Chapter 6 - Business Intelligence

Consequences of using low quality data

Inability to track customers accurately. Difficulty identifying the organization's most valuable customers. Inability to identify selling opportunities. Lost revenue opportunities from marketing to nonexistent customers. The cost of sending undeliverable mail. Difficulty tracking revenue because of inaccurate invoices. Inability to build strong relationships with customers.

Dynamic information

Includes data that change based on user actions. For example, static websites supply only information that will not change until the content editor changes the information.

Levels, Formats, and Granularities of Organizational Information

Information Levels: Individual, Department, Enterprise Information Formats: Document, Presentation, Spreadsheet, Database Information Granularities: Detail (fine), Summary, Aggregate (coarse).

Data models

Logical data structures that detail the relationships among data elements by using graphics or pictures.

Information Integrity issues

Occur when a system produces incorrect, inconsistent or duplicate data

Information types

Transactional: encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support daily operational tasks Analytical:encompasses all organizational information, and its primary purpose is to support the performance of managerial analysis tasks. Analytical information is useful when making important decisions such as whether the organization should build a new manufacturing plant or hire additional sales personnel.

data artist

a business analytics specialist who uses visual tools to help people understand complex data.

Big data

a collection of large, complex data sets, including structured and unstructured data, which cannot be analyzed using traditional database methods and tools.

primary key

a field that uniquely identifies a given record in a table

Data warehouse

a logical collection of information, gathered from many operational databases, that supports business analysis activities and decision-making tasks. primary purpose of a data warehouse is to combine information, more specifically, strategic information, throughout an organization into a single repository in such a way that the people who need that information can make decisions and undertake business analysis

Information integrity

a measure of the quality of information

foreign key

a primary key of one table that appears as an attribute in another table and acts to provide a logical relationship between the two tables.

Extraction, transformation, and loading (ETL)

a process that extracts information from internal and external databases, transforms it using a common set of enterprise definitions, and loads it into a data warehouse.

Information cleansing or scrubbing

a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information.

Relational database management system

allows users to create, read, update and delete data in a relational datatbase

Dynamic catalogue

an area of a website that stores information about products in a database.

data-driven website

an interactive website kept constantly updated and relevant to the needs of its customers using a database

Integrity constraints

are rules that help ensure the quality of information. The database design needs to consider integrity constraints

Structured query language (SQL)

asks users to write lines of code to answer questions against a database.

record

collection of related data elements.

Data dictionary

compiles all of the metadata about the data elements in the data model.

data mart

contains a subset of data warehouse information

Machine-generated data

created by a machine without human intervention. Machine-generated structured data includes sensor data, point-of-sale data, and web log (blog) data.

database management system (DBMS)

creates, reads, updates, and deletes data in a database while controlling access and security. Managers send requests to the DBMS, and the DBMS performs the actual manipulation of the data in the database.

attributes

data elements associated with an entity

Human-generated data

data that humans, in interaction with computers, generate. Human-generated structured data includes input data, click-stream data, or gaming data.

physical view of information

deals with the physical storage of information on a storage device.

business rule

defines how a company performs certain aspects of its business and typically results in either a yes/no or true/false answer. Stating that merchandise returns are allowed within 10 days of purchase is an example of a business rule.

Data visualization

describes technologies that allow users to see or visualize data to transform information into a business perspective.

data quality audits

determine the accuracy and completeness of its data.

Business-critical integrity constraints

enforce business rules vital to an organization's success and often require more insight and knowledge than relational integrity constraints.

Dirty Data

erroneous or flawed data

data scientist

extracts knowledge from data by performing statistical analysis, data mining, and advanced analytics on big data to identify trends, market changes, and other relevant information.

Advanced analytics

focuses on forecasting future trends and producing insights using sophisticated quantitative methods, including statistics, descriptive and predictive data mining, simulation, and optimization

Logical view of information

focuses on how individual users logically access information to meet their own particular business needs.

