MIS Chapter 6

The Problem

- Data rich, information poor -Can't get all the data they need quick enough -Businesses face data explosions such as digital images, email inboxes, and broadband connections doubles by 2010 -The amount of data generated is doubling every year -Some believe it will soon double monthly

Data Warehouse

-A logical collection of information gathered from many different operational databases that support business analysis activities and decision-making tasks -Aggregate information throughout an organization into a single repository for decision-making purposes -Extend the transformation of data into information -Provided the ability to support decision making without disrupting the day to day operations

Data Aggregation

-Collection of data from various sources for the purpose of data processing. -One example of a data aggregation is to gather information about particular groups based on specific variables such as age, profession, or income

The Solution

-Improving the quality of business decisions has a direct impact on costs and revenue -BI enables users to receive data for analysis that is reliable, consistent, understandable, and easily manipulated

Velocity

-The analysis of streaming data as it travels around the Internet

Volume

-The scale of data -Includes enormous volumes of data generated daily from machines and networks

Veracity

-The uncertainty or untrustworthiness of data including biases, noise, and abnormalities -Data must be meaningful to the problem being analyzed -Data must be kept clean and implement processes to keep from dirty data accumulating in systems

Source Data

-identifies the primary location where data is collected

Example of all this:

1 table named: Tracks is the Entity. The Attributes are the top categories such as track number, track title, and track length. The records are the attributes numbered 1-3 under the attribute track number. The primary key is track number and the foreign key is an attribute that is repeated in many tables so that you can find more relationships.

Low Quality

1. Customers enter inaccurate information to protect their privacy 2. Different entry formats 3. Operators enter abbreviated info by accident or to save time 4. Third party and external info contain errors

Identity Management

A broad administrative area that deals with identifying individuals in a system (such as a country, a network, or an enterprise) and controlling their access to resources within that system by associating user rights and restrictions with the established identity

Big Data

A collection of large, complex datasets, including structured and unstructured data, which cannot be analyzed using traditional database methods and tools and includes the following four common characteristics Variety Veracity Volume Velocity

Record

A collection of related data elements

Increased Scalability and Performance

A database must scale to meet increased demand, while maintaining acceptable performance levels

Primary Key

A field(or group) that uniquely identifies a given entity in a table, they provide a way of distinguishing each record in a table

Entity

A person, place, thing, transaction, or event about which information is stored (each entity has a table with rows and columns)

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, Loading*

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

Information cleansing or scrubbing

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

Data Map

A technique for establishing a match, or balance, between the source data and the target data warehouse

High Quality

Accurate, Complete, Consistent, Timely, Unique Can significantly improve the chances of making a good decision which impacts an organizations bottom line

Database Management System

Allows users to create, read, update, and delete data in a relational database while controlling access and security

Relational Database Management System

Allows users to read, create, update, and delete data in a relational databse

Information Timeliness

An aspect of information that depends on the situation

Data Driven Websites

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

Data Set

An organized collection of data

Structured Query Language Tool

Asks users to write lines of code to answer questions against a database

Information Quality

Business decisions are only as good as the quality of information used to make those decisions

Comparative Analysis

Can compare two or more data sets to identify patterns and trends

Data Dictionary*

Complies all of the metadata about the data elements in the data model

Data Mart

Contains a subset of data warehouse information sent from the ETL

Reduced Information Redundancy

Databases reduce information redundancy Inconsistency is one if the primary problems with redundant information

Physical View

Deals with the physical stage 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 (10-day return policy)

Department

Departmental goals, revenues, expenses, processes, and strategies

Information Granularities

Detail(fine), summary, aggregate(coarse)

Metadata*

Details about data Example: metadata about an image could be its size, resolution, and date created

Access Control

Determines types of user access, such as read-only access

Access Level

Determines who has access to the different types of information

Variety

Different forms of structured and unstructured data (spreadsheets, databases, email, videos, and PDF's)

Information Formats

Document, Presentation, Spreadsheet, and Database

Data Driven Website Advantages

Easy to manage content, easy to store large amounts of data, and easy to eliminate human errors

Transactional Information

Encompasses all of the information contained within a single business with a purpose to support the performing of daily operational tasks(airline ticket, sales receipt, packing slip)

Analytical Information

Encompasses all organizational information, and its primary purpose is to support the performing of managerial analysis tasks(product statistics, sales projections, future growth, and trends)

