1. Chapter 3 and Module C DATABASES AND DATA WAREHOUSES Building Business Intelligence

2. MORE CHERRIES PLEASE Ben & Jerry’s Ben & Jerry’s 190,000 pints of ice cream and frozen yogurt 190,000 pints of ice cream and frozen yogurt 50,000 grocery stores 50,000 grocery stores In the U.S. and 12 other countries In the U.S. and 12 other countries Meticulously tracks every piece of information on every pint Meticulously tracks every piece of information on every pint

3. MORE CHERRIES PLEASE Noticed a problem with Cherry Garcia Ice Cream Noticed a problem with Cherry Garcia Ice Cream Complaints of not enough cherries Complaints of not enough cherries Ben & Jerry’s could find no production problems Ben & Jerry’s could find no production problems Eventually found that the wrong photo was on the ice cream container Eventually found that the wrong photo was on the ice cream container Ben & Jerry’s analyzed all the information to create business intelligence Ben & Jerry’s analyzed all the information to create business intelligence

4. INTRODUCTION Organizations need business intelligence Organizations need business intelligence Business intelligence (BI) – knowledge about your customers, competitors, business partners, competitive environment, and internal operations to make effective, important, and strategic business decisions Business intelligence (BI) – knowledge about your customers, competitors, business partners, competitive environment, and internal operations to make effective, important, and strategic business decisions

5. INTRODUCTION IT tools help process information to create business intelligence according to… IT tools help process information to create business intelligence according to… OLTP OLTP OLAP OLAP

6. INTRODUCTION Online transaction processing (OLTP) – the gathering and processing transaction information, and updating existing information to reflect the transaction Online transaction processing (OLTP) – the gathering and processing transaction information, and updating existing information to reflect the transaction Databases support OLTP Databases support OLTP Operational database – databases that support OLTP Operational database – databases that support OLTP Batch Processing – processing all of the transactions at once; can be used to update a database Batch Processing – processing all of the transactions at once; can be used to update a database

7. INTRODUCTION Online analytical processing (OLAP) – the manipulation of information to support decision making Online analytical processing (OLAP) – the manipulation of information to support decision making Databases can support some OLAP Databases can support some OLAP Data warehouses only support OLAP, not OLTP Data warehouses only support OLAP, not OLTP Data warehouses are special forms of databases that support decision making Data warehouses are special forms of databases that support decision making

8. OLTP, OLAP, and Business Intelligence

9. THE RELATIONAL DATABASE MODEL There are many types of databases There are many types of databases The relational database model is the most popular The relational database model is the most popular Relational database Relational database

10. Database Characteristics Collections of information Collections of information Created with logical structures Created with logical structures Include logical ties within the information Include logical ties within the information Include built-in integrity constraints Include built-in integrity constraints

11. Database – Collection of Information

12. Database – Logical Structure Character Character Field Field Record Record File (Table) File (Table) Database Database Data Warehouse Data Warehouse

13. Database – Physical Structure Bits Bits Bytes Bytes Words Words

14. Databases – Created with Logical Structures Databases have many tables Databases have many tables In databases, the row number is irrelevant; not true in spreadsheet software In databases, the row number is irrelevant; not true in spreadsheet software In databases, column names are very important. Column names are created in the data dictionary In databases, column names are very important. Column names are created in the data dictionary

15. Database – Created with Logical Structures Data dictionary – contains the logical structure for the information in a database Data dictionary – contains the logical structure for the information in a database Before you can enter information into a database, you must define the data dictionary for all the tables and their fields. For example, when you create the Truck table, you must specify that it will have three pieces of information and that Date of Purchase is a field in Date format.

16. Databases – With Logical Ties Within the Information Logical ties must exist between the tables or files in a database Logical ties must exist between the tables or files in a database Logical ties are created with primary and foreign keys Logical ties are created with primary and foreign keys Primary key Primary key Composite primary key Composite primary key Foreign key Foreign key

17. Database – Logical Ties within the Information Customer Number is the primary key for Customer and appears in Order as a foreign key

18. Databases – With Built-In Integrity Constraints Integrity constraints – rules that help ensure the quality of the information Integrity constraints – rules that help ensure the quality of the information Examples Examples Primary keys must be unique Primary keys must be unique Foreign keys must be present Foreign keys must be present Sales price cannot be negative Sales price cannot be negative Phone number must have area code Phone number must have area code

19. Steps in Developing a Database Step 1: Define Entity Classes (tables) and Primary Keys Step 1: Define Entity Classes (tables) and Primary Keys Step 2: Defining Relationships Among Entity Classes Step 2: Defining Relationships Among Entity Classes ERD (entity relationship diagram) ERD (entity relationship diagram) Normalization Normalization Step 3: Defining Information For Each Relation Step 3: Defining Information For Each Relation Step 4: Use A Data Definition Language To Create Your Database Step 4: Use A Data Definition Language To Create Your Database

20. DATABASE MANAGEMENT SYSTEM TOOLS

21. 5 Components of a DBMS 1. DBMS engine 2. Data definition subsystem 3. Data manipulation subsystem Views Views Report generators Report generators QBE tools QBE tools SQL SQL 4. Application generation subsystem 5. Data administration subsystem

22. View Binoculars

23. Report Generator

24. Query-by-Example Tool

25. Structured Query Language SQL – standardized fourth-generation query language found in most DBMSs SQL – standardized fourth-generation query language found in most DBMSs Sentence-structure equivalent to QBE Sentence-structure equivalent to QBE Mostly used by IT professionals Mostly used by IT professionals Non-procedural language, which makes it different from other programming languages Non-procedural language, which makes it different from other programming languages

26. DATA WAREHOUSES AND DATA MINING Data warehouses support OLAP and decision making Data warehouses support OLAP and decision making Data warehouses do not support OLTP Data warehouses do not support OLTP Data warehouse Data warehouse Data mart Data mart Data-mining Data-mining

27. DATA WAREHOUSES AND DATA MINING

28. Data Marts

29. Data-Mining Tools

30. Data Warehouse Considerations Do you really need one, or does your database environment support all your functions? Do you really need one, or does your database environment support all your functions? Do all employees need a big data warehouse or a smaller data mart? Do all employees need a big data warehouse or a smaller data mart? How up-to-date must the information be? How up-to-date must the information be? What data-mining tools do you need? What data-mining tools do you need?

31. INFORMATION OWNERSHIP Information is a resource you must manage and organize to help the organization meet its goals and objectives Information is a resource you must manage and organize to help the organization meet its goals and objectives You need to consider You need to consider Strategic management support Strategic management support Sharing information with responsibility Sharing information with responsibility Information cleanliness Information cleanliness

32. Strategic Management Support Data administration – function that plans for, oversees the development of, and monitors the information resource Data administration – function that plans for, oversees the development of, and monitors the information resource Database administration – function responsible for the more technical and operational aspects of managing organizational information Database administration – function responsible for the more technical and operational aspects of managing organizational information

33. Sharing Information Everyone can share – while not consuming – information Everyone can share – while not consuming – information But someone must “own” it by accepting responsibility for its quality and accuracy But someone must “own” it by accepting responsibility for its quality and accuracy

34. Information Cleanliness Related to ownership and responsibility for quality and accuracy Related to ownership and responsibility for quality and accuracy No duplicate information No duplicate information No redundant records with slightly different data, such as the spelling of a customer name No redundant records with slightly different data, such as the spelling of a customer name GIGO – if you have garbage information you get garbage information for decision making GIGO – if you have garbage information you get garbage information for decision making