Get documents about "Informatica Workflows
Description
Informatica Workflows document sample
Document Sample
Assessment Date: 7/13/2011
Data Governance: Data Integration Technology Readiness Self-Assessment
Step 1 Within each of the 6 major categories, please enter the % priority weighting for each Data Governance
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
1. Data Accessibility: Provide Access to All Data Types and Formats
How do you integrate different types of data, Our data integration tool is primarily for The platform supports access to both We have one common tool that
including mainframe, structured, unstructured integrating relational data. For other structure and semi-structured formats. supports all these data types in an
1 Supported Data Types (e.g., Word documents and spreadsheets), data types, like mainframe, we use We have manual or hand-coded automated fashion, with common 30% 1 0.3
XML and EDI, relational, application, and scripts and hand-code to get at the mechanisms to access unstructured metadata.
message queue data? data. data.
How do you connect to specific applications, For a lot of our systems, we write Our tool has pre-built connectivity for Our platform has pre-built connectivity
systems, and data sources? custom code to establish connectivity. common systems such as relational to a wide variety of systems, including
databases, SAP, Siebel, and multiple mainframe formats,
2 Pre-built Connectivity BusinessObjects. messaging systems, and numerous 30% 3 0.9
applications.
How do you validate both input and output Our current system does not have data The platform validates and reports on The platform validates input/output
Input/Output Data data from all data sources and targets? input/output validation capability. the input and output data. data, and aids in the development of
3 25% 3 0.75
Validation metadata model.
How do you detect and record data access We log events in the various systems Our data integration tool provides Our data integration tool provides
events including exceptions and failures? and inspect the logs as needed. basic failed session statistics and error failed session statistics, error
4 Event Logging messages. messages, metadata statistics, and 5% 3 0.15
lineage that helps assess the
exceptions and failures.
How do you provide federated access to data? We don't federate data access; we We have a tool that can provide We have one common tool that
physically move or replicate data as federated access to data in-memory. provides both physical and
5 Federated Access needed. It's separate from our physical data virtual/federated access to data. 5% 1 0.05
integration tool.
How do you move data across firewalls, Most of our data movement is within Our tool can move data through Our tool supports secure, highly
irrespective of geographic or functional our own firewalls. firewalls, but security and performance performant data movement across
6 Cross-firewall Access boundaries? are not as good as they should be. firewalls. 5% 1 0.05
100% 2.2
Created by Informatica Corporation Page 1 Rev June 6, 2006
Assessment Date: 7/13/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
2. Data Availability: Deliver Data Reliably, When and Where Needed
How do you maximize the rate at which your We manually tune our processing and Our tool supports partitioning and Our tool makes it easy to configure
system can process data? workflows to try to increase parallelism, but it requires a lot of multiple performance enhancement
7 Throughput throughput. We can't easily support manual coding and the configuration is options including pipelining, dynamic 10% 3 0.3
partitioning. very cumbersome. partitioning, and smart parallelism.
How do you scale your system to meet We add more hardware to support Our tool takes advantage of 64-bit Our tool takes advantage of 64-bit,
growing demands? growing data volumes, but we're processing to improve scalability. thread-based parallel processing and
8 Scalability getting diminishing returns. grid deployment for near-linear 10% 3 0.3
scalability.
How do you manage failover and recovery We follow a process guideline for Our tool has automatic failover and Our tool has automatic failover and
should your system go down? failover scenarios. Recovery is done recovery capabilities. recovery capabilities, including grid
Automatic Failover and manually. deployments, and provides graphical
9 30% 3 0.9
Recovery status on the grid and other key
indicators.
How do you ensure continuous availability of We do our best to ensure our Our tool supports high availability Our tool enables us to easily configure
your data? hardware and software stay up and using multiple nodes, but it's very time- high availability including built-in
10 High Availability running. We aren't really configured for consuming and difficult to configure resiliency, automatic failover and 30% 3 0.9
true high availability across multiple and manage. recovery, and multi-node/grid
nodes on a grid. deployment.
