present data warehouse

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Planning & ProjectPlanning & ProjectManagementManagement

Fahri Firdausillah [M031010



Joke First, Serious LaterJoke First, Serious Later● Consultant:Consultant: So, your company is into dataSo, your company is into data

warehousing? How many data marts do you have?warehousing? How many data marts do you have?● Project Manager:Project Manager: Eleven.Eleven.

● Consultant:Consultant: That’s great. But why so many?That’s great. But why so many?● Project Manager:Project Manager: Ten mistakes.Ten mistakes.



Defining the BusinessDefining the BusinessRequirementsRequirements

Chapter 5Chapter 5



PreamblePreamble● OLTP and DW planning is different in term of OLTP and DW planning is different in term of

requirements clarityrequirements clarity● Planning DW is about solving users’ problems andPlanning DW is about solving users’ problems and

providing strategic information to the user.providing strategic information to the user.● OLTP systems are primarily data capture systems. OnOLTP systems are primarily data capture systems. On

the other hand, data warehouse systems arethe other hand, data warehouse systems areinformation delivery systems.information delivery systems.

● Unlike an OLTP system, which is needed to run the day-Unlike an OLTP system, which is needed to run the day-to-day business, no immediate payout is seen in ato-day business, no immediate payout is seen in adecision support system.decision support system.



Dimensional Analysis (cont'd)Dimensional Analysis (cont'd)● They can tell you what measurement units areThey can tell you what measurement units are

important for them, how they combine theimportant for them, how they combine thevarious pieces of information for strategicvarious pieces of information for strategicdecision making.decision making.

● Although the actual proposed usage of a dataAlthough the actual proposed usage of a datawarehouse could be unclear, the businesswarehouse could be unclear, the businessdimensions used by the managers for decisiondimensions used by the managers for decisionmaking are not nebulous at allmaking are not nebulous at all



Dimensional Analysis “in Action”Dimensional Analysis “in Action”



More Complex Dimensional ModelMore Complex Dimensional Model



Information PackagesInformation Packages● The business dimensions and their hierarchical levels formThe business dimensions and their hierarchical levels form

the basis for all further development phases.the basis for all further development phases.● The dimension hierarchies are the paths for drilling down orThe dimension hierarchies are the paths for drilling down or

rolling up in our analysisrolling up in our analysis



Requirements Gathering MethodsRequirements Gathering Methods

Grou p Sessi on

Interview

Types of Questions● Open Ended QuestionThese open up options for

interviewees to respond

● Closed QuestionThese allow limited responses to

interviewees● ProbesThese are really follow-up

questions. Probes may be usedafter open-ended or closedquestions



Sample Expectation fromSample Expectation fromInterviewsInterviews

Senior Executives Dept. Managers IT Dept. Professional

● Organization objectives● Criteria for measuring success●

Key business issues, current &future● Problem identification● Vision and direction for theorganization● Anticipated usage of the DW

● Departmental objectives● Success metrics●

Factors limiting success● Key business issues● Products & Services● Useful business dimensionsfor analysis● Anticipated usage of the DW

● Key operational sourcesystems●

Current information deliveryprocesses● Types of routine analysis● Known quality issues● Current IT support forinformation requests● Concerns about proposed DW



Adapting JADAdapting JAD

1. Pro

j ect

Defin

ition 2 . R e s e a r

c h

3

. Prep aratio

n

4. JADSessions

5 . F i n a l

D o c u m

e n t

1.1. Identify project objectives andIdentify project objectives andlimitationslimitations

2.2. Identify critical success factorsIdentify critical success factors

3.3. Define project deliverablesDefine project deliverables

4.4. Define the schedule of workshopDefine the schedule of workshopactivitiesactivities

5.5. Select the participantsSelect the participants

6.6. Prepare the workshop materialPrepare the workshop material

7.7. Organize workshop activities andOrganize workshop activities andexercisesexercises

8.8. Prepare, inform, educate thePrepare, inform, educate theworkshop participantsworkshop participants

9.9. Coordinate workshop logisticsCoordinate workshop logistics



Requirement Definition: Scope &Requirement Definition: Scope &ContentContent

Requirements denition document is the basis for theRequirements denition document is the basis for thenext phases. Formal documentation will also validatenext phases. Formal documentation will also validateyour ndings when reviewed with the usersyour ndings when reviewed with the users

● Data SourcesData Sources● Data TransformationData Transformation● Data StorageData Storage● Information DeliveryInformation Delivery● Information Package DiagramsInformation Package Diagrams



Requirements Denition DocumentRequirements Denition DocumentOutlineOutline

1.1. IntroductionIntroduction

2.2. General Requirements DescriptionsGeneral Requirements Descriptions

3.3. Specic RequirementsSpecic Requirements

4.4. Information PackagesInformation Packages

5.5. Other RequirementsOther Requirements

6.6. User ExpectationsUser Expectations

7.7. User Participation and Sign-Off User Participation and Sign-Off

8.8. General Implementation PlanGeneral Implementation Plan



Requirements as theRequirements as theDriving Force for DataDriving Force for Data

