About big data

From: http://www.slideshare.net/timoelliott/ukisug2014-big-data-presentation

Types of big data:

• Human generated data:
• Swipe of credit card
• Scan of bar code
• Actions captured on mobile phones
• Machine generated data:
• Data logers
• Sensors

From hindsight, to insight to foresight:

• Descriptive: what did happen
• Diagnostic: why did it happen
• Predictive: will it happen again
• Prescriptive: how can we make it happen

Types of data (sorted by % use in descending order) - ref2:

• Time series
• Business transactions
• Geospatial/location
• Graph (network)
• Clickstream
• Health records
• Sensor
• Image
• Genomic

According to Gartner (Ref3):

• Rising up to the peak of inflated expectation:
• Data science
• Predictive analytics
• In the downslope of desillusion
• Complexe event processing
• Big Data
• Content analytics

Big data can be used for:

• Engage and empower data consumers:
• Discovering new business opportunities
• Identify new product opportunities
• More reliable decision making
• Plan and optimize: Improve operation efficiency
• Personalize experience

Data lake: is a storage repository that holds a vast amount of raw data in its native format until it is needed.
HTAP = OLTP + OLAP = new generation of in-memory data platforms that can perform both online transaction processing (OLTP) and online analytical processing (OLAP) without requiring data duplication.

Ref 2: from http://www.paradigm4.com/wp-content/uploads/2014/06/P4-data-scientist-survey-FINAL.pdf

Ref 3: Gartner 2014 hype cycle: http://www.gartner.com/newsroom/id/2819918