《管理学专业英语教程(第4版)》教学课件—lesson16 Big Data_The Managment Revolution
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Value
gimensions of Big Data
What are the key difference between “Big Data and “analytics”?
Volume refers to the amount of data an organization or an individual collects and/or generates.
❖ The three edges of the integrated view of big data represent three dimensions of big data: volume, velocity, and variety.
❖ Inside the triangle are the five dimensions of big data that are affected by the growth of the three triangular dimensions: veracity, variability, complexity, decay, and value.
Big Data: The Management Revolution
管理学专业英语教程（第四版）
LOGO
Outlines
1
Introduction
2 Dimensions of Big Data
3 Five Management Challenges
LOGO
Introduction
We define ‘Big Data’ as a capability that allows companies to extract value from large volumes of data, Like any capability, it requires investment in technologies, processes and
❖ Improved customer service Big data analytics can integrate data from multiple communication channels(e.g. phone, email, instant message) and assist customer service personnel in understanding the context of customer problems holistically and addressing problems quickly.
IBM added veracity as a fourth dimension, which represents the unreliability and uncertainty latent in data sources.
LOGO
An integrated view of Big Data
LOGO
Additional Dimensions of Big Data
Big Data≠ analytics
Oracle introduced value as an additional dimension of big data. Firms need to understand the importance of using big data to increase revenue, and consider the investment cost of a big data project.
SAS added two additional dimensions to big data: variability and complexity. Variability refers to the variation in data flow rates. Complexity refers to the number of data sources.
Big Data≠ analytics
Velocity refers to the speed at which data are generated and processed.
Variety refers to the number of data types. Technological advances allow organizations to generate various types of structured, semi-structured, and unstructured data.
❖ The growth of the three-edged dimensions is negatively related to veracity, but positively related to complexity, variability, decay , and value.
LOGO
❖ Better Pricing Harnessing big data collected from customer interactions allows firms to price appropriately and reap the rewards.
❖ Cost Reduction Big data analytics leads to better demand forecasts, more efficient routing with visualization and real-time tracking during shipments, and highly optimized distribution network management.
Impacts of Big Data Application
❖ Personalization marketing By exploiting big data from multiple sources, firms can deliver personalized product/service recommendations, coupons, and other promotional offers.
gimensions of Big Data
What are the key difference between “Big Data and “analytics”?
Volume refers to the amount of data an organization or an individual collects and/or generates.
❖ The three edges of the integrated view of big data represent three dimensions of big data: volume, velocity, and variety.
❖ Inside the triangle are the five dimensions of big data that are affected by the growth of the three triangular dimensions: veracity, variability, complexity, decay, and value.
Big Data: The Management Revolution
管理学专业英语教程（第四版）
LOGO
Outlines
1
Introduction
2 Dimensions of Big Data
3 Five Management Challenges
LOGO
Introduction
We define ‘Big Data’ as a capability that allows companies to extract value from large volumes of data, Like any capability, it requires investment in technologies, processes and
❖ Improved customer service Big data analytics can integrate data from multiple communication channels(e.g. phone, email, instant message) and assist customer service personnel in understanding the context of customer problems holistically and addressing problems quickly.
IBM added veracity as a fourth dimension, which represents the unreliability and uncertainty latent in data sources.
LOGO
An integrated view of Big Data
LOGO
Additional Dimensions of Big Data
Big Data≠ analytics
Oracle introduced value as an additional dimension of big data. Firms need to understand the importance of using big data to increase revenue, and consider the investment cost of a big data project.
SAS added two additional dimensions to big data: variability and complexity. Variability refers to the variation in data flow rates. Complexity refers to the number of data sources.
Big Data≠ analytics
Velocity refers to the speed at which data are generated and processed.
Variety refers to the number of data types. Technological advances allow organizations to generate various types of structured, semi-structured, and unstructured data.
❖ The growth of the three-edged dimensions is negatively related to veracity, but positively related to complexity, variability, decay , and value.
LOGO
❖ Better Pricing Harnessing big data collected from customer interactions allows firms to price appropriately and reap the rewards.
❖ Cost Reduction Big data analytics leads to better demand forecasts, more efficient routing with visualization and real-time tracking during shipments, and highly optimized distribution network management.
Impacts of Big Data Application
❖ Personalization marketing By exploiting big data from multiple sources, firms can deliver personalized product/service recommendations, coupons, and other promotional offers.