WarehousingWarehousing

Chapter 6Chapter 6



PreamblePreamble● If accurate requirements denition is important for anyIf accurate requirements denition is important for any

operational system, it is many times more important foroperational system, it is many times more important fora data warehousea data warehouse

● extremely important that your datawarehouse containsextremely important that your datawarehouse contains

the right elements of information in the most optimalthe right elements of information in the most optimalformatsformats

● Every task that is performed in every phase in theEvery task that is performed in every phase in thedevelopment of the data warehouse is determined bydevelopment of the data warehouse is determined bythe requirementsthe requirements

● Every decision made during the design phase is totallyEvery decision made during the design phase is totallyinuenced by the requirements.inuenced by the requirements.



Data DesignData Design



Data Design (cont'd)Data Design (cont'd)● Structure for Business DimensionsStructure for Business Dimensions

● Importance of having the appropriate dimensions and theImportance of having the appropriate dimensions and theright contents in theright contents in the information package diagramsinformation package diagrams ..

● Structure for Key MeasurementsStructure for Key Measurements● Users measure performance by using and comparing keyUsers measure performance by using and comparing key

measurementsmeasurements● In order to review using proper key measurements, DW has toIn order to review using proper key measurements, DW has to

guarantee the information package diagrams contain all theguarantee the information package diagrams contain all therelevant keys.relevant keys.

● Levels of DetailLevels of Detail● DW needs to provide drill-down and roll-up facilities forDW needs to provide drill-down and roll-up facilities for

analysisanalysis● How deep detail of data is needed in DWHow deep detail of data is needed in DW



Data Design “in Action”Data Design “in Action”

Structure forBusiness Dimensions

Structure forKey Measurements

Levels of Detail



The Architectural PlanThe Architectural Plan



Source DataSource Data● Production Data: Data get from operational system.Production Data: Data get from operational system.

Normally include financial system, customerNormally include financial system, customerrelationship system, manufacturing system, etc.relationship system, manufacturing system, etc.

● Internal Data: Private data keep by internalInternal Data: Private data keep by internal

organization. Could be spreadsheets, documents, evenorganization. Could be spreadsheets, documents, evendepartmental databasedepartmental database

● Archived Data: Old data that is already not to be usedArchived Data: Old data that is already not to be usedin operational system.in operational system.

● External Data: Data from outside systems, it can alsoExternal Data: Data from outside systems, it can alsofrom outside company. This type of data usually do notfrom outside company. This type of data usually do notconform internal formatconform internal format



Data StagingData Staging

Bad data lead to bad decision,Bad data lead to bad decision,data quality in data warehouse is sacrosanctdata quality in data warehouse is sacrosanct● ETL process ensure data to be ready stored andETL process ensure data to be ready stored and

processed in DW.processed in DW.

● In many cases data need to be extracted from sourcesIn many cases data need to be extracted from sourcesin different scheme, different vendor, even in differentin different scheme, different vendor, even in differentformat of flat files.format of flat files.

● If data extraction for a DW poses great challenges, dataIf data extraction for a DW poses great challenges, data

transformation presents even greater challenges.transformation presents even greater challenges.

● Data need to be cleaned from misspelling, resolutionData need to be cleaned from misspelling, resolutionconflict, duplication, setting default missing values, etc.conflict, duplication, setting default missing values, etc.

● Initial load moves very large volumes of data. After thatInitial load moves very large volumes of data. After that

data staging will continuously extract the changes fromdata staging will continuously extract the changes fromsources.sources.

●

Extract

● Transform●

Load



Sample ArchitectureSample Architecture



Information Delivery StrategyInformation Delivery Strategy



MetadataMetadata● Operational Metadata:Operational Metadata:

When deliver information to the end-users, you must be ableWhen deliver information to the end-users, you must be ableto tie that back to the original source data sets. Operationalto tie that back to the original source data sets. Operationalmetadata contain all of this information about theoperationalmetadata contain all of this information about theoperationaldata sources.data sources.

● Extraction and Transformation Metadata:Extraction and Transformation Metadata:Storing information of extraction frequencies, extractionStoring information of extraction frequencies, extractionmethods, and business rules for the data extraction.methods, and business rules for the data extraction.

● End-User Metadata:End-User Metadata:Navigational map of the data warehouse, allows the end-Navigational map of the data warehouse, allows the end-users to use their own business terminology and look forusers to use their own business terminology and look forinformation in those ways.information in those ways.



Management & ControlManagement & Control● Sits on top of all the other components.Sits on top of all the other components.● Controls the data transformation and theControls the data transformation and the

data transfer into the data warehousedata transfer into the data warehouse

storage.storage.● Interacts with the metadata componentInteracts with the metadata component

to perform the management and controlto perform the management and control

functions.functions.● Metadata is the source of information forMetadata is the source of information for

the management module.the management module.



End of PresentationEnd of Presentation

&&Thank You Very MuchThank You Very Much

present data warehouse

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