Bigdata
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This document discusses the data problem of vast amounts and rapid growth of data being generated daily from various sources. It is estimated that 2.5 quintillion bytes of data are created every day as of 2012. This data includes structured data like social media posts, photos, and videos uploaded, as well as unstructured data. The large volume and speed of data generation presents challenges and opportunities for businesses to gain insights through analytics to improve customer experience, business agility, and drive growth. However, properly addressing this big data problem requires the right technologies and solutions around areas like Hadoop, R, ETL, data warehousing, and driving analytics maturity.
Bigdata
- 1. What is the Data Problem Vast Amount of Data • As of 2012, every day 2.5 quintillion (2.5x108) bytes of data were created. • 40% projected growth in global data generated per year vs. 5% growth in global IT spending. Speed at which data is generated • YouTube users upload 48 hours of new video every minute of the day. • According to Twitter’s 2012 research, it sees roughly 175 million tweets every day, and has more than 465 million accounts. Types of structured and unstructured data • 2 million blog posts every day , 250 million photos are uploaded to Facebook every day, 864,000 hours of video are uploaded to YouTube every day. Quality of Data • Poor data can cost businesses 20%–35% of their operating revenue. Bad data or poor data quality costs US businesses $600 billion annually.
- 2. What is the opportunity with this Problem Intelligence Drive new insights Customer experience Drive all Digital asset behavior based on segmentation & Machine learning Improve Business Agility Respond to complex Business events Drive Explosive growth Use information to run targeted campaigns to accelerate click to conversion
- 3. Myths and Realities about this problem
- 6. CAPITALIZING MEANS USING “BIG DATA” - BUT WHAT IS IT?
- 11. Because we loose money
- 14. c
- 15. Product Recommendations Odds recommendations Predictions on todays game
- 16. Ask the User Inferences from Users Behavior
- 32. R includes…
- 35. The alternative to thinking ahead would be to think backwards . . . and that’s just remembering Dr. Sheldon Cooper The Big Bang Theory
- 36. Analytics Maturity Performance Analytics Predictive Analytics Prescriptive Analytics Big Data Solutions drives Analytics Solutions Maturity
Editor's Notes
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