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