MIS - 7 [Compatibility Mode]

8/2/2019 MIS - 7 [Compatibility Mode]

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Data Management


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Data

Data

A necessity for almost any enterprise to carryout its business. Consists of raw facts, andwhen organized may be transformed into

information. Database

A collection of data organized to meet users

needsDatabase Management System (DBMS)

A group of programs that manipulate the database and

provide an interface between the database and the user

of the database or other application programs.


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Brief History of Data Management Early DBMSs (late 1960s) evolved from file-

based processing systems Visualize the data much as it was stored

Tree-based (hierarchical model)

-

DEPTS

EMPS MGR

ITEMS

NAME SS#


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Advent of Modern DBMS Early 1970s Ted Codd invented new data

model (=relational data model) and theconcept of data abstraction Soon thereafter, team of IBMers invented

SQL (Structured Query Language)

Became de-facto standard for query languagesbased on the relational data model

Commercial DBMS based on relational modelare now widely accepted in industry e.g., Microsoft Access, Oracle 9i, Sybase Adaptive

Server, >20 billion dollar industry!


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Data Hierarchy in a Computer System


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File Management Systems: a physical interface

Student

AdminStudentData

Year ListTheTraditionalApproach

Se arate

TimetableScheduler

Payroll

CourseData

LecturerData

Cheques

files arecreatedand storedfor eachapplicationprogram.


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File Management Systems: Sharing

Student

AdminStudentData

Year List

TimetableScheduler

Payroll

CourseData

LecturerData

Cheques


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Data redundancy

Program-Data dependence

Problems with the Traditional File Environment

Lack of flexibility

Poor security

Lack of data-sharing and availability


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The Contemporary Database Environment

The Database

Approach A pool of related

data is shared bymultiple

programs.Rather thanhaving separatedata files, eachapplication usesa collection ofdata that is eitherjoined or relatedin the database.


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Creates and maintains databasesCreates and maintains databases

Eliminates requirement for data definitionEliminates requirement for data definitionstatementsstatements

Database Management System (DBMS)

Acts as interface between applicationActs as interface between applicationprograms and physical data filesprograms and physical data files

Separates logical and design views ofSeparates logical and design views ofdatadata


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Data Base Structures

Hierarchical and Network DBMSHierarchical and Network DBMS

Relational DBMSRelational DBMS

ObjectObject--Oriented DatabasesOriented Databases


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Hierarchical Database Model

Hierarchical Database Model

A data model in which the data is organized in a top-down, orinverted tree structure.


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A Network Data Model

Network Data Model

An expansion of the hierarchical database modelwith an owner-member relationship in which amember may have many owners.


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A Relational Data Model

Relational Data Model

All data elements are placed in two-dimensional

tables, called relations, that are the logicalequivalent of files.


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Types of Databases

Centralized database

Used by single central processor or multiple processors in

client/server network

Distributed database

Stored in more than one physical location

Partitioned database

Duplicated database


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(Analytical Database)

Multidimensional data analysis Supports manipulation and analysis of large

volumes of data from multiple

dimensions/perspectives

Operational Databases

a a ases s ore e a e a a nee e osupport the operations of the entire

organizations .

Also called Subject area database(SADB),transaction data base,Production

databases or personal databases


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The Web and Hypermedia database

Organizes data as network of nodes

Supports text, graphic, sound, video andexecutable programs


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Characteristics of a Database

Structure

data types

data behavior Persistence

store data on

Performance

retrieve and storedata quicklyCorrectness

secon ary s orage

Retrieval

a declarative querylanguage

a proceduraldatabaseprogramming

language

Sharing

concurrency

Reliability and

resilience

Large volumes


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Conceptual design: Abstract model of database

from a business perspective

Designing Databases

ys ca es gn: Detailed description ofbusiness information needs


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Data Modeling and DatabaseModels

Data Model

A map or diagram of entities and theirrelationships.

Enterprise data modeling Data modeling done at the level of the

entire organization.

Entity-Relationship (ER) diagrams A data model that uses basic graphical

symbols to show the organization of andrelationships between data.


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Data Entities, Attributes, and Keys

Entity

A generalized class of people, places, orthings (objects) for which data is collected,stored, and maintained.

Attribute

A characteristics of an entity; something theentity is identified by.

Keys

A field or set of fields in a record that is usedto identify the record.

Entities

Customer,Employee

Attributes

Customer name,Employee name

Primary key

A field or set of fields that uniquelyidentifies the record.


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An Entity-Relationship Diagram


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The Use of Schemas andSubschema's

Schema

A description of the entire

database.

Subschema

A file that contains a

description of a subset of the

database and identifies

modifications on the dataitems in that subset.

21


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Management Requirements for Database Systems

Key elements in a database environment:

Data Administration

ata ann ng an o e ng et o o ogy

Database Technology and Management

Users


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Management Requirements for Database Systems


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Advanced Databases -


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todays Problem: Heterogeneous Information Sources

Heterogeneities are everywhere

PersonalDatabases

Different interfaces

Different data representations

Duplicate and inconsistent information

Digital Libraries

Scientific DatabasesWorldWideWeb


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Our Goal: Unified Access to Data

Integration System

Collects and combines information

Provides integrated view, uniform user interface

Supports sharing

WorldWorldWorldWorldWideWideWideWide

WebWebWebWeb

Digital Libraries Scientific Databases

Personal

Databases


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Data warehouse Evolution

200019951990198519801960 1975

Relational

Databases

Company

DWs

Building the

DW

Inmon (1992)

Data Replication

Tools

n ormat on-

Based

Management

DataRevolution

MiddleAges

PrehistoricTimes

PCs and

SpreadsheetsEnd-user

Interfaces

1st DW

Article

DW

Confs.

