UNIT 3 Data and Knowledge Management


Data and Knowledge Management

Defining Big Data

Big Data Generally Consist of: – Traditional enterprise data –Machine-generated/sensor data – Social Data – Images captured by billions of devices

located around the world

Characteristics of Big Data

• Volume

• Velocity

• Variety

The Database Approach

Database management system (DBMS) minimize the following problems:

–Data redundancy

–Data isolation

–Data inconsistency

Data Hierarchy Bit




File (or table)


Designing the Database

Data model



Primary key

Secondary keys

Entity-Relationship Modeling

• Database designers plan the database design in a process called entity- relationship (ER) modeling.

• ER diagrams consists of entities, attributes and relationships. – Entity classes – Instance – Identifiers

Database Management Systems

Database management system (DBMS)

Relational database model

Structured Query Language (SQL)

Query by Example (QBE)

Normalization • Normalization is a method for analyzing

and reducing a relational database to its most streamlined form for: –Minimum redundancy –Maximum data integrity – Best processing performance

• Normalized data is when attributes in the table depend only on the primary key.

Data Warehousing

Data warehouses and Data Marts Organized by business dimension or

subject. Multidimensional. Historical. Use online analytical processing.

Benefits of Data Warehousing

•End users can access data quickly and easily via Web browsers because they are located in one place. •End users can conduct extensive analysis with data in ways that may not have been possible before. •End users have a consolidated view of organizational data.

Data Marts

• A data mart is a small data warehouse, designed for the end-user needs in a strategic business unit (SBU) or a department.

Knowledge Management

• Knowledge management (KM)

• Knowledge

• Intellectual capital (or intellectual assets)

Knowledge Management System Cycle

•Create knowledge •Capture knowledge •Refine knowledge •Store knowledge •Manage knowledge •Disseminate knowledge

Leave a Reply

Your email address will not be published. Required fields are marked *