Big Data, Data Warehouses, and Business Intelligence Systems - Database Processing: Fundamentals, Design, and Implementation - page 560

Figure 12-24
Role of the OLAP Server
and OLAP Database

Transaction
Processing
Applications

Transaction
Processing
Applications

Transaction
Processing
Applications

Transaction
Processing
Applications

Transaction
Processing
Database

DBMS

Database
Extract OLAP

Reports

OLAP
Reports

OLAP
Reports

OLAP
Reports

OLAP
Reports

OLAP
Reports

OLAP
Database

OLAP Server

Data Mining

Instead of the basic calculations filtering, sorting, and grouping used in reporting applica-
tions, data mining involves the application of sophisticated mathematical and statistical
techniques to find patterns and relationships that can be used to classify data and predict
future outcomes. As shown in Figure 12-25, data mining represents the convergence of several
phenomena. Data mining techniques have emerged from the statistical and mathematics dis-
ciplines and from the artificial intelligence and machine-learning communities. In fact, data
mining terminology is an odd combination of terms used by these different disciplines.
Data mining techniques take advantage of developments for processing enormous data-
bases that have emerged in the past dozen or so years. Of course, all these data would not have
been generated were it not for fast and inexpensive computers, and, without such computers,
the new techniques would be impossible to compute.
Most data mining techniques are sophisticated and difficult to use. However, such tech-
niques are valuable to organizations, and some business professionals, especially those in
finance and marketing, have developed expertise in their use. Almost all data mining tech-
niques require specialized software. Popular data mining products are Enterprise Miner from
SAS Corporation, SPSS Modeler from IBM, and Insightful Miner from Insightful Corporation.
However, there is a movement to make data mining available to more users. For example,
Microsoft has created the Microsoft SQL Server 2012 SP1 Data Mining Add-ins for Microsoft

Figure 12-25
Convergence of Disciplines
for Data Mining

Statistics/
Mathematics

Artificial Intelligence
Machine Learning

Data
Mining

Huge
Databases

Data
Management
Technology

Cheap Computer
Processing and
Storage

Sophisticated
Marketing, Finance,
and Other Business
Professionals