2. Contents:
1) Introduction.
2) Definition of Big Data.
3) Characteristics of Big Data.
4) Importance of Big Data.
5) Phases of Big Data.
6) Challenges in analysis of Big Data.
7) Technology players in the field of Big Data.
8) Big Data opportunities.
9) Other Aspects of Big Data.
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3. Introduction:
“The growth of data is never ending.”
Today:
Data consumed in 30 seconds=40 Petabytes.
In 2015:
Data consumed in 30 seconds=120 Petabytes.
(approx. thrice)
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4. Big Data ?
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What is Big Data?
Big Data is a term used for managing large amount of datasets which is
difficult to be managed by on-hand database management tools or
traditional data processing applications.
Basically, Big Data is considered as a technology, but rather it is a
phenomenon which represents a challenge in utilizing this volume of data,
and also an opportunity for organizations who seek to ameliorate their
effectiveness.
5. Characteristics of Big Data:
Three v’s of Big data:
Volume- Amount of data
Variety- Speed rate in collecting or acquiring or generating or processing of data
Velocity- Different data type such as audio, video, image data (mostly
unstructured data)
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6. Importance of Big Data:
Government
➢ In 2012, the Obama administration announced the Big Data Research
and Development Initiative.
➢ 84 different big data programs spread across six departments
Private Sector
➢ Walmart handles more than 1 million customer transactions every
hour,
which is imported into databases estimated to contain more than
2.5 petabytes of data.
➢ Facebook handles 40 billion photos from its user base.
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7. PHASES OF BIG DATA
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A. Data Accession and Recording.
A. Information Pulling and Filtering.
A. Data Integration, Amalgamation, and Representation.
A. Query Processing, Data Modeling, and Analysis.
A. Data Elucidation and Interpretation.
8. CHALLENGES IN ANALYSIS OF BIG DATA
● Heterogeneity, Diversity and Incompleteness.
● Scalability
● Timeliness
● Privacy
● Human collaboration
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10. Big Data opportunities:
● Drive incremental revenue
● Predict customer behavior across all channels
● Understand and monetize customer behavior
● Improve operational effectiveness
● Machines/sensors: predict failures, network attacks
● Financial risk management: reduce fraud, increase security
● Reduce data warehouse cost
● Integrate new data sources without increased database cost
● Provide online access to ‘dark data’
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11. Other Aspects of Big Data:
A. Automating Research Changes the Definition of Knowledge
A. Claim to Objectively and Accuracy are Misleading
A. Bigger Data are not always Better data
A. Not all Data are equivalent
A. Just because it is accessible doesn’t make it ethical
A. Limited access to big data creatrs new digital divides
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Six Provocations for Big Data
12. Other Aspects of Big Data:
Five Big Question about big Data:
1- What happens in a world of radical transparency, with data widely available?
2- If you could test all your decisions, how would that change the way you compete?
3- How would your business change if you used big data for widespread, real time customization?
4- How can big data augment or even replace Management?
5-Could you create a new business model based on data?
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