INFS Lecture 9: Business Intelligence and Data Mining

Data visualization

graphically visualizing the answers

Business Intelligence

A broad term encompassing analytical use of data. Incorporates various methods that give companies ability to discover and utilize information they already own, and turn it into the knowledge that directly impacts corporate performance.

Slice and Dice

Adds, replaces, or eliminates specified attributes (or particular values) from the already displayed result

OLAP/BI Tools Functionalities

Basic features: slice/dice, pivot, drill. Additional functionalities: creating and examining calculated data, determining comparative or relative differences, performing exception analysis, trend analysis, forecasting, and regression analysis.

Data mining (2)

Data mining is an intersection of database management, artificial intelligence and statistics. Data warehouse is one of the primary sources for data mining.

Data mining

Discovering novel and interesting patterns in large amounts of data. Data should be accurate, meaningful, understandable, actionable.

Market basket analysis

Finds groups of items that tend to appear together in transactions

Front-End/BI Applications

Front-end applications accessing analytical data are also known as BI applications. Most users who need to access analytical data in data warehouses and data marts can not engage in direct access. Instead they are given access to front-end/BI applications.

Executive Dashboards

Intended for use by higher level decision makers within an organization. Contains an organized easy-to-read display of a number of critically important queries describing the performance of the organization. In general, the usage of executive dashboards should require little or no effort or training. Executive dashboards can be web-based.

OLAP/BI Tools

OLAP tools are designed for analysis of data in data warehouses and data marts. OLAP tools are also known as Business Intelligence (BI) tools, and are often referred to as OLAP/BI tools. They allow users to retrieve needed date from data warehouses and data marts by using simple point-and-click mechanisms. Based on the point-and-click actions by the user of the OLAP/BI tool, the tool writes and executes the code in the language of the DBMS that hosts the data warehouse or data mart that is being queried

Pivot (rotate)

Reorganizes the values displayed in the original query result by moving values of a dimension column from one axis to another

OLAP/BI Tool features

Slice and Dice. Pivot (rotate). Drill down/Drill up.

Predictive analytics

Using past data to predict future events

Business Intelligence software

enables business users to see and use large amounts of complex data.

drill up

makes the granularity of the data in the query result coarser (makes results larger and easier to read)

drill down

makes the granularity of the data in the query result finer (things get smaller)

support

measures the significance of the rule, so we are interested in rules with relatively high support

confidence

measures the strength of the correlation, so rules with low confidence are not meaningful, even if their support is high

data mining

mining transaction (operational) databases, containing data related to current day-to-day organizational activities can be of use in certain situations. However, the most appropriate and fertile source of data for meaningful and effective data mining is the enterprise wide corporate data warehouse which contains all the information from the operational data sources that has analytical value

Online analytical processing (OLAP)

querying and presenting data from data warehouses and/or data marts for analytical purposes

Online transaction processing (OLTP)

updating (i.e. inserting, modifying and deleting) retrieving and presenting data from databases for operation purposes