How do you configure your system to address We do most of our processing on a We have different tools that support We have one common tool which
data with different volume and timing scheduled batch basis. batch vs. message-based delivery. allows data volumes and latencies to
requirements-- from event-driven, message- Our processes have to be recoded be configured to meet business needs,
11 Volume and Timing 15% 3 0.45
based delivery to net-changed to scheduled, and/or recompiled to work in different without any recoding.
large-volume batch delivery? latency modes.
How do you configure your system to deliver We have to recode to handle different We have different tools that support We have one tool that supports all
data via different protocols and methods, protocols and methods based on different data delivery protocols and types of delivery protocols and
including loading physical databases for SQL- project needs. methods. methods via configuration, without
Breadth of Delivery based access, creating virtual data views (EII), requiring recoding.
12 5% 3 0.15
Protocols publishing to a message bus or queue, and
publishing Web Services?
100% 3
Created by Informatica Corporation Page 2 Rev June 6, 2006
Assessment Date: 7/13/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
3. Data Quality: Ensure Accurate, Validated Data
How do you currently profile and understand We run SQL queries and/or scripts We use a dedicated tool to profile data We have a tool to profile source data
13 Profiling your data? against the data on an ad hoc basis. sources and detect potential data that integrates with our data quality 40% 3 1.2
quality issues. remediation and monitoring tools, and
How do you monitor and measure the quality We only check data quality on an ad our monitor key data quality
We have established a few key data We data integration tools. metrics on
Monitoring and of your data? hoc basis. We don't us formal metrics quality metrics, but they're not an ongoing basis and receive alerts on
14 or conduct ongoing monitoring. systematically monitored. items that fall out of acceptable 20% 1 0.2
Measurement
ranges.
How do you cleanse your data and remediate Each time a data quality issue is We have a data quality tool where we We have an automatic capability for
data quality issues, such as accuracy, raised, we address it on a one-off can define business rules to address remediating data quality issues, which
15 Cleansing and Remediation completeness, conformity, integrity, basis, usually via hand-coding or quality issues. also provides historical statistics to 10% 1 0.1
consistency, and duplication? manual scrubbing of data. help root cause analysis.
What types of data are supported by your data We do not have specific data quality Our data quality tool is primarily All of our key data types (e.g.,
quality tools? tools. We address data quality on an focused on name and address data. customer, product/service, financial,
16 Breadth of Data ad hoc basis. employee, etc.) are supported by our 10% 3 0.3
data quality tool.
How easy is it for your business analysts, data The business folks have to ask IT to We have a data quality tool, but it's Our data quality tool provides an easy-
stewards, and other business-oriented users run queries for them, and they rely on really designed for IT users. Our to-use interface to enable both
to understand and address data quality spreadsheets and other manual tools business users can't work with it. business and IT users to visualize and
17 Ease of Use issues? to define data quality business rules. address data quality issues. 15% 5 0.75
How do ensure that your data quality logic and We define business rules in We have a data quality tool that The metadata for our data quality
business rules can be captured as metadata spreadsheets and other manual generates metadata, but it's siloed processes is captured automatically
18 Integrated Metadata and shared with other data integration documents, so there's no easy way to from our broader data integration and is seamlessly incorporated as part 5% 3 0.15
processes? share and reuse those rules. framework and other metadata. of our overall data integration lifecycle.
100% 2.7
Created by Informatica Corporation Page 3 Rev June 6, 2006
Assessment Date: 7/13/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
4. Data Consistency: Reconcile Data Values, Structure, and Semantics
How do you validate your data models and We manually review documentation We use a design tool to validate our We use a metadata-driven, integrated
relationships? and run queries to validate our data design and mapping. design and mapping tool that
19 Validation model. automatically validates the data model 20% 3 0.6
on-the-fly.
How do you transform data to reconcile both We hand-code scripts to transform We have a tool with a variety of pre- We have a tool with robust
syntactic and semantic variances across data to resolve syntactic differences built transformations that we can transformation capabilities that
different data structures? across systems. leverage. We largely focus on addresses not only syntactic issues,
20 Transformation syntactic and structural issues. but also structural and semantic 20% 5 1
variances across different systems.
