What is Big Data?

  • When data sets became so large and complex that they could no longer be managed using on-hand database management tools, we saw an emergence of Big data technologies.
  • This new generation of technologies and architectures were designed to extract economic value from datasets by enabling high-velocity capture, discovery, and analysis.
  • As a result of their invention, we now experience an entirely new information economy, “Infonomics:  The Practice of Information Economics”
  • Inadequately monitored and largely unregulated, this presentation will highlight ways that this Big Data puts our business strategy and Bay Area economy at Big Risk.
  • What is the Value of our Big Data?
  • Facebook “likes” and Twitter “tweets” are reported to represent $14 per “share” and $5 per “tweet”. *
  • Either a company will report an increase in revenue, or a company will pay for that tracked human behavior.
  • Either we prove that a human committed that behavior, we prove that the activity had a sales result, or we stop accepting false claims.
  • We need to do at least one.

How We Use Big Data

  • Marketing Campaign Analysis
  • Recommendation Engine
  • Customer Retention and Churn Analysis
  • Social Graph Analysis
  • Capital Markets Analysis
  • Predictive Analytics
  • Risk Management
  • Rogue Trading
  • Fraud Detection
  • Retail Banking
  • Network Monitoring
  • Research And Development

Archiving Please read more at the source Talend

While Business Intelligence has had some time to mature.

Big “social” data projects are new to the requirements of governance.

It appears we may not be equipped for rapidly evolving changes to enterprise management and data governance.

  • Limited Big Data Resources
  • Poor Data Quality = Big Risks
  • Project Governance not Fully Understood
  • What is a user worth? (Valuation)
  • What is a good user (Validity)
  • What is a real user vs. a fake user? (Accuracy, Fraud)
  • Open Container V. Closed Container

The concept of tampering is critical to valid data sources.

  • Science, Manufacturing, Forensics, Law, all consider the source of information and the capacity that others would have had to alter them.
  • Big data has moved the emphasis of business intelligence from closed to open containers. 
  • How should this affect our willingness and decisions to use that body of data? 
  • Which companies will analyze, and compile results and scores based on that information?
  • What will be our grounds to select those vendors and how will that selection be controlled by contract and SLA?
  • What is the Basis to Trust Those Who Measure Social Data?

External link - may require a login - you are leaving this site 10 SOCIAL MEDIA STATISTICS YOU NEED TO KNOW IN 2021 [INFOGRAPHIC]

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