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Conceptual Data Model

Logical Data Model

Physical Data Model

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EnterpriseData Model

Big picture (at Enterprise level)

Data Modelling in Business Analysis

Data modelling is the process of building a data model.

Data Model = Way�ndingMap

Blueprint

These are all types of models that represent a �ltered, simpli�ed viewof something complex with a goal of improving a ‘way�nding’ experienceby helping people understand part of the real world.(e.g., to help architects

communicate building plan)

(e.g., to help visitorsnavigate the city)

Data model focuses on What data is required and How it should be organised rather than what operations are performed on data.

Data model is independent of hardware and software constraints.

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Timer translates to Time

Allows for real-time snapshot or a snapshot for some time in the future.

Camera: Timer Setting

Can capture the current view or ‘to-be’some time in the future.

Model: Time Factor

Focus translates to Abstraction

Can make certain objects appear sharp or blurry.

Camera: Focus Setting

Allows to represent ‘sharp’ (concrete) or‘fuzzy’ (generic) concepts.E.g., we may abstract Employee and Consumer into a more generic Person.

Model: Abstraction Factor

Filter translates to Function

Can adjust the appearance of the entirepicture to produce certain e�ect.

Camera: Filter Setting

Allows to represent either business orfunctional view on the model.- Business: use business terms & rules- Application: use application terms & rules

Model: Function Factor

Format translates to Model Type

A camera has a number of di�erent formats in which the photo canbe captured.

Camera: Format Setting

To make the model either at very broad level, or more detailedlogical & physical view.- Conceptual: communication and de�nition of business terms & rules- Logical: clari�cation and detail of business rules & data structures- Physical: technical implementation on a physical database.

Model: Type Factor

Zoom translates to Scope

Allows to capture a broad area with minimaldetail, or a narrow scope with more detail.

Camera: Zoom Setting

Varies how much we can see in the model.E.g., model can include just claims processing,or all concepts in insurance business.Scope of model can be: a department, or anorganisation, or an industry.

Model: Scope Factor

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Entity

To represent concepts that are used by business processes(not to contain processes)E.g., Raw Materials, Finished Goods, Machinery, Product Schedule, etc. not Manufacturing

Entity types: conceptual, logical, and physical.

DataElement

A data element is a property of importance to the businesswhole values contribute to identifying, describing, ormeasuring instances of an entity.Data element can exist at conceptual (aka subject area), or logical, or physical levels.

Relationship

Rules are visually captured on data model through relationships. It captures the rules between two entities.Relationship Type: data rule or action rule.

Data rules: instructions on How data relate to one another.Action rules: instructions on What to do when data elementscontain certain values. E.g., take 10% o� of an order if the order contains more than 5 products.

Key

Data element(s) that allow us to �nd speci�c entityinstances are known as keys.A key has main characteristics: unique, non-volatile,and minimal.A foreign key is a data element that provides a link toanother entity.

Agree basic business concepts and rules.CDM includes business terms/concepts or subjects, their de�nitions,and relationships showing how these subjects interact with each other.

Take business needs de�ned in CDM down to next level of business solution.LDM is explained along with a comparison of relational and dimentional mindsets.

Key concepts and their business rules.e.g., “Customer can place many Orders.”

Key concepts focused around one or more measures, e.g., “I want to see Gross Sales Amount by Customer.”

All data elements required for a givenapplication (or business process), organised into entities according to strictbusiness rules and independent oftechnology.

All data elements required for a given reporting application, focused on measures and independent of technology.E.g., “I want to see Gross Sales Amount by Customer, andview the Customer’s �rst and last name.”

The LDM modi�ed for a speci�c database technology. E.g., “To improve retrievalspeed, we need a non-unique index onCustomer Last Name.”

The LDM modi�ed for a speci�c database technology. E.g., “Because there is a need to view Gross Sales Amount at aDay level, and then by Month and Year, we should considercombining all calendar data elements into a single table.”

