IQCards Data Warehousing Identify Qualify

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I D E N T I F Y Q U A L I F Y Selling Informatica into Data Warehouse Projects

Data Warehousing

Data WarehousingA repository of data stored electronically in a database to support reporting and analysis. Repository types include:

Data mart Departmental, subject area-specific data for historical reporting and analysis

Data warehouse Multi-subject area data for historical reporting and analysisEnterprise data warehouse Multi-subject area including both historical data

and real-time data for real-time reporting, operational data integration, and monitoring

Informatica ProvidesHigh performance, high availability Data Integration tools (also referred to as

Extract, Transform, and Load or ETL) to move data from source systems into the data warehouse at any latency (batch, near real-time, and real-time)

Metadata Management tools to track data changes and definitions, and to improve communication about the data between IT and business users

Data Quality tools to profile, cleanse, and enrich the data needed for the data warehouse

Identifying OpportunitiesHand-coding integration hard-coding transformation logic. This approach is

not flexible, is difficult for others to understand, and can introduce data quality issues

Legacy tools originally selected for the ETL are not scaling to meet data volumesIT is trying to save money by consolidating efforts and past projects, but they

are struggling to standardize on tools

Business users are complaining about poor quality data in the data warehouseDifficult for IT to show the business history and lineage of the dataThe business is having problems keeping pace (complying) with ever-changing

and increasing regulatory reporting requirements

Qualifying OpportunitiesData sources/volumes increasing dramatically. IT struggling to keep pace with

rate of change

IT asked to improve quality of service with reduced funding/resourcesBusiness users do not feel confident about making decisions based on their

data warehouse reports

Company is exposed to regulatory finesBusiness is demanding more real-time data in the data warehouse

Target ProspectsBuilding data marts, data warehouses, enterprise data warehouse solutionInvesting in business intelligence, enterprise reporting, data mining, real-time

dashboard solutions

Looking for ETL or data quality solutions to replace hand-codingInvesting in new or expanding data warehouse technologies

Buyers and InfluencersVP and Director of Data Warehousing (decision maker)Data Architect, DW Architect, Enterprise Architect (approver)CFO, COO, VP of Business Areas (business sponsor)

High Value QuestionsHow are you approaching data integration and data quality needs for your data

warehouse projects?

What tools have you used on past projects? Which are considered standards?How is the demand for latency requirements changing?How are data definitions communicated, discussed, and agreed on with the

business? What do you do when they change?

What consideration has been given to consolidating integration projects and talent?

What challenges are you experiencing with increasing regulatory reporting requirements?


I D E N T I F Y Q U A L I F Y Competing and Positioning

Data Warehousing

Top Competitors in Data WarehousingCompetitor Customer Perception Risk

Hand-coding No software to purchaseDevelopers know their

business the best

Expensive to maintainNot flexible or scalable

IBM Market thought leaderPre-existing data modelsAble to address software,

hardware, and services

IBMs closed and complex architecture and models are difficult to implement, learn, and maintain

Limited and restricted to IBM services (locked in)

Ab Initio Perceived as performance leader

Difficult to use, limited ecosystem

Inflexible on business terms (e.g., no offshore resources allowed)

High TCO for customersOracle and SAP

Provided as part of a full Business Intelligence stack

Adequate for departmental projects

Products are not scalable for enterprise deployments

Risk being locked into these vendors and out of their legacy applications

Key Customers

Oi Nationwide Insurance Electronic Arts

PositioningPosition Informatica as the most capable, neutral, and complete technology

vendor.

If customer is currently working with our data warehouse partners (Teradata, Netezza, DATAllegro, HP, or Neoview) contact the partner to explore opportunities to collaborate.

If customer is currently working with a competitor (IBM, Oracle, SAP, Sybase), develop a strategy that articulates the value of independent data integration and data quality software to meet enterprise needs.


I D E N T I F Y Q U A L I F Y Selling Informatica into Master Data Management Projects

Master Data Management

Master Data Management (MDM)A set of processes, technologies, and business policies that collect, match, reconcile, cleanse, persist, relate, and distribute master data to and from applications, 3rd party data sources, and end users. Sometimes referred to as Customer Data Integration (CDI), Product Information Management (PIM), and Reference Data Management.

Informatica ProvidesMaster Data Management software that meets data integration, synchronization,

quality, and identity matching needs across all applications (ERP, CRM, legacy, etc.)

