Business Intelligence and Analytics from Big Data to Big Impact

1. BUSINESS INTELLIGENCE
AND ANALYTICS-FROM BIG
DATA TO BIG IMPACT
GROUP NO. 1
NISHANT KUMAR (90)
LOKESH KHANDELWAL
MADHUR ANAND
CHIRAG SAXENA
AMAN MALHOTRA
PRAYUT SHENDYE

2. INTRODUCTION
Business Intelligence and Analytics
(BI&A)
• Business intelligence and analytics
(BI&A) and the related field of big
data analytics.
• Business intelligence (BI) is a
technology-driven process for
analyzing data and presenting
actionable information to help
executives, managers and other
corporate end user make informed
business decisions.
Analytics
• It is “the process of exploring data and
reports in order to extract meaningful
insights.
• Which can be used to better understand
and improve business performance.
Big Data
Extremely large data sets that may be
analyzed computationally to reveal patterns,
trends, and associations, especially relating
to human behavior and interactions.
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3. BI&A EVOLUTION AND ITS
APPLICATION
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4. EMERGENCE OF BI&A 1.0
▪ It began with Analytics 1.0 or Business Intelligence in 1990s with pre-defined queries
and descriptive/historic views of structured data, like customer data, sales data, financial
records.
▪ For the first time, data about production processes, sales, customer interactions, and more
were collected & analyzed using traditional relational databases where data that fits neatly
in rows and columns can be stored relational data base management system (RDBMS).
▪ Common analytical techniques used in analysis data mining and statistical methods.
▪ Data management and warehousing is considered the foundation of BI&A 1.0.
▪ BI platforms offered by major IT vendors including
▪ Microsoft, IBM, Oracle, and SAP (Sallam et al. 2011).
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5. BI&A 2.0
• Analytics 1.0 evolved to Analytics 2.0 or Big
Data Analytics
• In 2000s it come up with features like added
complex queries along with forward-looking and
predictive.
• It work with structured and unstructured data
such as social media, mobile data, call center
logs. To deal with unstructured data, companies
also turned to a new class of databases known as
NoSQL, or not only SQL to support key/value,
document, graph, columnar, and geospatial data.
BIG DATA ECOSYSTEM 5

6. BI&A 3.0
▪ Analytics 3.0 is essentially a combination of traditional business intelligence, big data and
Internet of Things (IoT) distributed throughout the network.
▪ Analytics 3.0, which is about connecting data generated at the edge with data that is stored in
enterprise data centers.
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7. CHARACTERISTICS OF BI EVOLUTION
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9. Sport Prediction – It is used to predict the result of the sports in
2012 Predict that US would win 108 medals and they win 104 in
summer Olympics.
Easier Commutes. Now traffic lights are reactive towards the
weather conditions ,accidents and using data from GPS system.
Smartphones- They are now using technologies like google lens, voice
recognition and different features like smart gesture security.
Personalized advertisement- Big data now used to analyze your
buying behavior, according to that more relevant buying stuff is
offered to you
Presidential Campaign- Now more data is collected and predict
outcome of the elections.
Healthcare- In heath care surgeries outcome predict
through the data result and epidemic of virus threat analyze
from big data.
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10. 01
India Rank 3rd
on Artificial
Intelligence
research
02
China is on the
top list and US
is on the 2nd
place.
03
Data quality
management is
trending in 2019
04
After BI&AI
quantum
intelligence is the
future.
Global Facts
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11. Place your screenshot
here
NETFLIX SUCCESS
STORY
BY USING BIG DATA
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13. THANKS YOU
Any questions?
THANK YOU
Any Question ?
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