Data Quality Assessment Whitepaper

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For most organizations, managing key information assets is more challenging than everespecially as your volume of data multiplies at an exponential rate.

Concern about data integrity exacerbates data management problems. Not trusting the accuracy of your organizations

expanding collection of information erodes end-user confidence in using the data. If your end-users perceive defects in

data quality, essential systems applicationssuch as customer relationship management (CRM), enterprise resource

planning (ERP), or business intelligence (BI)are likely to be underutilized, and thus fail to meet expectations.

Ultimately, the lack of use can erode your investments in these mission-critical applications.

One solution to solving data integrity issues is to ensure your organization has a good understanding of what the issues

are and how they affect your enterprises computing systems. To gain such understanding, many organizations use

data quality assessmentsgiving them a snapshot of data issues and identifying ways to begin correcting them. A data

quality assessment is the act of inspecting data, measuring data defects, analyzing the cause and impact of those

defects, and then reporting the results of the analysis to key stakeholders.

Conducting data quality assessments in your organization is a critical part of any Information Management (IM)

program. IM is a combination of strategy, practices, and open technologies for delivering trusted, integrated, and timely

information. SAP BusinessObjects IM products and services provide the most trusted foundation for business

decisions. In this overview of the SAP BusinessObjects Data Quality Assessment Methodology, we provide a high-level

discussion of the framework your organization can use to figure out how to begin a data quality assessment program.

We help you identify the individuals who need to be involved, and understand the types of issues those conducting the

assessment often face. When assessing our customer organizations, SAP BusinessObjects assessors employ our

complete, in-depth methodology which includes checklists, presentation models, and assessment strategies.

M A N A G E A S S E T S W I T H D A T A Q U A L I T Y A S S E S S M E N T S

D A T A Q U A L I T Y A S S E S S M E N T

METHODOLOGY FOR SUCCESSWHITEPAPER


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T H E D A T A Q U A L I T Y A S S E S S M E N T M E T H O D O L O G Y

THE SAP BUSINESSOBJECTS DATA QUALITY ASSESSMENT METHODOLOGY

The SAP BusinessObjects Data Quality Assessment Methodology is composed of four stages:

1. Pre-assessment planning

2.Conducting the data assessment

3. Presenting the assessment findings

4. Repeating the process

Each stage of the data quality assessment process includes a number of steps. Like any IT project, a data quality

assessment requires a certain amount of planning to ensure success. During the planning phase, an organization

establishes well-defined requirements for people involved in the assessment project.

STAGE 1: CREATING A PRE-ASSESSMENT PLAN

Establish Your Team

In the preplanning stage, you make decisions about personnel and project participation. As the scope of the project

begins to take shape, your key decision makers determine who in your organization is best able to supply the critical

insights and access to the data being studied. Typically, your assessment team would be composed of a project

manager, an assessor, subject matter experts (SMEs), IT systems support, and a database administrator (DBA) oranalyst who is responsible for maintaining the data. The assessor is the person responsible for actually performing the

physical assessment.

Sample the Data

To facilitate implementation of business rules and queries, your assessment team performs a review and

walkthrough of sample data with the key stakeholders. Whenever possible, its useful to share a sample set of

the problematic data with the assessment team in advancebefore the formal assessment takes place. This

preview allows your team to perform an initial evaluation of data structure, field composition, and business rule

structures aiding in the formal assessment. Additionally, reviewing sample data prior to the actual on-site

assessment allows your team the opportunity to uncover and identify data singularities and rules that need in-depth

examination during the assessment.

Dive Into Documentation

Because every data set has particular contexts, its important that assessment team members review any

documentation pertaining to the identified data sets. Any information that amplifies the data sets enlightening the

assessorswill speed the assessment process. A documentation review should include the review of any:

Data definitions

Data standards

Database schemas

Written policies and procedures

Written business rules and validation criteria

Identify Your Assessment Goals

Understanding how you define the success of an assessment project is a good precursor to the actualassessment itself. Answering questions like the following is a good place to start:

What are the business drivers behind your assessment? For example, is your organization seeking better data

for decision support, or is it preparing to build a new data warehouse?

What data quality problems do you perceive?

What assumptions or expectations does your organization have of the assessment?

Did a critical operational failure occur? If so, what were the conditions and symptoms?


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Establish Project Requirements

Interviewing key project stakeholders, consumers of the information, and custodians responsible for maintaining the

information provides important insights into identifying project requirements. Interviews help you determine which

specific data sets to assess, the business rules to measure against, and the relevant reports to generate.

Stakeholders can come from a variety of areas in your organization. Those with a great deal of customer contact help

provide an external view of data impacts, and those responsible for internal systems bring insights of how critical

processes are affected. Look to build a virtual team of stakeholders from sales and marketing, customer support,finance, and those responsible for delivering your product or service.

Define the Data Assessment Scope

Perhaps the most critical part of the assessment involves defining its scopethe amount and types of

data youll need to assess. Limiting the scope helps assessors deliver feedback to the organization quickly.

You can always perform multiple assessmentsespecially recommended if your organizations requirements span

broad segments of myriad data sets within the enterprise.

In defining the scope, your assessment team works with Business Objects to identify:

Specific databases, including location and platform

Specific tables within the databases

Specific columns within the tables

Once youve determined the scope and completed preplanning, you can begin a formal assessment on a

foundation of confidence.