How do you manage your business rules and We implement scripts and other types Our data integration tool generates We use a metadata-driven data
workflows at the logical and the physical of coding to apply business rules, so code to create data integration rules integration tool that deals with all
Logical Design and levels? the logical and the physical design are and manage workflows. design and business rules at the
21 15% 5 0.75
Workflow one in the same. logical level, abstracting them from the
physical layer.
How do you share and reuse business rules, We hand-code scripts to deal with data Our tool creates transformation We have one tool that captures all our
workflows, etc? integration, so it's not easy to share mappings and workflows that can be data integration and data quality logic
22 Reusability the code. reused. and workflows as metadata and 10% 1 0.1
enables sharing at both local and
global levels.
How do you catalog, search and filter Our business rules and relationships We have a basic metadata repository We have a metadata-driven tool so we
business rules, entity relationships, and are scattered in different tools and where we try to centralize rules, can easily search, filter, define, and
23 Cataloging domain values in your data integration systems. There is no centralized relationships, etc. modify data dictionaries and business 15% 5 0.75
environment? location for them. rules.
How do you synchronize data across multiple We have built point-to-point integration We use EAI and messaging We use a combination of data
systems to ensure consistency? between systems to keep data in technology to keep data synchronized integration and EAI/messaging
synch. in real time. technologies to ensure consistency in
24 Synchronization 20% 1 0.2
both context and meaning, as well as
data values.
100% 3.4
Created by Informatica Corporation Page 4 Rev June 6, 2006
Assessment Date: 7/13/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
5. Data Auditability: Establish Audit Trails and Internal Data Controls
How do you show the lineage of data across We review documentation and We have a metadata repository that We have a metadata management tool
multiple systems and applications, including interview the different system owners helps infer data relationships across that graphically displays data lineage,
25 Lineage both backward and forward tracking? to try to figure out the data lineage. systems and applications. with drill-down capabilities. 30% 5 1.5
How do you predict and document the impact We review documentation and Our tool provides metadata and Our tool provides reports on port
of changes across applications and systems? interview the different system owners metadata extension usage reports that details, metadata extensions and
26 Impact Assessment to try to figure out the impact of specify high-level usage across usage, and mapping dependencies 20% 5 1
changes, and then we document them. connected systems. across connected systems.
How do you design and manage workflows for We rely on email and shared file Our tool has basic data integration Our tool has robust workflow
your data integration processes? folders to manage our workflows. workflow design and management orchestration capabilities including
capabilities. support for grid deployments and
27 Workflow 20% 3 0.6
global, cross-team collaboration.
How do you monitor operational statistics and We review the logs and share process Our tool provides a dashboard with a Our tool provides a dashboard with the
28 Dashboard provide visibility into exceptions? statistics across the team via manually- high-level summary of workflows, ability to easily drill down into the 10% 3 0.3
generated reports. processes and status. details.
How do you detect invalid mappings and We run tests to detect errors using a We have a test environment within our We have an integrated test
failed sessions? separate tool. data integration tool to detect mapping environment that helps identify the root
29 Testing and session errors. We then run causes of invalid mapping and session 5% 3 0.15
queries for root cause analysis. errors as part of our data integration
tool.
How do you control and manage different We check dates and timestamps on We rely on a software change Our data integration tool has robust,
versions of your rules and workflows? our data integration code and management tool like Rational to granular version management and
30 Version Control workflows to track versions. manage different versions generated deployment capabilities built in. 15% 1 0.15
by our data integration tool.
100% 3.7
Created by Informatica Corporation Page 5 Rev June 6, 2006
Assessment Date: 7/13/2011
Readiness Score Weighted
Category Category Name Question % Priority Raw Score
Score
1 3 5
6. Data Security: Secure Access to Data
How do you classify data based on its Each group makes its own decisions The tool provides a mechanism to The tool supports an enterprise-wide
sensitivity, priority, and usage patterns? about how and whether they classify classify information by data type, strategy on information classification,
31 Data Classification their data, so there's no common priority, usage, locations and user enabling data to be easily grouped and 15% 3 0.45
framework. access within specific business areas. classified.