Business-Critical Integrity Constraint

Enforce business rules vital to an organization's success and often require more knowledge and insight than relational integrity constraints (15 day return policy because the produce would be bad by then)

Enterprise

Enterprise revenues, expenses, processes, and strategies

Inconsistent Data Definitions

Every department had its own method for recording data so when trying to share information, data did not match and users did not get the data they really needed

Dirty Data

Flawed Data, complete removal is impossible, business problem not MIS

Logical View

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

Increased Flexibility

Handle changes quickly and easily have only one physical view, provide users with different views, and have multiple logical views

Query By Example Tool

Helps users graphically design the answer to a question against a database

Real time information

Immediate, up to date information however can slow down decisions because real-time information is always changing

Low Quality Leads To:

Inability to track customers, difficulty to identify valuable customers, can't identify selling opportunities, etc.

Data Validation

Includes the tests and evaluations used to determine compliance with data governance policies to ensure the correctness of data, helps to ensure that every data value is correct and accurate

Database advantages from a business perspective include:

Increased flexibility Increased information integrity Increased scalability performance, Reduced information redundancy Increased information security

Individual

Individual knowledge, goals, and strategies

Information Levels

Individual, Department, and Enterprise

Increased Information Security

Information is an organizational assist and must be protected Databases offer several security features

4 Traits of the Value of Information

Information type, timeliness, quality, and governance

Information

Is everywhere in an organization and is stored in databases

Data Steward

Is responsible for ensuring the policies and procedures are implemented across the organization and acts as a liaison between the MIS departments and business

Data Model*

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

Database

Maintains information about various types of objects(inventory), events(transactions), people(employees), and places(warehouse)

Lack of Data Standards

Managers need to perform cross-functional analysis using data from all departments, which differed in granularities, formats, and levels

Performance

Measures how quickly people can access their demands

Information Integrity

Measures the quality of information

Ineffective Direct Data Access

Most data stored in operational databases did not allow users direct access; users had to wait to have their queries or questions answered by MIS professionals who could code SOL

Data Gap Analysis

Occurs when a company examines its data to determine if it can meet business expectations while identifying where missing data might exist

Information Integrity Issues

Occurs when a system produces incorrect, inconsistent, or duplicate data

Information Inconsistency

Occurs when the same data element has different values

Business Intelligence

Organizational data is difficult to access and contains structured and unstructured data

Password

Provides authentication of the user

Real time system

Provides real-time information in response to requests

Scalability

Refers to how well a system can adapt to increased demands

Data Governance

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

Aggregate(coarse)

Reports across departments, organizations, and companies

Summary

Reports for all sale personnel, all products, and all parts

Detail(fine)

Reports for each salesperson, product, and part

Relational Integrity Constraint

Rules that enforce basic and fundamental information-based constraints (not allow someone to create an order for a nonexisting customer or order zero pounds of raw material from a supplier)

Integrity Constraint

Rules that help ensure the quality of information, the database design need to consider these

Relational Database Model

Stores information in the form of logically related two-dimensional tables

Billing

The billing system has accounts payable customer contact information

Customer Service

The customer service system has the product user customer contact information

Attribute (field, columns)

The data elements associated with an entity (head columns in each table contain the attributes)

Poor Data Quality

The data, if available, were often incorrect or incomplete. Therefore, users could not rely on the data to make decisions

Information Redundancy

The duplication of data or storing the same information in multiple places

Data Stewardship

The management and oversight of an organization's data assets to help provide business users with high-quality data that is easily accessible in a consistent manner

Marketing and Sales

The marketing and sales system has decision maker customer contact information

Master data management

The practice of gathering data and ensuring that it is uniform, accurate, consistent, and complete, including entities

Date Element*

The smallest or basic unit of info can include a customer's name, address, email, discount rate, quantity ordered, and preferred shipping method

Data Latency

The time it takes for data to be stored or retrieved

Information Type

Transactional and Analytical

Inadequate Data Usefulness

Users could not get the data they needed; what was collected was not always useful for intended purposes

Repository

Where data is stored and managed

Data Broker

a business that collects personal information about consumers and sells that information to other organizations.

Data Lake

a storage repository that holds a vast amount of raw data in its original format until the business needs it

Data Driven Decision Management

an approach to business governance that values decisions that can be backed up with verifiable data

Data Point

an individual item on a graph or a chart

Analyze big data

data mining, big data analytics, and data visualization

DBMS uses three primary models for organizing information

hierarchical, network, and the relational database