DISCUSSION AGENDA

Introduction to BI&A

Evolution of BI&A

Applications of BI&A

BI&A Researches

Conclusions

Introduction to BI&A

Business Intelligence deals with

Current Business Data Collection

Business Data Inputs

Data Conversions

Business Analytics

Uses statistical and quantitative tools

Builds explanatory and predictive modeling

Techniques, technologies, systems, practices,

methodologies and apps that analyze critical business data

Introduction to BI&A

Extremely large data sets (Terabytes to Exabytes)

Complex (such as social media) where data lacks

uniformity

Data can be unstructured or structured

Requires advanced/unique storage, management

and analysis

Introduction to BI&A

Introduction to BI&A

Available data continues to increase and cost

of data acquisition and storage is/has been

declining

How is Big Data used?

Markets and Consumer Behavior

Product Development

Prompt Business Decisions

Service Improvements

Introduction to BI&A

Introduction to BI&A

IBM Tech Trends Reports that 93% of companies identify business

analytics as one of four major tech trends in the 2010s

Estimated shortfall of 140K 190K people with deep analytical skills by 2018

1.5 million data-savvy managers to analyze big data effectively

97% of companies with revenues over $100M use some form of

business analytics

Bloomberg BusinessWeek (2011)

Introduction to BI&A

Evolution of BI&A

1000 Times 1000 Times

Before 2000

Before 2010

From 2010

Evolution of BI&A

Data are mostly structured.

Collected by companies through various legacy systems

Mostly command line interface system

Limited Internet connectivity, only for data analysis

Eight characteristics 1. Reporting, 2. Dashboards, 3. ad hoc query,

4. Search-based BI, 5. OLAP,

6. Interactive visualization 7. Scorecards,

8. predictive modeling and data mining.

Evolution of BI&A

Data are both structured and unstructured. Besides the traditional RDBMS data is also collected about users

Traditional database works in combination with social media

Deals with lot of user generated contents Photos Videos Blogs Gaming data Shopping data

Eight characteristics mostly unchanged, have little better search capabilities

Evolution of BI&A

Data collected are more location aware, person-centered, and context-relevant.

Some modern advanced data analytics tools claims to address all 13 characteristics Gartner BI platform.

These tools have support for RFID, barcodes, and radio tags

There are some lightweight RDBMS tool for mobile devices.

Applications of BI&A

Applications of BI&A

Data sources: User searches, customer transaction logs, user generated contents.

Analytics: Association rule mining, Anomaly detection, Social network analysis, Text

and web analytics

Influences: Long-tail marketing, personalized recommendation, increased sale and

customer satisfaction

Example:

Data sources: Public surveys, citizens & government employees feedbacks

Analytics: Information integration, Content and text analytics

Influences: Improving government transparency, empowering citizens

Example:

Applications of BI&A

Data sources: High volume of system generated data.

Analytics: Specific mathematical and analytical models

Influences: Technological improvements of existing products or services,

revolutionary new products or services.

Example:

Data sources: Personal health information, Electronic health records (EHRs), medical

researches.

Analytics: Genetic research, Patient network analysis, Adverse drug side-effect analysis

Influences: Improved healthcare system, Improved patient empowerment

Example:

Applications of BI&A

Data sources: Criminal records, crime maps, criminal network intelligence, cyberspace

monitoring.

Analytics: Criminal association rule mining and clustering, Multilingual text analytics,

Cyber attacks analysis and attribution

Influences: Improved safety and security

Example:

Applications of BI&A

Traditional DBMS

Big Data Handlers

Mobile Data Handlers

Applications of BI&A

Applications of BI&A

Adaptive Analysis

Extended from: Competing on Analytics, Davenport and Harris, 2007

Traditional

New Data

Standard Reporting

Ad hoc Reporting

Query/Drill Down

Alerts

Forecasting

Simulation

Predictive Modeling

Optimization

Optimization under Uncertainty

Continual Analysis

Entity Resolution

Annotation and Tokenization

Relationship, Feature Extraction

New Methods

BI&A Researches

(Big) Data

Analytics

Mobile

Analytics

Network

Analytics

Web

Analytics

Text

Analytics

BI&A Researches

Foundational Technologies

RDMS, Data Warehousing, ETL, OLAP

Emerging Research

Statistical machine learning Sequential and temporal mining Spatial Mining Process Mining Parallel DBMS Cloud Computing

(Big) Data

Analytics

Foundational Technologies

Information Retrieval, Search Engines, Enterprise Search Systems

Emerging Research

Statistical NLP Opinion Mining Multilingual Analysis Mobile IR

Text

Analytics

Example:

Example:

BI&A Researches

Foundational Technologies

Bibliometric Analysis, Social Network Theories, Network Visualization

Emerging Research

Link Mining Dynamic Network Modeling Agent-based Modeling Virtual Communities

Network

Analytics

Foundational Technologies

Web services, Smartphone Platforms

Emerging Research

Mobile Web Service Mobile Sensing Apps Mobile Social Networking Mobile Visualization Mobile Advertising and Marketing

Mobile

Analytics

Example:

Example:

BI&A Researches

Foundational Technologies

Information retrieval, Computational Linguistics, Web Service, Mashups

Emerging Research

Cloud Services Cloud Computing Social Media Analytics Web Visualization

Web

Analytics

Example:

BI&A Researches

Researchers Trend

BI&A Researches

BI&A Researches

BI&A Researches

Education Challenges

Business Industry shifted to Data Analysis & rapid Business Decision Making

Decision making largely take place in Marketing, Finance and Logistics

Business School started to educating professionals

BI&A Knowledge and Skills

Critical analytical & IT skills

Business domain knowledge

Communication skills

Program Development

Master of Science (MS) degree in BI&A Add a concentration in existing MS IS program BI&A certificate program

Conclusions

Technological improvements Rapid increase of mobile device usage More proliferation of social networking Service integrations & customizations

Performance Latency and Reliability Control & Maintenance Security & Privacy Vendor Lock-in standards