seminar 2 – part 1 managing data to improve business performance ref: chapter 3 of turban and ...

Seminar 2 – Part 1

Managing Data to Improve Business Performance

Ref: Chapter 3 of Turban and Volonino

Learning Objectives1. Describe how data and document

management impact profits and performance.2. Understand how managers are supported or

constrained by data quality.3. Discuss the functions of databases and

database management systems.4. Understand how logical views of data provide

a customized support and improve data security.

5. Describe the tactical and strategic benefits of data warehouses, data marts, and data centers.

Learning Objectives cont’d

6. Describe transaction and analytic processing systems.

7. Explain how enterprise content management and electronic records management reduce cost, support business operations, and help companies meet their regulatory and legal requirements.

Applebee’s International Learns & Earns

Problem: Huge quantities of data in manyDatabases.

Solution: Enterprise data warehouse implemented.

Results: Improved profitability.

Applebee’s enterprise data warehouse and feedback loop.

Data, Master Data, and Document ManagementData management is crucial for

productivity of managers and employees

Data – Organisations key assetData decisions high quality

dataHigh Quality Data how data is

managed

Data life cycleData Management – a structured

approach to managing data.◦Principles of Diminishing Value, ◦90/90 Rule, and ◦Principles of data in context.

Analyzing Any Business

Business analytics

Data Visualization

Dow Jones industrial average (DJIA) for a single day in tabular display and graphical display.

MDM – Master Data ManagementMaster Data Management (MDM) – integrating to provide a more unified view of data

Operational versus Analytical Master Data ManagementDemystifying Master Data Management

Data management's top eight stories of 2008Human resources data analytics brings metrics to workforce management

Would You Like Fries With That? And Does Cross-Selling Justify Master Data Management?

Master Data EntitiesMain entities of company

◦Customers◦Suppliers ◦Employees

Different Master Data needs

Model of an enterprise data warehouse.

Data QualityData’s usefulnessQuality of the decision based on

the data◦Accuracy◦Accessibility◦Relevance vs. Reliability◦Timeliness◦Completeness

Data Quality Example

Document ManagementEffective business continuity planning requires

the timely restoration of critical functions after a disruption to normal business operations.

This would include developing plans for recovery of essential IT infrastructure, critical applications, and time sensitive business processes.

In the aftermath of emergency situations, however, it is all too common to find that organizations fail to plan adequately to protect and replicate paper records, as necessary to mitigate risk and continue operations.

Document Management Implementation of any record management

and/or paper digitization solution is a significant undertaking and must be approached with a detailed plan of action and significant buy-in and approval from all stakeholders. Implementation breaks down into 4 distinct phases:

Identifying objectivesIdentifying products that meet those

objectivesImplementing a systemDigitization of records

File Management Systems - Example of primary and foreign keys.

Hierarchy of data for a computer-based file.

A file Management Approach

Computer-based files of this type cause problems such as redundancy,inconsistency, and data isolation.

Database and Database Management Systems

DBMS Data Access – An integrated Approach

Database management system provides access to all data in the database.

Data Warehouse, Marts and Centers - Data warehouse framework and views.

Content Management

Electronic records managem

ent from creation to

retention or destruction.

ERM Vendors – check these out!

ACCUTRAC® SOFTWARE

Managerial IssuesReducing uncertainty.Cost-benefit issues & justification.Where to store data physically.Legal issues.Internal or external collection, storage,

maintenance, & purging of databases of information.

Disaster recovery.Data security & ethics.Privacy.Legacy systems.Data delivery.