chapter4:

4.1 Managing Data

Difficulties in Managing Data:

1.Amount of data increases exponentially

2.Data are scattered and collected  by many individuals using various methods and devices

3.Data come from many sources (e.g. Clickstream data )

4.Data security, quality and integrity are critical.

4.2 The Database Approach

Database management system (DBMS) provides all users with access to all the data.

DBMSs minimize the following problems:

Data redundancy: The same data are stored in many places

Data isolation: Applications cannot access data associated with other applications

Data inconsistency: Various copies of the data do not agree.

DBMSs maximize the following issues:

Data Security: keeping the organization’s data safe from theft, modification, and/or destruction.

Data integrity: Data must meet constraints (e.g., student grade point averages cannot be negative).

Data independence: Applications and data are independent of one another. Applications and data are not linked to each other, meaning that applications are able to access the same data.

Data Hierarchy:

Bit: a binary digit, or a “0” or a “1” - The smallest unit of data a computer can handle.

Byte: eight bits and represents a single character (e.g., a letter, number or symbol)

Field: is a group of related characters (e.g., student’s name, age,  mobile number)

Record: a group of logically related fields (e.g., student in a university database)

4.3 Database Management Systems

Database management system (DBMS): a software that provides users with tools to add, delete, access, and analyze data stored in one location.

Relational database model: based on the concept of two-dimensional tables

4.4 Data Warehousing

Data warehouse: a repository of current and historical data to support decision makers in the organization.

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

4.5 Data Visualization Technologies

Data governance:  an approach to managing data across an entire organization.

Master data management: a process/method that provides an organizations with the ability to store, maintain, exchange and synchronize a consistent, accurate and timely ‘single version of the truth’ for the organization's core master data.

Master data: a set of core data [customer, employee, vendor, geographic location] that span all enterprise information systems.

Transaction data: data that are generated and captured by operational systems.

4.6 Knowledge Management

Knowledge: information that is contextual, relevant, and actionable

Explicit knowledge: codified (documented) in a form that can be distributed to others (CCE student’s handbook)

Tacit knowledge: a set of  insights, expertise and skills Knowledge that people carry in their heads, but difficult to write down in a document.