Vendor DW

Frameworks


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What is a Data Warehouse?

A Data Warehouse is a

subject-oriented, integrated,

- ,

non-volatile

collection of data used in support of

management decision makingprocesses.


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Subject-Oriented: The data warehouse is organized around the key

subjects (or high-level entities) of the enterprise.

Major subjects include Customers, Patients,Students,Products etc .

n egra e

The data housed in the data warehouse are defined

using consistent

Naming conventions Formats

Encoding Structures

Related Characteristics


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Time-variant

The data in the warehouse contain a time

dimension so that they may be used as a historical

record of the business

-

Data in the data warehouse are loaded and

refreshed from operational systems, but cannot be

updated by end-users


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The Data Warehouse Continued

Characteristics of data warehousing are:

Time variant. The data are kept for many years so they canbe used for trends, forecasting, and comparisons over time.

Nonvolatile. Once entered into the warehouse, data are notu dated.

Relational. Typically the data warehouse uses a relationalstructure.

Client/server. The data warehouse uses the client/serverarchitecture mainly to provide the end user an easy accessto its data.

Web-based. Data warehouses are designed to provide anefficient computing environment for Web-based applications


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Data Warehouse- A Practitioners Viewpoint

A data warehouse is simply a single,

complete, and consistent store of data obtained

from a variety of sources and made available

to end users in a way they can understand anduse it in a business context.

-- Barry Devlin, IBM Consultant

W h i d I d t


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Warehousing and Industry

Warehousing is big business

$2 billion in 1995

$3.5 billion in early 1997

Predicted: $8 billion in 1998 [Metagroup]

WalMart has largest warehouse 900-CPU, 2,700 disk, 23 TB Teradata system

~7TB in warehouse

40-50GB per day

W h i S i li d DB


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Warehouse is a Specialized DB

Standard DB

Mostly updates

Many small transactions Mb - Gb of data

Current sna shot

Data Warehouse Mostly reads

Queries are long andcomplex

Gb - Tb of data

Index/hash on p.k. Raw data

Thousands of users (e.g.,

clerical users)

Lots of scans Summarized, reconciled

data

Hundreds of users (e.g.,decision-makers,analysts)

P iti f th D t W h Withi


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Position of the Data Warehouse Within

the Organization

Th D t W h


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The Data Warehouse Architecture


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The Data Mart

A data mart is a small scaled-down version of a datawarehouse designed for a strategic business unit (SBU) or adepartment. Since they contain less information than thedata warehouse they provide more rapid response and aremore easily navigated than enterprise-wide datawarehouses.

Replicated (dependent) data marts are small subsets of thedata warehouse. In such cases one replicates some subsetof the data warehouse into smaller data marts, each of whichis dedicated to a certain functional area.

Stand-alone data marts. A company can have one or moreindependent data marts without having a data warehouse.Typical data marts are for marketing, finance, andengineering applications.

Position of the Data Mart Within


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Position of the Data Mart Within

the Organization

Data Mart

Decision

Support

Information

ata

Delivery

Data Mart

Data Mart

Decision

SupportInformation

Decision

Support

Information

Data Warehousing: Two Distinct Issues


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Data Warehousing: Two Distinct Issues

(1) How to get information into warehouse

Data warehousing

(2) What to do with data once its inwarehouse

Warehouse DBMSBoth rich research areas

Industry has focused on (2)

Wh C D W h D ?


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What Can a Data Warehouse Do?

Some of the benefits of a DW are:

Immediate information delivery Data integration from across and even

Future vision from historical trends

Tools for looking at data in new ways

Freedom from IS department resourcelimitations (you dont need programmersto use a data warehouse)


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Examples of Common DW Applications


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Sales Analysis

Determine real-time product sales to make vital pricing and distributiondecisions.Analyze historical product sales to determine success or failure attributes.Evaluate successful products and determine key success factors.

Quickly isolate past preferred customers who no longer buy.Identify daily what product is in the manufacturing and distribution pipeline.Instantly determine which salespeople are performing, on both a revenueand margin basis, and which are behind.

Examples of Common DW Applications

Financial Analysis

Compare actual to budgets on an annual, monthly and month-to-date basis.Review past cash flow trends and forecast future needs.Instantly generate a current set of key financial ratios and indicators.Receive near-real-time, interactive financial statements.

Human Resource AnalysisEvaluate trends in benefit program use.Identify the wage and benefits costs to determine company-wide variation.

Other Areas

Warehouses have also been applied to areas such as: logistics, inventory,

purchasing, detailed transaction analysis and load balancing.

The Future of Data Warehousing


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g

Typical Nonintegrated Information Architecture

i2 Supply Chain Oracle Financials Siebel CRM 3rd Party Data

OracleFinancial

DW

MarketingDW

SupplyChain

Data Mart

Subset Non-Architected Data Marts

Federated Integrated Information Architecture


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Federated Integrated Information Architecture

i2 Supply Chain Oracle Financials Siebel CRM 3rd Party Data

CommonData Staging

FederatedFinancial

DW

FederatedMarketing

DW

FederatedSupply ChainData Mart

Subset Non-Architected Data Marts

MIS - 7 [Compatibility Mode]

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