How do you keep duties or areas of We assign different areas of The tool has a well-defined workflow The tool enables granular segregation
responsibility separate for different users to responsibility to different users, but it's manager and admin functions to of duties, as well as reporting on
32 Segregation of Duty reduce the risk of unauthorized modifications pretty high level and there's no built-in separate tasks for different users. interdependencies of different tasks. 15% 1 0.15
or misuse of data? way to enforce it.
How do you restrict and enforce controls over We assign different privileges to The tool supports user- and role-based The tool has robust privilege
the use of features and access to data by different users, but it's not very privilege management to manage management capabilities for managing
different users and administrators? granular and there's no built-in way to access to data and key features. and reporting on granular privileges
33 Privilege Management enforce it. such as copy object, maintain labels, 25% 3 0.75
and change object status.
How do you support user authentication The tool has an independent user The tool integrates with LDAP to The tool integrates tightly with LDAP
34 Client Authentication against external lightweight directory access management service and does not ensure appropriate user and has a repository to track the real- 15% 3 0.45
protocol (LDAP)? integrate with LDAP. authentication. time authentication status.
How do you manage Web Services security We're not yet addressing Web Our tool supports SSL and certificate- Our tool supports the latest Web
for data integration? Services security. based Web Service security. Services security standards at both the
35 Web Services Security message and transport layers for 20% 3 0.6
authentication, encryption and
authorization.
How do you securely transmit data? We currently do not transport data in Our tool supports transmission of data Our tool supports encryption and
encrypted format. in encrypted format. secures synchronization across
36 Encryption firewalls leveraging built-in security 10% 5 0.5
with encryption and compression.
100% 2.9
TOTAL SCORE 17.9
OUT OF A MAXIMUM 30
Created by Informatica Corporation Page 6 Rev June 6, 2006
Assessment Date: 7/13/2011
RESULTS of Data Governance: Data Integration Technology Readiness Self-Assessment
Attribute
Attribute Rating Interpretation & Recommendation
Data Accessibility 2.2 You scored low in Data Accessibility, which means that users may have difficulty accessing all
the data they need. You should evaluate more automated approaches to accessing different
types of data. Specifically, consider PowerExchange and PowerCenter Connect Options.
Data Availability 3.0 You scored medium in Data Availability, so much of your data is typically available as needed
by users. However, you may want to evaluate enhancements such as ensuring High
Availability of your critical data, or ensuring that different latencies and volumes are supported
in one common platform. Specifically, you might consider implementing PowerCenter High
Availability Option, or taking advantage of database processing capacity with Pushdown
Optimization.
Data Quality 2.7 You scored low in Data Quality, which means that users may have little confidence in the data,
and your business may be experiencing avoidable errors and duplications. You should
evaluate ways to address data quality issues in a programmatic fashion, leveraging data
quality tools to help automate the process. Specifically, you can start by assessing your
current state with Informatica Data Explorer, and implementing a focused program such as
name and address cleansing with Data Cleanse and Match Option.
Data Consistency 3.4 You scored medium in Data Consistency, so you have likely resolved basic consistency issues
such as syntactic and structural differences between systems. To continue to improve
consistency, you should ensure that you are using a metadata-centric approach, to address
semantic issues and to ensure consistency by capturing business logic in a common glossary
or repository. Specifically, you may consider PowerCenter Advanced Edition, which includes
Metadata Manager for enhanced metadata capabilities.
Data Auditability 3.7 You scored medium in Data Auditability, so you have a good start on ensuring that your data is
well documented and properly controlled. You should continue to leverage metadata for data
lineage and enable impact analysis. You should also look to tools that enable cross-enterprise
visibility and collaboration, with robust dashboard and version management capabilities. You
can take advantage of the Metadata Manager, Data Analyzer and Team-based Development
capabilities in PowerCenter Advanced Edition.
