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Foundations of Business Intelligence: Databases and Information Management
Foundations of Business Intelligence: Databases and Information Management
The major capabilities of database management systems (DBMS), and the reason why is a relational DBMS so powerful
Capabilities of Database Management Systems
Querying and Reporting
Designing Databases
Normalization and Entity-Relationship Diagrams
Database Management Systems
software that permits an organization to centralize data, manage them efficiently, and provide access to the stored data by application programs
Reducing the Traditional File Problems
Relational DBMS
represent data as two-dimensional tables
Non-relational Databases and Databases in the Cloud
use a more flexible data model and are designed for managing large data sets across many distributed machines and for easily scaling up or down
The reason why information policy, data administration, and data quality assurance essential for managing the firm's data resources
Establishing an Information Policy
specifies the organization’s rules for sharing, disseminating, acquiring, standardizing, classifying, and inventorying information
Data Governance
Database Administration
Data Administration
Ensuring Data Quality
Data Cleansing
The principal tools and technologies for accessing information from databases to improve business performance and decision making
The Challenge of Big Data
data sets with volumes so huge that they are beyond the ability of typical DBMS to capture, store, and analyze
Business Intelligence Infrastructure
Hadoop
For handling unstructured and semi-structured data in vast quantities, as well as structured data, organizations
In-Memory Computing
relies primarily on a computer’s main memory (RAM) for data storage
Data Warehouses and Data Marts
database that stores current and historical data of potential interest to decision makers throughout the company
data mart is a subset of a data warehouse in which a summarized or highly focused portion of the organization’s data is placed in a separate database for a specific population of users
Analytic Platforms
Commercial database vendors have developed specialized high-speed
Analytical Tools: Relationships, Patterns, Trends
Online Analytical Processing (OLAP)
supports multidimensional data analysis
Data Mining
More Discovery Driven
Sequences
Classification
Clustering
Associations
Forecasting
Text Mining and Web Mining
Text mining tools are now available to help businesses analyze these data
The discovery and analysis of useful patterns and information from the World Wide Web
The problems of managing data resources in a traditional file environment
File Organization Terms and Concepts
Field
Record
Byte
File
Bit
Database
Problems with the Traditional File Environment
Lack of Flexibility
A traditional file system can deliver routine scheduled reports after extensive programming efforts, but it cannot deliver ad hoc reports or respond to unanticipatedinformation requirements in a timely fashion
Poor Security
Because there is little control or management of data, access to and dissemination of information may be out of control
Program-Data Dependence
refers to the coupling of data stored in files and the specific programs required to update and maintain those files such that changesin programs require changes to the data
Lack of Data Sharing and Availability
Because pieces of information in different files and different parts of the organization cannot be related to one another
Data Redundancy and Inconsistency
Data redundancy is the presence of duplicate data in multiple data files so that the same data are stored in more than one place or location