The Role and Challenges of Data in the Digitalization Era
Prof. Veda C. Storey
Whenever she asks her students to talk about Data, they respond: "it is everywhere"
Real-time data
Integrity
Inferencing
Prediction
Integrity
Inferencing
Prediction
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Overview
1) A Digital World
2) Data Management
3) Problems and Applications
She has been working on this with Carson Woo, so he gets credits too.
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Closed vs. Open Environment
Closed - data generated, collected and used within organizational boundaries.
Open - users have access to sources of data that are open and shared (e.g. web)
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Progression of Data Management
- Structured Databases
- Big Data
- Digitalization - Continuous Innovation based on Data (we are moving here)
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1. Data Challenges
- Sheer Volume,
- Discover and interprete patterns in data,
- Technological advances (e.g. blockchain)
Traditional Data Management Challenges (we find these in the textbooks)
- Syntax
- Structure
- Semantics
- Situation (Context)
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2. Big Data
- Creative capture and application of data.
- There are many ways we can capture, organize and share data.
Big Data Challenges
- Volume is difficult to control
- Variety
- Velocity
- Veracity
- Value is difficult to assertain (in a model, Value is in the middle of the other 4 V-words)
she gave a few examples of different volumes of data - until petabytes (amount of photos on facebook). Interesting example: Wallmart - 40 petabytes of recent transaction data. This data can be modeled, maniputlated and visualized.
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Puting together the Ss from traditional data management and the Vs of Big Data.
Open challenge: how to account for all Vs and Ss in an integrated manner?
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Digitalization
Definition: conversion of analog to digital information and processes recognizes transformative role of technology as it digitizes many different aspects of processes and operations across business and society
Impact: increasing pace of digitalization means that as a society, we are changing the ways that things are done, and we must adapt.
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What are the data challenges of Digitalization?
She presented a 3D framework, showing three axis (x, y and z) with the Ss on y; Close and Open environment in x; and people, task, structure and technology on z.
*Where did the Vs go? They are important as well!
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Emerging Technology: Blockchain
In a model of Higher Education, traditionally, Universities hire professors and students pay Universities. In a blockchain model, you may take out the MiddleMan, i.e. the University. There will be some kind of smart contract: as soon as the students fulfil the requirements for their degree, they will graduate.
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They looked at the four Ss in light of Blockchain
Another 3D model, but with a cone on the x-axis.
*Strange... I do not understand why we should be worried specifically with Blockchain. I mean, there are several emerging technologies. Why does this one merit attention? She did not motivate very well this point.
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Applications - How can data help?
- Feeding 10 billion people
- Healthcare Monitoring
- Feeding 10 billion people
- Healthcare Monitoring
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