Free Data Management Fundamentals Practice Questions

A.  

Active resistance

B.  

Psychological

C.  

Systematic

D.  

Structural

A.  

Size, Speed and Sensitivity

B.  

Volume, Variety and Velocity

C.  

Direction, Depth and Details

D.  

Expansive, Engaged and Enormous

E.  

Complexity, Compliance and Completeness

A.  

Lack of results gathered can indicate a lack of assessment performance

B.  

The assessments are done by different teams within the organization and may have different results

C.  

Interpreting these results is difficult

D.  

Data Management and Data Governance results are gathered and interpreted differently, depending on the organization being evaluated

E.  

Performing these activities objectively can ensure the success of the assessment and affect the acceptance and implementation of the data management and/or Data Governance program

A.  

Order Management

B.  

Marketing & Sales

C.  

Sales order

D.  

Invoicing

E.  

Product Development

F.  

Customer

A.  

Continuous, consistent, current and private

B.  

Complete, consistent, current and authoritative

C.  

Secure, auditable, publicly available and free

D.  

Complete, consistent, content and relevant

E.  

Secure, auditable. complete and relevant

A.  

Better corporate compliance with legal and regulatory demands, especially in relation to data protection, security and privacy

B.  

Lower operational costs resulting from better data quality and a reduced need for cost of failure and rework activities

C.  

The current corporate information policy states that company data must be managed and effectively governed

D.  

Enhanced customer perceptions of your company's brand and enhanced customer acquisition, retention and loyalty

E.  

New sales and revenue opportunities that better managed data will enable

A.  

Data Quality Assurance

B.  

None of the above

C.  

Data Quality Planning

D.  

Data Quality Audit

E.  

Data Quality Control

F.  

Data Quality Improvement

A.  

Optimism, objective, sustainable

B.  

Sustainable, embedded, measured

C.  

Measured, objective, embedded

D.  

Embedded, systematic, sustainable

E.  

Sustainable, realistic, embedded

A.  

Staff turnover in most organisations makes longer term planning impossible

B.  

Short term wins help ensure on-going political support

C.  

Short term wins help to distract stakeholders from delayed delivery on bigger issues

D.  

You need to align your deliverables with internal project budgeting cycles

E.  

People find it hard to sustain commitment to change if they do not see compelling results within a relatively short time period

A.  

Communications can influence the socialization and acceptance of the results and implementation of a data management or Data Governance program

B.  

Many organizations will overlook the communications aspect of a data management or Data Governance assessment

C.  

Findings may affect stakeholder's positions and roles

D.  

Each organization will approach data management and Data Governance communications differently

E.  

Data management and Data Governance communications are different from each other

A.  

Managing performance of data assets

B.  

Ensure metadata quality, consistency, currency and security

C.  

Managing the availability of data throughout the data lifecycle

D.  

Provide standard ways to make metadata accessible to metadata consumers

E.  

Managing the performance of data transactions

F.  

Establish or enforce the use of technical Metadata standards to enable data exchange

A.  

TRUE

B.  

FALSE

A.  

Perform a one off review of data quality

B.  

Create a new data store for regulator required metrics

C.  

Capture and document all metrics and store in a central repository

D.  

Undertake an audit of current process and produce a report

E.  

Provide the framework and guidance to enable a business led ongoing Data Governance process

A.  

TRUE

B.  

FALSE

A.  

A change management model, prioritising security changes and then updatingthe active directory

B.  

An enterprise data model, rolling out data flow diagrams and enbedding securityinto the database

C.  

A security model, classifying each organisational role and putting the physicaldata behind a firewall

D.  

A classification model, classifying each data concept and locating the physicaldata

E.  

A metadata model, locating the data and moving it into the metadata repository