STAGE 2: CONDUCTING THE DATA ASSESSMENT

To begin the formal data assessment, its important to set the context under which projects can be most

successful. The assessor performs the following analyses and tests on the data being studied:

Data profileincluding frequency distributions, uniqueness, and completeness tests

Column analysissingle-column validity tests

Referential integritytests for primary and foreign-key integrity

Business rules compliancecross-column, cross-table, and cross-database analysis

Also, depending on the projects scope, the assessor may evaluate specific aspects of the data set, such as the quality

of street addresses or the level of redundancy of records. The actual time it takes to conduct an assessment is highly

dependent on the amount and scope of data to be evaluated, along with the number and complexity of business rules

to be matched against the data. The assessment process involves building a data profile of the required tables and

columns, checking for referential integrity, and then building each of the required business rules. The assessment

continues until each validation and business rule has been compared against the data and the results stored in the

metadata repository. During this period, access to SMEs is key to tuning the business rules and reviewing intermediate

findings.

During the assessment, the assessor generally uses an assessment tool, like SAP BusinessObjects Data Insight,

which helps automate the process. The software establishes a baseline that can be repeated at regular intervals

helping you to understand progress made on quality initiatives at later dates. An assessment tool automates column

validation and assesses the business rules defined during the preassessment planning phase. The results of the tool-

generated queries will be saved in a metadata repository for use in preparing the assessment findings presentation.


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STAGE 3: PRESENTING THE ASSESSMENT FINDINGS

Once all tests and queries have been conducted, the assessor compiles the results and requests a preliminary review

by the SMEs. Once the SMEs have provided feedback, your team can prepare the final findings. Final findings typically

are reported via written reports and verbal presentations, as required.

Upon completing the data quality assessment, the project manager presents the findings to your key stakeholders.

Depending on your requirements and the assessments outcome, the presentation will include topics such as:

Examples of specific data defects

Anecdotes of the impact defects have on your organizations day-to-day business

Reports of domain measurements and analysis tests

A view of changing metrics over time

Recommendations for both data capture and process improvements

Suggestions for how to clean existing data elements

Often the findings from the assessment generate new questions about the data. Because youve kept scope size to a

minimum, you may identify additional data elements for investigation during final findings. This underscores the

importance of making data quality assessment practices repeatable and extensible to other data. Also, if you establish

an environment where you run business rule tests periodically, your organization can perform trend analyses over time.

STAGE 4: REPEATING THE PROCESS ON A REGULAR BASIS

Its important to note that a data quality assessment is not a one-time activity. Data ages and changes faster than most

organizations can keep up, and a continual monitoring and reporting process on key data elements is essential for

optimal operations management.


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Because data is ever-evolving, its important you establish a repeatable process for conducting data quality

assessments over time. An analysis of client and trading partner data reveals how dynamic your data really isand

how vulnerable it is to degradation. Data degradation occurs as clients move, get married, have children, or change

jobsor for any number of reasons beyond your organizations control. You might choose to phase out products

attributes or stock keeping unit (SKU) information, rebrand a product from a trading partner, or acquire new data via amerger or acquisitionany of these and similar actions and events affect your data.

Establishing a repeatable assessment program provides insight into how your data has evolved, performance against

business rules youve established, and how even single pieces of data can affect downstream processes. As part of an

overall BI program, repeatable data quality assessments can be a barometer of how your data assets are performing

for you.


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L E V E R A G E T H E P O W E R O F Y O U R I N F O R M A T I O N A S S E T S

A data quality assessment is just one piece of building a comprehensive data quality strategy for an organization. It

uncovers hidden and imperceptible problems early in the project lifecycle, when projects can be affected without fear of

complete project failure. The data quality assessment quantifies the number and type of defects found, along with

identifying the affected records. Quantifying and analyzing defects is critical to knowing where the highest priority data

quality problems exist allowing your organization to implement the appropriate processes and technology solutions,and leveraging the power of your information assets.

Our assessment methodology provides a framework for developing a self-contained and reusable data quality

assessment projectcomprising business rules, analysis, measurements, history, and reports about a particular

source. The project becomes a dashboard through which your data quality can be improved, and the improvements

measured over time.

ACCELERATE PERFORMANCE WITH BUSINESS INTELLIGENCE SOLUTIONS

Our industry-leading solutions are based on SAP BusinessObjects 3.0, the first and only BI platform to deliver a

complete set of BI capabilities. Our BI solutions embrace superior reporting, query, and analysis tools, performance

management, and data integration. SAP BusinessObjects makes it easy for you to track performance, understand corebusiness drivers, and manage your business to higher levels of performance. Key SAP BusinessObjects 3.0 features

include:

Information managementcomprising the data integration, data quality, metadata, and lifecycle management

products you need to trust vital business information

The SAP BusinessObjects BI platformcomposed of a set of common services to simplify the deployment and

management of BI tools, reports, applications, and analytic engines

Performance management products and serviceshelping you align strategy by tracking and analyzing key

business metrics and goals via management dashboards, scorecards, analytics, and alerts

To speed your organization to new levels of performance, SAP BusinessObjects Field Services offers a comprehensive

set of education and consulting services specifically integrated to our world-class products. From tactical installation tostrategic transformation, our global team delivers the highest levels of excellence in driving your success.

In addition to SAP Field Services, thousands of partners in over 80 countries enrich our services and support. Tapping

into the SAP Partner Network, you access the companies who are fueling business innovation with SAP Business

Objects. Our system integrators, value-added resellers, and original equipment manufacturer (OEM) partners can be

an essential part of your successconsistently delivering results that exceed expectations.

Data Quality Assessment Whitepaper

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