Data Security 2.9 You scored low in Data Security, which means your data has a high risk of being
compromised. You should ensure that you are using a tool that manages and secures access
to your data, and appropriately encrypts the data. You can consider PowerCenter which has
built-in data encryption and fine-grained access control capabilities.
OVERALL 17.9 Overall, you scored low on the readiness of your data integration infrastructure to support your
data governance program. It will be difficult to ensure the ongoing success of your governance
program without additional investment in your infrastructure. You should evaluate your data
governance goals and priorities, and look to tools to help automate data integration to ensure
key data attributes such as quality, availability, and auditability.
Created by Informatica Corporation Page 7 Rev June 6, 2006
Assessment Date: 7/13/2011
RESULTS of Data Governance: Data Integration Technology Readiness Self-Assessment
Data
Accessibility
4
3
Data Security 2 Data Availability
1
0
Data
Data Quality
Auditability
Data
Consistency
Created by Informatica Corporation Page 8 Rev June 6, 2006
Data Governance: Business Value of Data
Step Go to the "Value-Revenue", "Value-Cost" and "Value-Risk" tabs for ideas on ome typical ways in which data
1 impacts business value.
Step For the value areas that are relevant to you, identify the appropriate key business metric(s) for your
2 organization and estimate the impact of improving data integration and governance on those metrics. Feel
free to change the categories to tailor them to your organization.
Step Use this sheet to summarize the key metrics and estimated impact, and to share with your organization for
3 further discussions.
Business Value Category Explanation Key Metrics Estimated Impact
A. INCREASE REVENUE
1 New Customer Acquisition Lower the costs of acquiring new customers
2 Cross-Sell / Upsell Increase penetration and sales within existing customers
3 Sales and Channel Management Increase sales productivity, and improve visibility into demand
4 New Product / Service Delivery Accelerate new product/service introductions, and improve "hit
rate" of new offerings
5 Pricing / Promotions Set pricing and promotions to stimulate demand while improving
margins
B. LOWER COSTS
6 Supply Chain Management Lower procurement costs, increase supply chain visibility, and
improve inventory management
7 Production & Service Delivery Lower the costs to manufacture products and/or deliver services
8 Logistics & Distribution Lower distribution costs and improve visibility into distribution
chain
9 Invoicing, Collections and Fraud Improve invoicing and collections efficiency,and detect/prevent
Prevention fraud
10 Financial Management Streamline financial management and reporting
C. MANAGE RISK
11 Compliance (e.g. SEC/SOX/Basel II/ Prevent compliance outages to avoid investigations, penalties,
PCI) Risk and negative impact on brand
12 Financial/Asset Risk Management Improve risk management of key assets, including financial,
commodity, energy or capital assets
13 Business Continuity/ Disaster Reduce downtime and lost business, prevent loss of key data,
Recovery Risk and lower recovery costs
39d1d92a-7c18-45c3-b9af-3a1a08111d57.xls Value of Data Page 9
Examples of Key Capabilities by Data Attribute
A. INCREASE REVENUE Explanation Typical metrics Data Integration Examples Quality Consistency Auditability Security Accessibility Availability
1 New Customer Lower the costs of - cost per new - Marketing analytics Customer targeting Sharing of correlated Predict the impact of Secure access to Cross-firewall Accelerated delivery
Acquisition acquiring new customer acquisition - Customer data quality and on-boarding customer data with changes, e.g. valuable customer access to third party of sales lead data to
customers - cost per lead improvement based on accurate sales and third party switching credit lead, financial and customer data e.g. appropriate channels
- # new customers - Integration of 3rd party data customer/prospect/ channels to reduce bureaus or other information credit bureaus,
acquired/month per (from credit bureaus, directory market data channel conflict and implementing a new address directories,
sales rep or per services, salesforce.com, etc.) duplication marketing sytem list brokers, etc.
