week 02 - topic 03 - data, text _ document management

John von Neumann Institute - Vietnam National University Ho Chi Minh CityInformation Technology for ManagersBMIT5103 Information Technology for ManagersBMIT5103

Week 02 - Topic 03

DATA, TEXT & DOCUMENT MANAGEMENT

BMIT5103 Course

Information Technology for Managers

Dr. Huy Nguyen


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STUDY GUIDE

TOPIC 03Data, Text & Document Management

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Learning outcomes:

1. Data, text & document management & their impacts on performance;

2. File Management systems;

3. Functions of databases & Database Management systems;

4. Tactical & strategic benefits of data warehouses, data marts & data

centres.


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Topics overview:

1. Importance of managing data, text & document & their impacts on business

performance;

2. Associating data, text & documents as strategic assets of organisations &

proving necessity of data management;

3. Need for a database & a data warehouse for storing & managing data;

4. High-quality data depends on effective approaches to data management;

5. Data visualisation deployment for supporting decisions;

6. Problems & issues which occur due to poor management of data;

7. MDM consolidates data from various data sources into a master reference

file which creates accurate & consistent data across the enterprise; concept

& definition of a master reference file;

8. Data quality & integrity is still the main concern when storing & managing

data to gain users trust;


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Topics overview (cont.):

9. Text mining & analysis & DMS;

10. FMS & their limitations compared to DBMS; databases & DBMS benefits

compared to CFS;

11. Databases to data warehouses in terms of real-time support & benefits;

12. Characteristics & development of a data warehouse;

13. Concept of data mart, operational data stores & dimensional databases;

14. ECM is an important data management technology, particularly for large &

medium-sized organisations;

15. ECM includes EDM, WCM, DAM & ERM;

16. ERM are important data management technology for large & medium-sized

organisations; business value of ERM;

17. ECM & ERM growth.


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No Focus areas Assigned readings

1 Data, text & document management Chapter 3, pp 59 - 69

2 File Management systems Chapter 3, pp 69 - 72

3 Database Management systems Chapter 3, pp 72 - 76

4 Data warehouses, data marts & data centres Chapter 3, pp 76 - 82

5 Enterprise Content Management Chapter 3, pp 82 - 84


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AGENDA

Data, text & document management

File Management systems

Database Management systems

Data warehouses, data marts & data centres

Enterprise Content Management

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Data is foundation of any IS & needs to be managed for its useful life

cycle;

Managers & information workers may be constrained by data that

cannot be trusted because it is incomplete, out of context, outdated,

inaccurate & inaccessible, therefore requiring a longer time to analyse;

Data visualisation & decision support tools function to format data into

meaningful contexts for users;

Data quality, integrity, privacy & ethics;

Roles of text mining & analysis, document management & DMS towards

ensuring business efficiency & productivity.


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IMPORTANCE OF DATA MANAGEMENT

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Enterprise can be effective with accessible high quality data whenneeded to obtain:

Opportunity to earn revenues;

Ability to cut expenses;

Improve business processes and performance.

Data is retrieved from a data repository:

Database;

Data warehouse.

Uncertainty of data is a constraint on managers because data is:

Untrusted , imcomplete, out of context;

Outdated, inaccurate, inaccessible.


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DATA LIFECYCLE

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DATA MANAGEMENT

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Data principles:

Diminishing data value;

90/90 data use;

Data in context.

Data visualization:

Tools to visualize data and support to decision making.

Problems and challenges of data management:

Nonstandardized, unsynchronized;

Increasing volume of data exponentially with time;

Data dispersion, security, privacy, quality, and integrity;

Data validity, data redundant or out-of-date


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MASTER DATA MANAGEMENT

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Process to integrate data from various resouces into a unified datarepository through data entities;

Master data entities:

Better, more accurate data;

Better responsiveness;

Better revenue management;

More responsive business decisions.


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TRANSFORMING DATA INTO KNOWLEDGE

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Better revenue management and more responsive business decisions


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GAINING INSIGHT FROM TEXT & DOCUMENTS

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Text mining and analytics:

Exploration;

Preprocessing;

Categorizing and modeling.

Document management:

Enabling the company to access and use the content contained in thedocuments;

Cutting labor costs by automating business processes;

Reducing the time and effort required to locate information the businessneeds to support decision making;

Improving the security of the content, thereby reducing the risk ofintellectual property theft;

Minimizing the costs associated with printing, storage, and searching forcontent.


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FILE MANAGEMENT SYSTEMS

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File Management system;

Disadvantages of FMS compared to DBMS.


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HIERARCHY OF DATA

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CHARACTERISTICS

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Accessing records from computer files:

Sequential file organization;

Direct or random file organization.

Limitations of File environment:

Data redundancy;

Data inconsistency;

Data isolation;

Data security.


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FILE MANAGEMENT

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DATABASE MANAGEMENT SYSTEMS

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Two basic types of databases: centralised database & distributed

database;

Advantages & capabilities of DBMS


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CENTRALIZED

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DISTRIBUTED

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CHARACTERISTICS

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Advantages & capabilities:

Permanence;

Querying

Concurrency

Backup and replication

Rule enforcement

Security

Computation

Change and access logging

Automated optimization.


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CHARACTERISTICS (cont.)

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Data filtering and profiling: Inspecting the data for errors,inconsistencies, redundancies, and incomplete information.

