reducing tool costs

© 2013 Kalido I Kalido Confidential I April 8, 202311

Session Topic: Reducing Tool Costs

Eliminate redundant tools. Reduce recurring costs.


Traditional Data Warehouse Build

Master Data Governance and Stewardship

Schema Management

Model and Metadata Management

Workflow ProductsData Profiling CDI MDM Tools PIM MDM Tools

OperationsData Integration

ETL Tools

Modeling Tools Metadata Repositories

Modeling Tools

Process Automation

Task Execution and Monitoring

Deployment and Migration

Archiving

Restore for Model and Data

Undo Loads

Audit and Logging

Presentation

Metadata Management for BOBJ

Native XLS Pivot Table Generation

Native QlikView Generation

Metadata Management for MSAS

Metadata Management for COGN

MDM Consumer Interface

Report-Time Formula Management


Model-Driven, Best Practices-based, Automation

Master Data Governance and Stewardship

Schema Management

Model and Metadata Management

Hierarchy Management Workflow and SecurityData Profiling and Validation Data Authoring

Controlled PublicationIdentity Management

Auto-generated Application

Browse and Search Full History and Audit TrailsAuto Match and Merge

OperationsData Integration

Data Validation

Suspense and Exception Handling

Data Sourcing and Field Mapping

Delta Detection

Surrogate Key Management

Code Management and Lookup

Currency and UoM

Graphical Modeling

Model FederationMulti-GranularitySub-typing and Inheritance

Composite EntitiesRagged Hierarchies Change ManagementKPI Management

Business Metadata Classification Hierarchies

Star and Snowflake Schema

Physical Schema Management

Slowly Changing Dimensions

Data Mart and Aggregates

Data Load and Index Management

Rollup Path Awareness

Incremental Summary Generation

Process Automation

Task Execution and Monitoring

Deployment and Migration

Archiving

Restore for Model and Data

Undo Loads

Audit and Logging

Presentation

Metadata Management for BOBJ

Native XLS Pivot Table Generation

Native QlikView Generation

Metadata Management for MSAS

Metadata Management for COGN

MDM Consumer Interface

Report-Time Formula Management

Automated


Kalido Business Information Model - Cutaway

Transactions

Measures

Contextual ObjectsReference dataMaster data

Attributes

Dimensions


The Traditional Modeling Approach

Conceptual Model

BusinessRepresentative

Data Architect

Logical Data Model

BusinessDictionary

Physical Data ModelStaging Normalised Star Schema Data Mart

DBA

BusinessAnalyst

Sources Physical Schema & Data

ETL

ETL

Staging

ETL

Normalised Star Schema Data MartETL

ETL

ETL

ETL

ETL

ETL

BI Layer

Developer

BI Developer

Business Requirements


Software Automation Transforms The Model Into Metadata That Automates Warehouse Creation

A Kalido Information Engine is

deployed by pressing “Start” and

letting the Kalido software

automatically structure the tables

and generate the BI semantic layer.


Metadata Repositories

1. Can be invasive to the development process2. Big initial push, but often get out of date and stop being used3. Project runs out of time and ‘metadata and documentation’ pushed

to future phase that never comes4. Silos of metadata (spreadsheets, ETL focused repositories, glossaries)5. Become “write only” databases


Metadata in Kalido – Starts in BIM


Model to Reporting

BI, Reporting, Analysis

Cognos Framework

Manager

Universal Information Director

Data MartGeneration

TimeYear

Day

Month of Year

Day of Week

Day of Month

Finance

Account

J ournal Entry

Asset ClassGeneral Ledger

Column

Product

Product

Product Subgroup

Product Group

Product Category

Product Class Packaging

Sales RevenueMargin Deductions

►Amount

Gross Sales

►Amount

I nternal Organization

Employee

Field EmployeeHeadquarters

Employee Contractor

Department

Corporation

Division

Quarter

Quarter of Year

Month

Kalido Warehouse

Sourcethe Business Metadata

Translate Business Model to Semantic Definitions - Set scope - Define hierarchy - Interpret time variance - Select paths - Generate aliases

Automatically Generate Semantic Layer

Update and Maintain the Semantic Layer

Business Objects

Universe

Microsoft Analysis Services


ETL: A Traditional Warehouse Takes 12-18 Months

80% of the project effort is invested in Data Integration, Testing, Modeling, BI Development and Release to Production processes


Source: customer benchmark

Kalido Reduces ETL

Traditional DW vs. Kalido Agile Approach

Tim

e &

Mo

ney

65% Reduction in Data Integration

20% Reduction in Data Access/BI vs. Traditional

KalidoTime To

Value Zone


Summary of ETL Sunsetting

ETL primarily for data sourcing– Exceptions for your most complex derivations, calculations

still easier by modeling/automating component parts still managed within Kalido in value-added loop for consistency,

easy change/extend, mart/BI generation, and re-use

50-75% reductions in ETL work

Dramatic impact on– Delivery acceleration– Ease of change/agility– Ease of maintenance– Risk of business change, incomplete requirements, etc.– Overall TCO


Multiple MDM Domain Support

Manage all types/domains of master data

Handles EVERY master data domain – such as organization, channel, supplier, KPI, employee

Not limited to just product data or just customer data

Generic data model

Objective

Capabilities

BenefitsA single tool for all types of master dataConsistency as domains are addedEasy for IT to support and maintain

Objective

Anheuser-Busch InBev manages more than 250 classes of data

All of Kalido MDM customers manage more than one “major” data domain

Customer Examples


Sophisticated Modeling

Ensure relationships between master data domains can be created and managed

Supertyping and subtyping

Business rule definition and management

Data validation rules

Accessibility by both IT and business users

Objective

Capabilities

BenefitsEasily handles the many complex data relationships between entitiesCommon understanding between IT and line of business end users

Objective

A Components Distributor uses Kalido to manage complex product hierarchies. They serve as a broker between suppliers and customers. A single part may be supplied by multiple suppliers, each with their own part numbers. It may also be used by multiple customers, also with their own part numbers.

Customer Example


Workflow

Automate and drive the data stewardship process when people need to make decisions

Flexible, robust built-in workflow routes master data validation actions to specific users or groups for human resolution

Flexible and comprehensive “state” transition steps

Change workflow routing based on context

Controllable via API for exits to external code modules for the most complex workflows

Easily manages increasingly complex governance and stewardship processes

Objective

Capabilities

BenefitsAutomated data stewardship process saves time and effortFocuses data stewards on only resolving exceptions

Objective

A UK media company includes 14 different departments in the lifecycle of master data, requiring extremely complex workflow

Customer Example


Tool Elimination Summary

ER Modeling Tools

Metadata Management Tools

ETL Tools

MDM Products and/or Workflow Products

Initial purchase cost and on-going annual product maintenance for all of these tools can be significant!


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reducing tool costs

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