Relational Dimentional(captures HOW business works) (captures WHAT business is monitoring or measuring)

CDM / SAM

LDM

PDM

Mindset

Take business needs business solution de�ned in LDM to next level of technical solution.PDM is the LDM modi�ed for a speci�c set of software or hardware. PDM oftengives up perfection for practicality, factoring in real concerns (speed, space, security)

What is Data Model

Data Model Components

Data Model Levels

Camera Settings applied to Data Model

Data Modelling Process

How to Work E�ectively with Others

Build Conceptual Data Model

Business Needs, Wants, Ideas

Design Logical Data Model

Business Requirements

Customerʼs Business Specialist and IT BA

Software Requirements

Design Physical Data Model

Database Model

IT BA / Data Modeller

Elicit & Analyse Business Requirements

Technical / DB Designer

Identify Non-functional Requirements

Analyse & VerifySoftware Requirements

Validate & DefineTechnical Solution

De�ne scope, audience, context forinformation.

De�ne key business concepts and theirde�nitions.

Main purpose is for communication andagreement of scope and context.

Main purpose is for communication andagreement of de�nitions and businesslogic.

Relationships optional. If shown,represent hierarchy.

Many-to-Many relationships OK.

Conceptual Data Model Logical Data Model Physical Data Model

Represent core business rules and datarelationships at a detailed level.

Provide enough detail for subsequent�rst cut physical design.

Many-to-Many relationships resolved.

No attributes shown. Attributes are optional. If shown, can be composite attributes to convey businessmeaning.

Attributes required and all attributes areatomic. Primary and foreign keys de�ned.

Not normalised. (Relational models) Not normalised. (Relational models) Fully normalised. (Relational models)

Subject names should represent high--level data subjects/concepts, orfunctional areas of the business.

Concept names should use buinessterminology. Many concepts aresupertypes, although subtypes may beshown for clarity.

Entity names may be more abstract. Supertypes all broken out to includesubtypes.

One-page model/diagram. Should be one-page model/diagram. May be larger than one page.

Business-driven. Cross-functional and more senior peopleinvolved in development process withfewer IT.

Cross-functional and technology driven.Resolve non-functional requirements.

Informal notation. ‘Loose’ notation required - some formatconstruct needed, but ultimate goal is tobe understood by business users.

Formal notation required.

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Tip

person or organisation of interest. Employee, Patient, Passenger

Naming an Entity Example

product or service of interest Product, Service, Course

calendar or time interval of interest Semester, Fiscal Period

location of interest to the enterprise Distribution Point, WarehouseWhere

event or transaction of interest Order, Return, Complaint, Deposit

documentation of the event of interest Invoice, Contract, Ticket

Who

What

When

WhyHow

What the business says...

Students enroll for a course by submitting an application via our web portal,providing their name, date of birth, email, selected courses, and card details.TopTrainingCorp arranges for distribution of the necessary payment to therelevant examination centre and certi�cation body. Instructors deliver our courses over 3 days after which the students sits 2examinations consisting of 40 multiple-choice questions.

Completeness Integrity Flexibility Understandability

Correctness Simplicity Integration Implementability

Data Model Quality

Business Dimension of Quality

Technical Dimension of Quality

Whether the model conforms tothe rules of data modellingtechnique (i.e., whether it is avalid data model). This includes diagrammingconventions, naming rules, de�nition rules, and rules ofcomposition and normalisation.

Data model contains theminimum possible entitiesand relationships.

Consistency of data modelwith the rest of theorganistion’s data.

Ease with which the datamodel can be implementedwithin the time, budget,and technology constraintsof the project.

Whether the model contains allinformation required to supportthe required functionality ofthe system.

Whether the model de�nesall business rules whichapply to the data.

Ease with which the datamodel can cope with thebusiness and/or regulatorychange.

Ease with which theconcepts and structures inthe data model can beunderstood.

Characteristics of Good Data Model

Persuading business and technicalpeople of the value of datamodelling.Building an e�ective workingrelationship. Teamwork.

Recognising People Issues

Understanding context.Identifying stakeholders.Asking key questions.Packing it up.

Setting Expectations

Following good practices:- work close with client,- keep in touch with all stakeholders- organise real progress meetings,- active listeningDealing with problems:- establish who is accountable for resolving- take time out- keep it in perspective

Staying on Track

Following up.Writing reports.Continuous improvement.

Achieving Closure

Tip

Thai Son, BA Manager, Harvey Nash

A data model is a statement of business requirements as they relate to data.