Data quality: Correcting, standardizing, and verifying the integrity ofthe data.

Data synchronization: Integrating, matching, or linking data fromdisparate sources.

Data enrichment: Enhancing data using information from internaland external data sources.

Data maintenance: Checking and controlling data integrity over time.


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DATABASE MANAGEMENT

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DATA WAREHOUSES, DATA MARTS & DATA CENTRES

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Comparison between databases & data warehouses;

Need for real-time data warehousing & analytics;

Benefits of data warehousing;

Characteristics & the building of a data warehouse;

Data marts, operational data stores, multidimensional databases &

data centres.


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DATABASES & DATA WAREHOUSES

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Databases:

Are designed and optimized to store data;

Online transaction processing (OLTP) system;

Constantly being added, edited, or updated.

Data warehouses:

Are designed and optimized to respond to analysis questions that are

critical for a business;

Added within a schedule or a plan.


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DATA WAREHOUSE

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Real-time support from a data warehouse;

Need for data warehouse:

Business intelligence, decision making support.

Benefits of data warehouse:

Marketing and sales;

Pricing and contracts;

Forecasting;

Sales performance;

Financial.


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DATA WAREHOUSE FRAMEWORK & VIEWS

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CHARACTERISTICS OF DATA WAREHOUSE

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Organization;

Consistency;

Time variant;

Nonvolatile;

Relational;

Client/server;

Web-based;

Integration;

Real time.


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BUILDING A DATA WAREHOUSE

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DATA MARTS, OPERATIONAL DATA STORES

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Reasons data warehouses fail:

Data warehousing design;

Data warehousing implementation;

Data warehousing operation.

Data marts:

Lower cost, scaled down version of data warehouse;

Are designed for a strategic business unit or a single department.

Operational data stores:

Use concepts and benefits of the data warehouse to the operational

portions of the business at a lower cost.


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DATA CENTRES

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Facilities containing mission-critical IS and components that deliverdata and IT services to the enterprise;

Store and integrate networks, computer systems, and storagedevices;

Huge and include temperature and fire controls, physical and digitalsecurity, redundant power supplies such as uninterruptible power

sources and redundant data communications connections.


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ENTERPRISE CONTENT MANAGEMENT

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ECM & ERM;

Volume of electronic records should be continuously reviewed to

determine whether they should be retained or destroyed;

Business value of ERM;

Expected growth of ECM & ERM in the future.


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KEY FORCES TO ADOPT ECM

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Compounding growth of content generated by organizations;

Need to integrate that content within business processes;

Need to support increasing sophistication for business-user contentaccess and interaction;

Need to maintain governance and control over content to ensureregulatory compliance and preparedness for legal discovery.


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ECM & ERM

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BUSINESS VALUE & GROWTH OF ECM & ERM

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Types of lawsuits against companies include:

Patent violations, product safety negligence, theft of intellectualproperty, breach of contract, wrongful termination, harassment,

discrimination

Discovery, or the request for information;

Keeping corporate data safe will be an incredible challenge;

Planning and managing electronic documents and records areelements of every business process.


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Content summary:

- Data, text & document management:

Data is foundation of any IS & needs to be managed for its useful life cycle;

Managers & information workers may be constrained by data that cannot betrusted because it is incomplete, out of context, outdated, inaccurate &

inaccessible, therefore requiring a longer time to analyse;

Data visualisation & decision support tools function to format data intomeaningful contexts for users;

Data quality, integrity, privacy & ethics;

Roles of text mining & analysis, document management & DMS towardsensuring business efficiency & productivity.

- File Management systems:

File Management system;

Disadvantages of FMS compared to DBMS.


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Content summary (cont.):

- Database Management systems:

Two basic types of databases: centralised database & distributed database;

Advantages & capabilities of DBMS.

- Data warehouses, data marts & data centres:

Comparison between databases & data warehouses;

Need for real-time data warehousing & analytics;

Benefits of data warehousing;

Characteristics & the building of a data warehouse;

Data marts, operational data stores, multidimensional databases & data centres.

- Enterprise Content Management:

ECM & ERM;

Volume of electronic records should be continuously reviewed to determine whetherthey should be retained or destroyed;

Business value of ERM;

Expected growth of ECM & ERM in the future.


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Study questions:

1. What constraints managers face when they cannot trust data;

2. Why it is difficult to manage, search & retrieve data located throughout the enterprise;

3. How data visualisation tools & technology can improve decision making;

4. What text & document management is;

5. Describe three limitations of the file management approach;

6. Describe three data functions of a DBMS;

7. Compare databases & data warehouses in terms of data volatility & decision support;

8. Why ERM is important for an organisation;

9. Explain how having detailed real-time or near real-time data can improve productivity

& decision quality;

10.A data mart can substitute for a data warehouse or supplement it. Compare &

discuss these options;

11.Discuss the factors that make document management so valuable. What capabilities

are particularly valuable;

12.Relate document management to imaging systems.


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THANK YOU FOR YOUR ATTENTION !

NEXT TOPIC: NETWORK MANAGEMENT & MOBILITY

week 02 - topic 03 - data, text _ document management

Documents

managersbmit5103agenda

readings1 data

associating data

data warehouse13

highquality data

data management5

data marts datacentres

concept of data mart