Chapter 9: Business Intelligence Systems

Hyper-organization theory

--Framework for understanding this new direction in KM. --Focus moves from knowledge and content per se to fostering authentic relationships among creators and users of knowledge

Challenges of Content Management

-Databases are huge -Content dynamic -Documents do not exist in isolation -Contents are perishable -In many languages

Possible Problems with Source Data

-Dirty Data -Missing Values -Inconsistent data -Data not integrated -Wrong granularity --too fine -- not fine enough -too much data --too many attributes --too many data points

Functions of a Data Warehouse

-Extract data from operational, internal & external databases. -Cleanse data. -Organize, relate data warehouse. -Catalog data using metadata

Off-the-Shelf

-Horizontal market products (SharePoint) -Vertical market applications

Drawbacks of Expert Systems

1. Difficult & expensive to develop 2. Difficult to maintain 3. Don't live up to expectations

Basic Reporting Operations

1. Sorting 2. Filtering 3. Grouping 4. Calculating 5. Formatting

Improve process quality, increase team strength

2 fundamental ways KM benefits organizations

reporting application

A BI application that inputs data from one or more sources and applies reporting operations to that data to produce business intelligence

data warehouse

A facility for managing an organization's BI data.

unsupervised data mining

A form of data mining whereby the analysts do not create a model or hypothesis before running the analysis. Instead, they apply the data mining technique to the data and observe the results. With this method, analysts create hypotheses after the analysis to explain the patterns found.

BigData

A term used to describe data collections that are characterized by huge volume, rapid velocity, and great variety.

cluster analysis

An unsupervised data mining technique whereby statistical techniques are used to identify groups of entities that have similar characteristics. A common use for cluster analysis is to find groups of similar customers in data about customer orders and customer demographics

Dynamic Reports

BI documents that are updated at the time they are requested

semantic security

Concerns the unintended release of protected data through the release of a combination of reports or documents that are not protected independently.

In-house custom

Customer support department develops in-house database applications to track customer problems

Pig

Hadoop query language

business intelligence

Information collected from multiple sources such as suppliers, customers, competitors, partners, and industries that analyzes patterns, trends, and relationships for strategic decision making

Dynamic

Key characteristic of OLAP

predictive policing

Police departments analyze data on past crimes, including location, date, time , day of week, type of crime, and related data, to predict where crimes are likely to occur.

Recently, Frequently, Money

RFM

Content Management Systems (CMS)

Support management and delivery of documents, such as reports, web pages, and other expressions of employee knowledge.

Hyper-social knowledge management

The application of social media and related applications for the management and delivery of organizational knowledge resources.

Data mining

The application of statistical techniques to find patterns and relationships among data for classification and prediction.

the singularity

The point at which computer systems become sophisticated enough that they can create and adapt their own software and hence adapt their behavior without human assistance.

Publish Results

The process of delivering business intelligence to the knowledge workers who need it.

cross-selling

The sale of related products; salespeople try to get customers who buy product X to also buy product Y

Market-basket analysis

Unsupervised data mining technique for determining sales patterns.

data triangulation

Use of multiple sources of references to draw conclusions about what the truth is

Dimension

a characteristic of a measure

supervised data mining

a form of data mining in which data miners develop a model prior to the analysis and apply statistical techniques to data to estimate values of the parameters of the model

decision tree

a hierarchical arrangement of criteria that predict a classification or a value

OLAP Cube

a presentation of an OLAP measure with associated dimensions; same thing as an OLAP report

Online Analytical Processing (OLAP)

a second type of reporting application (more generic than RFM)\ Provides the ability to sum, count, average, and perfrom other simple arithmetic operations on groups of data

MapReduce

a technique for harnessing the power of thousands of computers working in parallel

BI Server

a web server application that is purpose-built for the publishing of business intelligence

Rich Directory

an employee directory that includes not only the standard name, email, phone, and address, but also organizational structure and expertise

Hadoop

an open-source program supported by the Apache Foundation that implements MapReduce on potentially thousands of computers

confidence

conditional probability estimate

data mart

data collection, smaller than the data warehouse, that addresses the needs of a particular department or functional area of the business

Push Publishing

delivers business intelligence to users without any request from the users; the BI results are delivered according to a schedule or as a result of an event or particular data condition

Business Information (BI) Systems

information systems that process operational, social, and other data to identify patterns, relationships, and trends for use by business professional & other knowledge workers.

regression analysis

measures the effect of a set of variables on another variable

Expert Systems Shells

programs that process a set of rules

granularity

refers to the level of detail represented by the data

Pull publishing

requires the user to request BI results

Expert Systems

rule-based systems that encode human knowledge in the form of if/then rules

If/Then Rules

statements that specify if a particular condition exists, then to take some action

Measure

the data item of interest

support

the probability that two items will be purchased together

BI analysis

the process of creating business intelligence

Knowledge Management (KM)

the process of creating value from intellectual capital and sharing that knowledge with employees, managers, suppliers, customers & others who need that capital

data acquisition

the process of obtaining, cleaning, organizing, relating, & cataloging source data

lift

the ratio of confidence to the base probability of buying an item

BI Application

the software component of a BI system

Drill Down

to further divide the data into more detail

Neutral Network

type of supervised data mining, predicts values and makes classifications such as "good prospect" and "poor prospect"

Subscriptions

user requests for particular BI results on a particular schedule of in response to particular events

RFM Analysis

way of analyzing and ranking customers according to their purchasing patterns.