From Big Data to Smart Data 1st Edition by Fernando Iafrate ISBN 1848217552 978-1848217553

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Product details: 

ISBN 10: 1848217552 

ISBN 13: 978-1848217553

Author: Fernando Iafrate

A pragmatic approach to Big Data by taking the reader on a journey between Big Data (what it is) and the Smart Data (what it is for).

Today’s decision making can be reached via information (related to the data), knowledge (related to people and processes), and timing (the capacity to decide, act and react at the right time). The huge increase in volume of data traffic, and its format (unstructured data such as blogs, logs, and video) generated by the “digitalization” of our world modifies radically our relationship to the space (in motion) and time, dimension and by capillarity, the enterprise vision of performance monitoring and optimization.

Table of contents: 

1 WHAT IS BIG DATA
1.1 The four “V”s characterizing Big Data
1.1.1 V for “Volume”
1.1.2 V for “Variety”
1.1.3 V for “Velocity”
1.1.4 V for “Value”, associated with Smart Data
1.2 The technology that supports Big Data

2 WHAT IS SMART DATA
2.1 How can we define it
2.1.1 More formal integration into business processes
2.1.2 A stronger relationship with transaction solutions
2.1.3 The mobility and the temporality of information
2.2 The structural dimension
2.2.1 The objectives of a BICC
2.3 The closed loop between Big Data and Smart Data

3 ZERO LATENCY ORGANIZATION
3.1 From Big Data to Smart Data for a zero latency organization
3.2 Three types of latency
3.2.1 Latency linked to data
3.2.2 Latency linked to analytical processes
3.2.3 Latency linked to decision-making processes
3.2.4 Action latency

4 SUMMARY BY EXAMPLE
4.1 Example 1: date/product/price recommendation
4.1.1 Steps “1” and “2”
4.1.2 Steps “3” and “4”: enter the world of “Smart Data”
4.1.3 Step “5”: the presentation phase
4.1.4 Step “6”: the “Holy Grail” (the purchase)
4.1.5 Step “7”: Smart Data
4.2 Example 2: yield/revenue management (rate controls)
4.2.1 How it works: an explanation based on the Tetris principle
4.3 Example 3: optimization of operational performance
4.3.1 General department (top management)
4.3.2 Operations departments (middle management)
4.3.3 Operations management (and operational players)

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Tags: Fernando Iafrate, From Big Data, Smart Data