Cloudera Impala, AWS, Spark, Storm, offer the possibility of real-time processing of Big
Data and provide analytics,
Now is the time to move
beyond just collecting, storing & managing the data to take rapid actions
on the continuous streaming data – Real-Time!!
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