Identifying OpportunitiesBusiness operations impaired by poor data quality and accessibility issuesInability to access, profile, integrate, and synchronize data among systemsInability to cleanse and enrich data as it moves between systemsInaccurate identity matches and key business attributes (e.g., customer,

partner, etc.)

Inconsistent, inaccurate, and duplicate data across business applicationsHigh error rate in regulatory reporting

Qualifying OpportunitiesBusiness performance is sufferingHigh development costsHigh marketing spend, low results Missed cross-sell or up-sell opportunities Poor customer serviceLosing competitive advantage in the market placeFailed regulatory audits resulting in increased fines and penalties

Buyers and InfluencersBusiness Managers and departments focused on implementation of an MDM application (home-grown, IBM, SAP, Oracle, Siperian, Initiate, etc.). Specifically, IT managers responsible for database systems, and senior executives down to analysts within Sales, Marketing, Finance, Supply Chain Management, and Compliance.

High Value QuestionsAre you building or purchasing an MDM solution?How are you identifying the MDM solution and what applications does it need

to support?

How do you plan to access, understand, and integrate data from the source systems?

What systems will require operational or real-time integration and synchronization?

How do you cleanse and enrich poor quality data?How confident are you in the quality and completeness of the data in your

source systems?

Where people are involved, how do you plan to accurately match identities?



Master Data Management

Top Competitors in Master Data ManagementCompetitor Customer Perception Risk

Hand-coding IT resources believe they can write their own interfaces and data quality rules

Customers experience difficulties and delays adapting the MDM system to meet new business requirements or expand to incorporate data from other systems

IBM, Oracle and SAP

The data integration and data quality software from these application vendors will meet their needs

Customer does not consider the limitations of these vendor supplied technologies. While they may work well with other applications supplied by this vendor, they do not work well with the customers current technology investments.

EAI Software EAI software used for other application integration projects has worked fine so it will work on MDM projects

System does not scale to meet data loads; unable to apply complex transformation logic; no integrated data quality capabilities

Key CustomersCustomer and Product Information Management System (SAP MDM)

Customer Data Integration (Siebel UCM)

Employee Hub (developed in house)

PositioningIf customer is currently working with our MDM partners (Siperian, Initiate),

contact the partner to explore opportunities to collaborate.

If customer is currently working with a competitor (IBM, SAP, Oracle), develop a strategy that articulates the value of independent data integration and data quality software.

If customer is building their own master data management solution, position Informaticas Data Integration, Data Quality, and Identity Resolution software to save money, reduce product risk, and improve the overall quality of the MDM application.


I D E N T I F Y Q U A L I F Y Selling Informatica into Operational Data Integration Projects

Operational Data Integration

Operational Data Integration The integration and leveraging of data across enterprise applications or other critical production systems for operational use.

Data Replication Maintaining a copy of one systems data on another system, usually done in one direction

Data Synchronization Maintaining data consistency and integrity between two systems either synchronously or asynchronously

Data Integration Hub A system which synchronizes data in a one-to-many or many-to-many method in order to maintain consistent and accurate data across applications

Informatica ProvidesAccess and integration of data from any source, format or latency needOrchestration capabilities for automating data transformation and integration

processes

Integrated Data Quality solution for cleansing dataChange Data Capture (CDC) to ensure most current data is captured

Identifying OpportunitiesOrganizations in highly competitive, information-centric marketsNeed to move data from/to/between systems crossing corporate firewall, while

ensuring data integrity

Implementing new applications that share data with other systemsHigh use legacy systems (i.e., mainframes) or high-volume production systemsNeed to manage integration sprawl Using multiple tools for integration projectsIncreasing data complexity and data volumes (2X every 18 months by most

accounts)

Application migration and consolidation projects resulting from mergers and acquisitions

Qualifying OpportunitiesInconsistent, incorrect, or out of date data impacting business users, customers,

or suppliers

Hand-coding point-to-point integration interfaces is error prone, inflexible, cannot be reused, costly to maintain

Investigating Operational Data Store (ODS) to improve the accessibility of data in production systems

Looking to reduce on-going IT operational costsEAI implementation more complex and lengthier than expected

Buyers and InfluencersCIOs, Directors and VPs of Applications, Program Management Office (PMO)

leaders, Enterprise Architects, Application Architects, Application Project Managers, Line of Business Managers

High Value QuestionsHow do you currently back-up and replicate data from transactional systems?How do you support real-time information needs? How confident are you in the data consistency and accuracy across your

applications?

