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MARKETERS FLUNK THE BIG DATA
TEST
Big data refers to the
ever-increasing volume,
velocity, variety,
variability and complexity
of information. Data expansion over the years
Big Data
Application of Big Data
• Optimizing Machine and Device Performance
• Understanding and Targeting Customers
• Understanding and Optimizing Business Processes
• Personal Quantification and Performance Optimization
• Financial Trading
How Marketing and data work!
 Marketing optimization/performance.
 Customer engagement.
 Customer retention and loyalty.
KEY FEATURES
REASONS FOR BAD DATA ANALYSIS
• Most Organizations rely too much on gut
In today’s volatile business
environment, judgment built from
past experience is increasingly
unreliable. With consumer behaviors
in flux, once-valid assumptions can
quickly become outdated.
• Struggle with statistics
• Dangerously distracted by data
Sometimes, one can blindly follow data without applying the
human intellect. This, leads to higher risk of taking wrong
decisions.
HOW TO IMPROVE
Focus on Goal and filter out the noise
Three key qualities:
 Comfort with ambiguity
 Ability to ask strategic questions based on data
 Narrow focus on higher-order goals.
Indian Managers Globally
CHALLENGES
• Globalization of Economy
• Corporate restructuring
• Newer organizational designs
• Emphasis on knowledge management
Relevance to an Indian Manager
A manager working in some MNC can be
mislead with data. It is important to
consider that if managers get better access
to raw numbers and big data keeps
growing, the importance of the filtering
ability will only intensify, and a well well-
guided team environment will
only help in filtering out the noise, which
will further help them to achieve their goals.
Data Facts
• The amount of data generated
in two days is almost as much
as all the data before 2003.
• Harnessing Big Data could reduce Health Care costs by 8%.
• In 1985, it cost $100,000 to store a gigabyte of data. It cost 5 cents
in 2013.
• Today’s data centers occupy an area of land equal in size to almost
6,000 football fields.
Marketers flunk the big data test 2

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Marketers flunk the big data test 2

  • 1. MARKETERS FLUNK THE BIG DATA TEST
  • 2. Big data refers to the ever-increasing volume, velocity, variety, variability and complexity of information. Data expansion over the years Big Data
  • 3. Application of Big Data • Optimizing Machine and Device Performance • Understanding and Targeting Customers • Understanding and Optimizing Business Processes • Personal Quantification and Performance Optimization • Financial Trading
  • 4. How Marketing and data work!  Marketing optimization/performance.  Customer engagement.  Customer retention and loyalty. KEY FEATURES
  • 5. REASONS FOR BAD DATA ANALYSIS
  • 6. • Most Organizations rely too much on gut In today’s volatile business environment, judgment built from past experience is increasingly unreliable. With consumer behaviors in flux, once-valid assumptions can quickly become outdated.
  • 7. • Struggle with statistics
  • 8. • Dangerously distracted by data Sometimes, one can blindly follow data without applying the human intellect. This, leads to higher risk of taking wrong decisions.
  • 10. Focus on Goal and filter out the noise Three key qualities:  Comfort with ambiguity  Ability to ask strategic questions based on data  Narrow focus on higher-order goals.
  • 11.
  • 12. Indian Managers Globally CHALLENGES • Globalization of Economy • Corporate restructuring • Newer organizational designs • Emphasis on knowledge management
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  • 14. Relevance to an Indian Manager A manager working in some MNC can be mislead with data. It is important to consider that if managers get better access to raw numbers and big data keeps growing, the importance of the filtering ability will only intensify, and a well well- guided team environment will only help in filtering out the noise, which will further help them to achieve their goals.
  • 15. Data Facts • The amount of data generated in two days is almost as much as all the data before 2003. • Harnessing Big Data could reduce Health Care costs by 8%. • In 1985, it cost $100,000 to store a gigabyte of data. It cost 5 cents in 2013. • Today’s data centers occupy an area of land equal in size to almost 6,000 football fields.