Introduccion a BI y conceptos

2.  Data sources often store only current data,
not historical data
 Corporate decision making requires a unified
view of all organizational data, including
historical data
2

3.  Data warehouse
A physical repository where relational data are
specially organized to provide enterprise-wide,
cleansed data in a standardized format
 A DW delivers a collection of integrated data
used to support the decision making process
for the enterprise
3

4.  A data warehouse is a repository (archive) of
information gathered from multiple sources,
stored under a unified schema, at a single site
 Greatly simplifies querying, permits study of
historical trends
 Shifts decision support query load away from
transaction processing systems
4

5. 5

6.  Characteristics of data warehousing
 Subject oriented
▪ organized based on use: sales, products, customers
6

7.  Characteristics of data warehousing
 Integrated
▪ inconsistencies removed
7

8.  Characteristics of data warehousing
 Time variant: data are normally time series, A
warehouse maintains historical data
 Nonvolatile: stored in read-only format, periodically
refreshed, Changes are recorded as new data
8

9.  Characteristics of data warehousing
 Summarized
▪ in decision-usable format
 Large volume
▪ data sets are quite large
 Non normalized
▪ often redundant
 Metadata
▪ data about data are stored
9

10.  Integrated, company-wide view of high-quality
information (from disparate databases)
 Separation of operational and informational systems and
data (for improved performance)
10

11.  Data mart
A departmental data warehouse that stores
only relevant data
 Focuses on a particular subject or department
11

12. Legacy
systems Legacy
feed data to Systems
Sales
the
Finance
Data Mart
Data Mart
Operational Marketing
Data Store Data Mart
warehouse.
Accountin
Operational g
Data Store Data Mart
The
warehouse Operational
Organizational
feeds
Data Store
Data
Warehouse
specialized Operational
information to Data Store
departments.
12

13. Organizational Data
Warehouse
The data Corporate
Highly granular data
Normalized design
Finance
Data Mart
Sales
Data Mart
Marketing
Robust historical data
mart serves Large data volume
Data Model driven data
Versatile
Data Mart
the needs of General purpose DBMS
technologies
Accting
Data Mart
one
business Data Marts
Departmentalized
unit, not the Summarized, aggregated
data
Star join design
organization. Limited historical data
Limited data volume
Requirements driven data
Organizational Focused on departmental
Data needs
Multi-dimensional DBMS
Warehouse technologies
13

14.  Dependent data mart
A subset that is created directly from a data
warehouse
 Quality data
 Support enterprise wide data model
14

15.  Independent data mart
A small data warehouse designed for a
strategic business unit or a department, but its
source is not an EDW
15

16.  Operational data stores (ODS)
A type of database often used as an interim
area for a data warehouse, especially for
customer information files
 Volatile
 Used for short-term decisions involving
mission-critical application
 Store only very recent information
16

17.  Oper marts
An operational data mart. An oper mart is a
small-scale data mart typically used by a single
department or functional area in an
organization
 The data for an oper-mart come from an ODS
17

18.  Enterprise data warehouse (EDW)
 Is a large scale DW that is used across the
enterprise for decision support
 A technology that provides a vehicle for pushing
data from source systems into a data warehouse
18

19. 19

20.  Metadata
Data about data. In a data warehouse,
metadata describe the contents of a data
warehouse and the manner of its use
20

21.  Metadata
 As with other databases, a warehouse must include
a metadata repository
▪ Information about physical and logical organization of
data
▪ Information about the source of each data item and the
dates on which it was loaded and refreshed
21

22.  Direct benefits of a data warehouse
 Allows end users to perform extensive analysis
 Allows a consolidated view of corporate data
 Better and more timely information
 Enhanced system performance
 Simplification of data access
 Data integration
 No more redundancy
 Consistency of data content
22

23.  Direct benefits of a data warehouse
 Improved data quality
 Historical enterprise data
 Unlimited, ad-hoc reporting
 Reliable trend analysis reporting
 Faster data delivery and data access
 Business intelligence (BI) capabilities
23

24.  Indirect benefits result from end users using
these direct benefits
 Enhance business knowledge
 Present competitive advantage
 Enhance customer service and satisfaction
 Facilitate decision making
 Help in reforming business processes
24

25.  DECISION SUPPORT SYSTEMS AND
BUSINESS INTELLIGENCE. Turban
 Modern Data Warehousing, Mining, and
Visualization: Core Concepts. George M.
Marakas
 Modern Database Management.9th
Edition.Jeffrey A. Hoffer, Mary B. Prescott,
Heikki Topi
25