1. MGS Business Intelligence The Data Warehouse & Relational Database Management System Jul 17, 2017

2. Designing & Building the Data Warehouse
Agenda
Data Warehouse
Relational Database
Designing & Building the Data Warehouse

3. The Data Warehouse The Data Warehouse
is physically separated from all other operational systems
holds aggregated data and transactional data for management separate from that data used for online transaction processing

4. Personal Legacy Data Systems Warehouse Data Flow Operational
Data Store
Data
Warehouse
Personal
Data
Warehouse
Legacy
Systems
Data
Mart
Metadata

5. The Data Warehouse The Data Warehouse
is physically separated from all other operational systems
holds aggregated data and transactional data for management separate from that data used for online transaction processing

6. Characteristics of a Data Warehouse
Subject Orientation
Data Integrated
Consistent Naming and Measurement Attributes
Time Variant
Nonvolatility

7. Business Intelligence & Data Warehouse
Executive Information System
Dashboard Balanced Scorecard
KPI
Financial Metrics
Business Intelligence & Data Warehouse
Internal Source Systems
Data Warehouse
Data Mart
Extract, Transformation and Load
External Data Sources
Business Intelligence
Business Objects
Cognos
Microstrategy
Brios
Microsoft Access
Etc.
Advanced Analytics
SAS
Minitab
SPSS

8. Data Warehouse Vendors
Business Objects
Cognos
Hyperion
IBM
Microsoft
NCR / Teradata
Oracle
SAS

9. Metadata What is Metadata? Data about Data
Without metadata, the data is meaningless
Provides consistency of the truth
Components of Metadata
Transformation Mapping
Extraction and Relationship History
Algorithms for Summarization (and calculations)
Data Ownership
Patterns of Warehouse Access
Business Friendly naming conventions
Status Information

10. Designing & Building the Data Warehouse
Agenda
Data Warehouse
Relational Database
Designing & Building the Data Warehouse

11. Relational Database
A relational database is a collection of data items organized as a set of formally-described tables from which data can be accessed or reassembled in many different ways without having to reorganize the database tables. The relational database was invented by E. F. Codd at IBM in 1970.
The standard user and application program interface to a relational database is the structured query language (SQL). SQL statements are used both for interactive queries for information from a relational database and for gathering data for reports.
A relational database is a set of tables containing data fitted into predefined categories. Each table (which is sometimes called a relation) contains one or more data categories in columns. Each row contains a unique instance of data for the categories defined by the columns. For example, a typical business order entry database would include a table that described a customer with columns for name, address, phone number, and so forth. Another table would describe an order: product, customer, date, sales price, and so forth. A user of the database could obtain a view of the database that fitted the user's needs. For example, a branch office manager might like a view or report on all customers that had bought products after a certain date. A financial services manager in the same company could, from the same tables, obtain a report on accounts that needed to be paid.

12. Relational Database
When creating a relational database, you can define the domain of possible values in a data column and further constraints that may apply to that data value. For example, a domain of possible customers could allow up to ten possible customer names but be constrained in one table to allowing only three of these customer names to be specifiable.
The definition of a relational database results in a table of metadata or formal descriptions of
the tables, columns, domains, and constraints. Meta is a prefix that in most information technology usages means "an underlying definition or description." Thus, metadata is a definition or description of data and metalanguage is a definition or description of language.
A database is a collection of data that is organized so that its contents can easily be accessed, managed, and updated. The most prevalent type of database is the relational database, a tabular database in which data is defined so that it can be reorganized and accessed in a number of different ways. A distributed database is one that can be dispersed or replicated among different points in a network. An object-oriented programming database is one that is congruent with the data defined in object classes and subclasses.
SQL (Structured Query Language) is a standard interactive and programming language for getting information from and updating a database. Although SQL is both an ANSI and an ISO standard, many database products support SQL with proprietary extensions to the standard language. Queries take the form of a command language that lets you select, insert, update, find out the location of data, and so forth.

13. Business Intelligence Environment
Internal Source Systems
Data Warehouse
Data Mart
Extract, Transformation and Load
SQL
RDBMS
External Data Sources
Business Intelligence
Business Objects
Cognos
Microsoft Access
Etc.

14. Relational Database IBM DB2, DB2/400 Microsoft SQL/Server Teradata
Oracle
Sybase
Informix / Red Brick
Microsoft Access
MySQL

15. SQL Request BI Software Application Result Set Relational Database
RDBMS
BI Software
Application
Result
Set

16. SQL SQL – Structured Query Language DDL – Data Definition Language
Create
Drop
Alter
DML – Data Manipulation Language
Insert
Update
Delete
Select

17. SQL Select Statement SELECT column1, column2, . . .
FROM table1, table2, . . .
WHERE criteria1
AND/OR criteria2
ORDER BY column1, column1, . . .

18. SQL Select Statement SELECT column1, column2, . . .
FROM table1, table2, . . .
WHERE criteria1
AND/OR criteria2
GROUP BY column1, column1, . . .
HAVING criteria1
AND/OR criteria2
Aggregation
ORDER BY column1, column1, . . .