office/store
2 Cross-Sell / Upsell Increase penetration - % cross-sell rate - Single view of customer across Accurate, complete, Single view of Improve governance Customer data Opportunity Real-time customer
and sales within - # products/customer all products, channels de-duplicated customer reconciling of customer master privacy and security identification with analytics enabling
existing customers - % share of wallet - Marketing analytics & customer customer data to differences in data by maintaining assurance to protect integrated access to tailored cross-selling
- customer lifetime segmentation create single view business definitions & visibility into definition customers and CRM, SFA, ERP and at customer
value - Customer lifetime value structures across of and changes to comply with others touchpoints
analysis groups data regulations
3 Sales and Channel Increase sales - sales per rep or per - Sales/agent productivity Completeness and Alignment of Provide traceability Secure access for Incorporation of Continuous
Management productivity, and employee dashboard validity of sales channel/sales for demand and partners/distributors to revenue data, availability of lead,
improve visibility into - close rate - Sales & demand analytics activity, pipeline and incentives based on revenue reports share sensitive internal or external pipeline and revenue
demand - revenue per - Customer master data demand data consistent sales through data lineage demand and revenue SFA data, and data in data to sales,
transaction integration productivitydata information forecast partners and channels
- Demand chain synchronization spreadsheets
4 New Product / Accelerate new - # new products - Data sharing across design, Accurate, de- Consistent Ensuring compliance Improved Access to data in both Distributed, round-
Service Delivery product/service launched/year development, production and duplicated product application of with product collaboration on applications/ the-clock
introductions, and - new product/service marketing/sales teams design and product and service regulations through prototyping, testing systems as well as environment for
improve "hit rate" of launch time - Data sharing with 3rd parties development data definitions and version control and and piloting through design documents collaborative data
new offerings - new product/service e.g. contract manufactuers, across functional and descriptions across view of lineage secure data sharing sharing
adoption rate channels, marketing agencies, geographical functions and with
etc. boundaries partners
5 Pricing / Promotions Set pricing and - margins - Cross-geography/cross- Complete, accurate Global/cross- Rationalization of Segregation of Holistic pricing Real-time pricing data
promotions to - profitability per channel pricing visibility product pricing and functional pricing and improved differential pricing and management based to enable constant
stimulate demand segment - Differential pricing analysis and discount/ profitability reconciliation of record keeping for promotions data for on data from monitoring & on-the-
while improving - cost-per-impression, tracking data pricing and price changes different customers, applications, fly pricing adjustments
margins cost-per-action - Promotions effectiveness promotions data channels, etc. including pricing based on demand
analysis spreadsheets
39d1d92a-7c18-45c3-b9af-3a1a08111d57.xls Value- Revenue Page 10
Examples of Key Capabilities by Data Attribute
B. LOWER COSTS Explanation Typical metrics Data Integration Examples Quality Consistency Auditability Security Accessibility Availability
6 Supply Chain Lower procurement - purchasing discounts - product master data De-duplicated, Reconciled view of Improve governance Encrypted data Access to EDI and Real-time supply chain
Management costs, increase supply - inventory turns integration complete view of purchases across all of product master data exchange with unstructured data management, aligned
chain visibility, and - quote-to-cash cycle - demand analysis products and materials
suppliers to improve by maintaining visibility extended network of (typically in with just-in-time
improve inventory time - cross-supplier purchasing data to improve supply
purchasing into definition of and suppliers/distributors Excel/Word) from production models
management - demand forecast history chain efficiency effectiveness & changes to data suppliers/distributors
accuracy negotiation stance
7 Production & Lower the costs to - production cycle times - cross-enterprise inventory Improved planning and Reconciled product Ensure compliance Role-based access to Integrated access to Near real-time
Service Delivery manufacture products - cost per unit (product) rollup product management and materials master with production critical operational EDI, MRP, SCM and production and
and/or deliver services - cost per transaction - scheduling and production based on accurate data to ensure regulations through data, bsaed on other data transaction data to
(service) synchronization materials, inventory accurate inventory and version control and business need streamline operations
