ADM 2372 Lecture Notes - Hierarchical Database Model, Database Model, Data Warehouse

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15 Apr 2012
Department
Course
Professor
Chapter 7 Databases and Data Warehouses
DATABASES
Organizational Data and Information
Relational Database Fundamentals
Database Management Systems
Integrating Data Among Multiple Databases
DATA WAREHOUSING
Overview and Fundamentals of Data Warehousing
Business Intelligence
Data Mining
Database:
A database is a collection of data.
Each database, each file, each group of data should have one unique identifier. We all
have an individual student ID, no two students have the same ID. You need to have
unique identifiers for elements in the database. If you do analysis, and you want to
retrieve information, you will get duplicate information and it would get messy,
confusing and inaccurate.
What is the difference between data and information?
Data is raw numbers, and information is analyzed data, or data with meaning.
Data are raw facts that describe the characteristics of an event.
Information is data converted into a meaningful and useful context (aspect of
granularity)
*Granularity: amount of detail of the information.
- The higher you go up in an organization, the more you look at the big picture,
rather than the tiny details, because you want to do the planning and forecasting.
Organizational Data and Information
Information granularity refers to the extent of detail within the
information (fine and detailed or coarse and abstract)
Levels
Formats
Granularities
Transactional data: Encompasses all of the data contained within a single business
process or unit of work, and its primary purpose is to support the performing of
daily operational tasks. (Transactions within units, and functional areas)
Sales receipts, airline tickets, packing slips (Transactional) (processed to give)
Product statistics, trends, future growth, sales forecasts (Analytical)
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Analytical information: Encompasses all organizational information, and its
primary purpose is to support the performing of higher-level analysis tasks.
(Supports the decision-making at higher levels)
The Value of Quality Data and Information
Accuracy: Are all the values correct? For example, is the name spelled correctly? Is
the dollar amount recorded properly? Typo’s etc.
Completeness: Are any of the values missing? For example, is the address complete
including street, city, province, and postal code?
Consistency: You want to be consistent in the type of data you are collecting. If you
are consistent in the type of data you are collecting, and the totals are not consistent
with the individual cells. Is aggregate of summary information in agreement with
detailed information? For example, do all total fields equal the true total of the
individual fields?
Uniqueness: Is each transaction, entity, and event represented only once in the
information? For example: are there any duplicate customers?
Timeliness: Is the information current with respect to the business requirements?
For example, is information updates weekly, daily, or hourly?
What are some of the reasons why we have poor information?
- There are four primary sources of low-quality information that relate to internal
and external activities:
o Employee is not trained to use the system.
o Online customer forms will have mistakes often (intentionally and
unintentionally). They write some information, and they don’t want to write
all of it.
Four Primary Sources of Low-Quality Information:
- Online customers intentionally enter inaccurate information to protect their
privacy
- Data or information from different systems have different entry standards and
formats
- Call center operators enter abbreviated or erroneous information to save time.
- Third party and external information contains inconsistencies, inaccuracies and
errors.
What Are the Implications of Poor Information for Businesses?
Think of implications related to customers and business opportunities.
Inability to accurately track customers
Difficulty identifying valuable customers
Inability to identify selling opportunities
Marketing to nonexistent customers
Difficulty tracking revenue due to inaccurate invoices
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