Structured data

has a defined length, type, and format and includes numbers, dates, or strings such as Customer Address. Structured data is typically stored in a traditional system such as a relational database or spreadsheet and accounts for about 20 percent of the data that surrounds us.

query-by-example (QBE) tool

helps users grapahically design the answer to a question against a database

Static information

includes fixed data incapable of change in the event of a user action.

database

maintains information about various types of objects (inventory), events (transactions), people (employees), and places (warehouses).

Data visualization tools

move beyond Excel graphs and charts into sophisticated analysis techniques such as controls, instruments, maps, time-series graphs, and more.

Information inconsistency

occurs when the same data element has different values

Analysis paralysis

occurs when the user goes into an emotional state of over-analysis (or over-thinking) a situation so that a decision or action is never taken, in effect paralyzing the outcome.

entity

or table, stores information about a person, place, thing, transactuon or event.

Infographics

present the results of data analysis, displaying the patterns, relationships, and trends in a graphical format

Distributed computing

processes and manages algorithms across many machines in a computing environment

Real-time systems

provide real-time information in response to requests.

Metadata

provides details about data. For example, metadata for an image could include its size, resolution, and date created. Metadata about a text document could contain document length, data created, author's name, and summary.

Information Granularity

refers to the extent of detail within the information (fine and detailed or coarse and abstract)

Relational integrity constraints

rules that enforce basic and fundamental information-based constraints

Unstructured data

s not defined, does not follow a specified format, and is typically free-form text such as emails, Twitter tweets, and text messages. Unstructured data accounts for about 80 percent of the data that surrounds us.

data element (or Data field)

s the smallest or basic unit of information. Data elements can include a customer's name, address, email, discount rate, preferred shipping method, product name, quantity ordered

relational database model

stores information in the form of logically related, two dimensional tables

information cube

the common term for the representation of multidimensional information

Information redundancy

the duplication of data, or the storage of the same data in multiple places.

Data governance

the overall management of the availability, usability, integrity, and security of company data.

content creator

the person responsible for creating the original website content

content editor

the person responsible for updating and maintaining website content

Master Data Management (MDM)

the practice of gathering data and ensuring that it is uniform, accurate, consistent, and complete, including such entities as customers, suppliers, products, sales, employees, and other critical entities that are commonly integrated across organizational systems

Data mining

the process of analyzing data to extract information not offered by the raw data alone.

Business intelligence dashboards

track corporate metrics such as critical success factors and key performance indicators and include advanced capabilities such as interactive controls, allowing users to manipulate data for analysis.

Data-mining tools

use a variety of techniques to find patterns and relationships in large volumes of information that predict future behavior and guide decision making.

advantages of using data-driven websites

- Much easier to use than a customer query tool - web interface requires few or no changes to database model - costs less to add a web interface in front of a DBMS than to redesign and rebuild the system to support changes. - Easy to manage content - Easy to store large amounts of data: - Easy to eliminate human errors

Four Primary Reasons for low quality Information

1. Online customers intentionally enter inaccurate information 2. different systems have different entry standards and formats 3. data entry personnel enter abbreviated information 4. third-party and external info has inconsistencies, inaccuracies and errors

Example of low quality information

1. completeness 2. consistency 3. accuracy

different industries use business intelligence include

Airlines: Analyze popular vacation locations with current flight listings. Banking: Understand customer credit card usage and nonpayment rates. Health care: Compare the demographics of patients with critical illnesses. Insurance: Predict claim amounts and medical coverage costs. Law enforcement: Track crime patterns, locations, and criminal behavior. Marketing: Analyze customer demographics. Retail: Predict sales, inventory levels, and distribution. Technology: Predict hardware failures.

3 Core Concepts of data warehousing

Data Mart Information Cleansing Data Mining

Methods for Analyzing Big Data

Data Mining Big Data Analytics Data Visualization

Real-time information

Immediate, up-to-date information. One of the biggest pitfalls is continual change