- straight-through- and order data production planning view of lineage
processing rate
8 Logistics & Lower distribution costs - distribution costs per - integration with 3rd party Reduction in logistics Consistent definition Predict the impact of Encrypted data Bi-directional Availability of order
Distribution and improve visibility into unit logistics management and and distribution errors across extended changes, e.g. flagging exchange with integration of data with status and delivery
distribution chain - average delivery times distribution partners with accurate, ecosystem of key data dependencies on a 3rd extended network of 3rd party logistics and data on a real-time, as-
- delivery date reliability validated data such as ship-to, party provider's data logistics partners, distribution partners needed basis
delivery information distributors and
customers
9 Invoicing, Improve invoicing and - # invoicing errors - invoicing/collections Reduced errors in Reconciliation of Detection/prevention of Secure customer Integration of Hourly or daily
Collections and collections efficiency,and - DSO (days sales reconciliation invoicing/billing to purchase orders to inefficiencies or fraud access to billing and historical customer availability of
Fraud Prevention detect/prevent fraud outstanding) - fraud detection accelerate collections invoices to payments though dashboard payment data data with third party reconciled invoicing
- % uncollectable across geographies, and alerts data to detect suspect and payments data
- % fraudulent organizational transactions and
transactions hierarchies prevent fraud
# Financial Streamline financial - End-of-quarter days to - Financial data Improved fidelity in Consistent Built-in audit trail on Segregated, secure Incorporation of On-demand
Management management and close warehouse/reporting financial management interpretation of chart financial reporting data access to sensitive spreadsheet data with availability of financial
reporting - Financial reporting - Financial reconciliation with accurate, of accounts across all to ensure financial data data from financial management data to
efficiency - Asset complete financial functions and transparency and management and business users
- Asset utlization rates management/tracking data geographies regulatory compliance reporting systems
39d1d92a-7c18-45c3-b9af-3a1a08111d57.xls Value- Cost Page 11
Examples of Key Capabilities by Data Attribute
C. MANAGE RISK Explanation Typical Metrics Data Integration Examples Quality Consistency Auditability Security Accessibility Availability
11 Compliance (e.g. Prevent compliance -# negative audit/inspection - Financial reporting Proactive reduction of Reconcile data Ensuring compliance Secured, encrypted Leverage compliance On-demand,
SEC/SOX/Basel II/ outages to avoid findings - Compliance monitoring & data conformity and being reported across on data integrity reporting data metrics tracked in continuous availability
PCI) Risk investigations, penalties, - probability of compliance reporting accuracy issues groups, functions to through version available to spreadsheets, along to reporting and
and negative impact on lapse through scoring and ensure consistency control and data authorized, with system-based monitoring systems
brand - cost of compliance lapses monitoring lineage designated personnel data
- audit/oversight costs
12 Financial/Asset Improve risk - errors & omissions - Risk management data Continuous data Validation of Visualize data Ease management Integrate financial and Real-time availability
Risk Management management of key - probability of loss warehouse quality monitoring to correlated data for relationships and oversight through risk management of key financial and
assets, including - expected loss - Reference data integration maintain fidelity on financial reporting and dependencies at access records and systems data with risk indicators for
financial, commodity, - safeguard and control costs - Scenario analysis financial data risk management both business and IT granular privilege spreadsheet-based ongoing monitoring &
energy or capital assets - Corporate performance level management data prevention
management
13 Business Reduce downtime and - mean time between failure - Resiliency and automatic Updated, de- Synchronized data Impact and Secure cross- Access to off- High availability and
Continuity/ Disaster lost business, prevent (MTBF) failover/recovery for all data duplicated data across primary and dependency firewall access for premise data to automatic
Recovery Risk loss of key data, and - mean time to recover integration processes reduces and backup systems analysis across operations from support failover/recovery to
lower recovery costs (MTTR) simplifies data multiple applications secondary data secondary/backup prevent or minimize
- recovery time objective storage and and systems for centers systems downtime
(RTO) management continuity and
- recover point objective requirements recovery planning
(RPO-- data loss)
39d1d92a-7c18-45c3-b9af-3a1a08111d57.xls Value- Risk Page 12