How would your business users rate the timeliness and accuracy of the data required to serve their operations?



Operational Data Integration

Top Competitors in Operational Data IntegrationCompetitor Customer perception value Risk

Hand-coding No software, low cost way of integrating

Specialized resources required to maintain (complex and expensive)

Project at risk if rapid change is required to support new business needs

IBM Broad range of products to address operational integration needs (WebSphere, InfoSphere, DataMirror)

Confusing and overlapping products

High maintenance costsProducts may not work together

as expected

At risk for becoming captive to IBM (services, hardware, software)

EAI Vendors Traditional integration approach for many customers

Lacking key data processing abilities: batch data movement, change data capture, complex transformations, data cleansing and enrichment, data and metadata traceability

Very difficult and lengthy implementation

GoldenGate Data Replication market leader

Limited to Data Replication, no transformation capabilities

Custom coding required to work with most other integration technologies

Key CustomersReplication BNSF, MAAF

Synchronization Daewoo Electronics, Deutsche Bank, CEMEX

Data Integration Hub Virgin Media, LinkShare, KPN

Positioning Use the table below to correctly position the elements of Informaticas Operational Data Integration

Operational Data IntegrationData Replication

Data Synchronization

Data Integration Hub

Straight copy with no transformation 4

Continuous data movement 4 4 4Format conversion 4 4Data transformation to fit target 4 4Data sharing across multiple applications 4

Orchestration of data integration tasks 4


I D E N T I F Y Q U A L I F Y Selling Informatica into Data Migration and Consolidation Projects

Data Migration and Consolidation

Data Migration and Data ConsolidationData Migration moving data from an old technology platform to a new

platform (e.g., old hardware to new hardware or old application to new application) typically motivated by pressing line of business requirements

Data Consolidation moving data from multiple systems to a single or centralized system (e.g., combining systems after an acquisition) for the purpose of reducing IT cost

Informatica ProvidesA proven methodology for data migration projects (Velocity)A complete set of tools to profile data, define and communicate data

definitions, and cleanse, migrate, and synchronize data as required

A proven network of Partner and Professional Services to assist customersIdentifying Opportunities

Recognize the need for a planned data migration and looking to implement best practices

No data migration strategy in place or relying on hand-coded, one-off interfaces to move the data

Do not recognize data quality issues as part of the processQualifying Opportunities

Current or recently completed projects where unplanned data migration efforts resulted in excessive costs and delays

Project teams actively seeking to further reduce project costs, improve delivery schedules, and provide greater value to the business

Current economic conditions impose heightened budget constraints

Target ProspectsImplementing, updating, or consolidating enterprise applications (e.g., CRM,

ERP, HR, SCM, MDM)

Currently or recently involved in mergers or acquisitionsInvesting in legacy modernization efforts (i.e., mainframe retirement)

Buyers and InfluencersBuyers and decision makers CIO, Director, VP of Applications, Program

Management Leader

Influencers and approvers Architect, Project Manager, Developer, and System Integrator

High Value QuestionsHow prepared are you to integrate data from additional, unforeseen sources?Tell me about your past experiences with data migration projects.How does the team plan to undertake the data migration effort? What consideration have you given to data quality? What would be the impact of project delays (cost to the project team, costs of

running legacy systems, impacts to the business)?



Data Migration and Consolidation

Top Competitors in Data Migration and ConsolidationCompetitor Customer Perception Risk

Hand-coding

Data migration is a one-time event, and it is simple enough to hand-code the interfaces and discard them

No standard data migration methodology to mitigate risk and adapt to unforeseen needs that always occur as a project matures

Ongoing synchronization needs are realized at the end of the projects; the hand-code is not suitable for production use

Business users complain about the quality of the new system and resist adoption; business benefits are not realized

IBM One stop shop for services, software and hardware

Customer exposed to higher services costs and tools that are not built for data migration projects

As problems arise, customers best option is to buy more IBM

SAP/ Business Objects

SAP Services know their SAP target application/s the best

SAP Services only know SAP and the customer remains responsible for educating SAP on their source systems

Mappings and other objects are not reusable on other, non-SAP projects

Key CustomersKey customers using Informatica for data migration and consolidation