19. SQL – Example 1 SQL CREATE TABLE ADDR_BOOK ( NAME char(30),
COMPANY char(20),
E_MAIL char (25)
Output
Name Company
John Smith Microsoft
Jeff Jones Delta

20. SQL – Example 2 2a) SQL SELECT NAME, COMPANY, E_MAIL FROM ADDR_BOOK
WHERE COMPANY = ‘Microsoft'
Output
Name Company
John Smith Microsoft
2b)
Table - Product
ID Name Category
I Internet A
B Browsers A
A Application Null
G Graphics Null
SQL
SELECT
ID,
NAME
from
PRODUCT
WHERE CATEGORY = NULL

21. SQL – Example 3 SQL SELECT ADDR_BOOK.NAME, COMPANY.EMAIL FROM
WHERE ADDR_BOOK.EMPLOYEE_ID = COMPANY.EMPLOYEE_ID
Output
Name
John Smith
Jeff Jones

22. SQL – Example 4 SQL CREATE TABLE CUSTOMER ( CUST_NO INTEGER,
FIRST_NAME CHAR(30),
LAST_NAME CHAR(30),
ADDRESS CHAR(50),
CITY CHAR(30),
STATE CHAR (2),
ZIP_CODE CHAR(9),
COUNTRY CHAR(20) )
CREATE TABLE ORDER (
ORDER_NO INTEGER,
DATE_ENTERED DATE,
CUST_NO INTEGER )
SQL
SELECT
ORDER.ORDER_NO, CUSTOMER.NAME, CUSTOMER.ADDRESS, CUSTOMER.CITY, CUSTOMER.ZIP_CIDE, CUSTOMER.COUNTRY
FROM
ORDER, CUSTOMER
WHERE ORDER.CUST_NO = CUSTOMER.CUST_NO
AND
ORDER.DATE_ENTERED = ' '

23. SQL – Example 5 SQL CREATE TABLE ADDR_BOOK ( NAME char(30),
COMPANY char(20),
E_MAIL char (25)
Output
Name Company
John Smith Microsoft
Jeff Jones Delta

24. SQL – Example 6 – Referential Integrity
CREATE TABLE CUSTOMER (
CUST_NO INTEGER PRIMARY KEY,
FIRST_NAME CHAR(30),
LAST_NAME CHAR(30),
ADDRESS CHAR(50),
CITY CHAR(30),
ZIP_CODE CHAR(9),
COUNTRY CHAR(20) )
CREATE TABLE ORDER (
ORDER_NO INTEGER PRIMARY KEY,
DATE_ENTERED DATE,
CUST_NO INTEGER REFERENCES CUSTOMER (CUST_NO) )
SQL
CREATE TABLE ORDER_ITEMS (
ORDER_NO INTEGER,
ITEM_NO INTEGER,
PRODUCT CHAR(30),
QUANTITY INTEGER,
UNIT_PRICE MONEY )
ALTER TABLE ORDER_ITEMS
ADD PRIMARY KEY PK_ORDER_ITEMS (ORDER_NO, ITEM_NO)
ADD FOREIGN KEY FK_ORDER_ITEMS_1 (ORDER_NO)
REFERENCES ORDER (ORDER_NO)

25. SQL – Example 7 – Index
When you have a primary key, you already have an implicitly (or explicitly) defined unique index on the primary key columns. It's generally a good idea to define non-unique indexes on the foreign keys.
SQL
CREATE UNIQUE INDEX PK_CUSTOMER ON CUSTOMER (CUST_NO)
CREATE UNIQUE INDEX PK_ORDER ON ORDER (ORDER_NO)
CREATE INDEX FK_ORDER_1 ON ORDER (CUST_NO)
CREATE UNIQUE INDEX PK_ORDER_ITEMS ON ORDER_ITEMS (ORDER_NO, ITEM_NO)
CREATE INDEX FK_ORDER_ITEMS_1 ON ORDER_ITEMS (ORDER_NO)

26. Designing & Building the Data Warehouse
Agenda
Data Warehouse
Relational Database
Designing & Building the Data Warehouse

27. Why Business Intelligence
Improve consistency and accuracy of reporting
Reduce stress on operational systems for reporting and analysis
Faster access to information
BI tools provide increased analytical capabilities
Empowering the Business User
Companies are realizing that data is a company’s most underutilized asset

28. ERM vs. DM ERM - Entity Relationship Model Remove redundancy
Efficiency of transactions
DM - Dimensional Model
Intuitive View of the Data
Efficiency of access and analysis

29. Dimensional Model

30. Retail Sales Dimensional Model (Partial)

31. Fact Table Contains Foreign Keys that relate to Dimension Tables
Have a many-to-one relationship to Dimension Tables
Contains Metrics to be aggregated
Typically does not contain any non-foreign key or non-metric data elements
Level of Granularity defines depth and flexibility of analysis

32. Dimension Table
Contains a Primary Key that relates to the Fact Table(s)
Has a one-to-many relationship to the Fact Table(s)
Contains Descriptive data used to limit and aggregated metrics from the Fact Table(s)
Can sometimes contain pre-aggregated data

33. Warehouse Architecture Specification
Common Sources
Common Dimensions
Common Business Rules
Common Semantics
Common Metrics

34. Time Dimension Date (Primary Key) – a day, 365 per year
Week – defined by an end of week day
Month – January, February, March,
Quarter – Q1: 01/01 – 03/31
Q2: 04/01 – 06/30
Q3: 07/01 – 09/30
Q4: 10/01 – 12/31
Year – 2000, 2001, 2002, 2003
Fiscal Month – 4/4/5
Fiscal Quarter
Fiscal Year

35. Time Dimension Date (Primary Key) – a day, 365 per year
Weekday/Weekend
Day of Week – Monday, Tuesday, Wednesday, . . .
Season – Winter, Spring, Summer, Fall
Holiday – Labor Day, 4th of July, Memorial Day, . . .
. . .