Cemex realized $MM in ROI through data consolidation of global ERP system http://www.cemex.co.uk/

ACH Foods reduced data migration project costs by 50% using Informatica methodology and tools http://www.achfood.com/

Aircelle reduced data migration project costs by 40% while improving data quality http://www.aircelle.com/

PositioningPosition Informatica for data migration and consolidation projects as a tool

to guard against project delays, budget over-runs, failing to meet business expectations, and potential costs associated with extending the life of legacy systems

Migration projects position Informatica to support business development goals

Consolidation projects position Informatica as a cost savings tool


I D E N T I F Y Q U A L I F Y

Data QualityData Quality processes and rules are used to implement and manage enterprise-wide data quality initiatives including profiling, name-and-address cleansing, standardization, matching, house-holding, consolidation, enrichment and monitoring.

Informatica Provides

Data profiling software to assess project risk identify data issues within sources, measure data quality, and identify all data attributes which need to be cleansed

Data quality software cleanses and enriches the data Dashboards and reports provide ongoing monitoring and management of data

quality levels

Tools allow the business to manage exceptionsSupport for all master data types enabling customers to use one solution for all

their data quality needs (customer, supplier, product, asset, financial data types)

Identifying Opportunities

Absence of tools and processes to identify the extent of data quality issues in their systems and resolve them quickly

Duplicate, incorrect, or missing data creates lack of confidence in use of data for business decisions

Acknowledges hand-coding data quality rules is difficult, time consuming, non-reusable, expensive, and inflexible

Qualifying Opportunities

Exposed to business risk, lost revenues, or profits due to data quality issuesSeeking to reduce costs by rationalizing customers, products, or suppliersCustomer Service organizations experiencing problems related to incorrect or

incomplete customer data

Sales or Marketing organizations investing in customer cross-sell/up-sell initiatives

Implementing or building an MDM solutionHas experienced or is exposed to regulatory fines due to late or poor quality

reports

Target Prospects

Focused on Data Governance initiativesInvolved in or have gone through mergers or acquisitionsLooking to improve customer interactions and sales effortsLooking to rationalize products, suppliers, or partnersUndertaking data migration or data consolidation projects

Buyers and Influencers

Influencer: Line of Business ExecutivesBuyers and decision makers: CIOs, Sr. IT Executives, Data Analysts and

Stewards

Business Leaders responsible for compliance or regulatory reports

High Value Questions

What part of the organization has been impacted the most due to poor data quality?

How do you monitor and manage data quality across your organization today? How do you handle data quality issues today?When you generate reports for internal, regulatory, or compliance requirements,

how much time is spent re-validating and correcting the data? How has this impacted your submissions?

Selling Informatica into Data Quality ProjectsData Quality


I D E N T I F Y Q U A L I F Y

Top Competitors in Data Quality

Competitor Customer Perception Risk

Hand-coding Easy to do, no software license costs

Hand-coding data quality rules is time consuming, inflexible, and difficult to change

No ongoing monitoring or reporting of data quality levels

IBM Single provider of Software, Services, and Hardware

Few skilled resources outside of IBM Services, locking the customers into IBMs Services and rates

Limited data quality outside data warehousing

SAS Dataflux

Easy to use, business- oriented data quality tool

Single provider of BI, DI, DQ and ERP Applications

SAP/ Business Objects

SAP Services know their SAP target application/s the best

Questionable experience beyond Name and Address, and data warehousing efforts

Lost top development and DQ resources after SAP acquisition, exposing customer to risks due to first time effort for technology and services personnel

Key CustomersKey customers using Informatica for Data Quality

Bank of America avoided an estimated $20M in regulatory penalties (Data Explorer, Data Quality)

Banco Nacional de Costa Rica avoided $1.5M in annual IT costs (Data Explorer)

Motorola reduced duplicate customer records, direct savings of $320K per year (Data Quality)

PositioningPosition Informatica Data Quality as the highest performance, most accurate and flexible (supports all master data types) product available in the market. Informatica Data Quality uniquely enables business and IT collaboration which is critical for all data quality projects. Seamlessly integrated with PowerCenter, Informatica Data Quality can operate either as part of Informaticas unified platform or in a stand-alone environment.

Competing and PositioningData Quality

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IQCards Data Warehousing Identify Qualify