Data Management Fundamentals Questions and Answers
Achieving near-real-time data replication, using a source accumulation technique,
triggers on:
Adoption of a Data Governance program is most likely to succeed:
Taxonomies can have different structures, including:
Data profiling is a form of data analysis used to inspect data and assess quality.
Type of Reference Data Changes include:
A general principle for managing metadata includes Responsibility.
As part of its transformation, the organization must identify and respond to different kinds of roadblocks. Please select the answer that is not a roadblock:
Modeling Bid data is a non-technical challenge but critical if an organization that want to describe and govern its data.
Reference and Master Data Management follow these guiding principles:
Data replication is useful as it provides:
Looking at the DMBoK definition of Data Governance, and other industry definitions, what are some of the common key elements of Data Governance?
Data Integration and Interoperability (DII) describes processes related to the movement and consolidation of data within and between data stores, applications and organizations.
RACI is an acronym that is made up of the following terms.
Business requirements is an input in the Data Warehouse and Business Intelligence context diagram.
Please select the correct definition of Data Management from the options below.
Data and text mining use a range of techniques, including:
Deliverables in the document and content management context diagram include:
Big Data and Data Science Governance should address such data questions as:
A goal of metadata management is to manage data related business terminology in
order toc
What result(s) is/are Data Handling Ethics trying to avoid?
Business metadata focuses largely on the content and condition of the data and includes details related to data governance.
When developing a Data Governance operating framework, what areas should be considered?
Sample value metrics for a data governance program include:
Differentiating between data and information. Please select the correct answers based on the sentence below: Here is a marketing report for the last month [1]. It is based on data from our data warehouse[2]. Next month these results [3] will be used to generate our month-over-month performance measure [4].
Match rules for different scenarios require different workflows, including:
When recovering from multiple system failures, what is the biggest difficulty faced
by a DBA?
An enterprise's organisation chart has multiple levels, each with a single reporting
line. This is an example of a:
Data lineage is useful to the development of the data governance strategy.
No recorded negative ethical outcomes does not mean that the organization is processing data ethically. Legislation cannot keep up with the evolution of the data environment so how do we stay compliant?
To push up the urgency level requires adding of the sources of complacency or increasing of their impact.
Every DMM and Data Governance assessment must define how the assessment team will interact with its subjects (after defining the subject/stakeholder list). This is important because:
Data Governance includes developing alignment of the data management approach with organizational touchpoints outside of the direct authority of the Chief Data Officer. Select the example of such a touchpoint.
There are three basic approaches to implementing a Master Data hub environment, including:
In Resource Description Framework (RDF) terminology, a triple store is composed of a subject that denotes a resource, the predicate that expresses a relationship between the subject and the object, and the object itself.
Which of these is NOT a component of an enterprise wide data strategy?
The key architecture domains include:
What are the three characteristics of effective Data Governance communication?
Different types of product Master Data solutions include:
A successful Data Governance program requires that all enterprise data be certified.
Reference and Master data definition: Managing shared data to meet organizational goals, reduce risks associated with data redundancy, ensure higher quality, and reduce the costs of data integration.
Data Integration and Interoperability is dependent on these other areas of data management:
MPP is an abbreviation for Major Parallel Processing.
The library of Alexandria was one of the largest collection of books in the ancient
world. Which DMBoK knowledge area is most aligned with managing the collection?
Oversight for the appropriate handling of data falls under both Data Governance and Legal Counsel. What are they NOT required to do?
Controlling data availability requires management of user entitlements and of structures that technically control access based on entitlements.
Developing complex event processing solutions require:
Data governance requires control mechanisms and procedures for, but not limited to, escalating issues to higher level of authority.
ANSI standard 859 has three levels of control of data, based on the criticality of the data and the perceived harm that would occur if data were corrupt or otherwise unavailable, including:
GDPR and PIPEDA are examples of:
Big data is often defined by three characteristics. They are:
Please select the correct principles of the General Data Protection Regulation (GDPR) of the EU.
Content management includes the systems for organizing information resources so that they can specially be stored.
There are three techniques for data-based change data capture, namely:
Reference and master data require governance processes, including:
Business glossaries have the following objectives:
Release management is critical to batch development processes that grows new capabilities.
Domains can be identified in different ways including: data type; data format; list; range; and rule-based.
Emergency contact phone number would be found in which master data
management program?
The Belmont principles that may be adapted for Information Management disciplines, include:
Please select the correct general cost and benefit categories that can be applied consistently within an organization.
An input in the Metadata management context diagram does not include:
Coupling describes the degree to which two systems are intertwined.
What key components make up the Data Governance Charter?
The failure to gain acceptance of a business glossary may be due to ineffective:
Technical metadata describes details of the processing and accessing of data.
Creating the CDM involves the following steps:
Issues caused by data entry processes include:
Business activity information is one of the types of data that can be modelled.
Please select the four domains of enterprise architecture:
The business glossary application is structured to meet the functional requirements of the three core audiences:
Well prepared records have characteristics such as:
Business people must be fully engaged in order to realize benefits from the advanced analytics.
Defining quality content requires understanding the context of its production and use, including:
ISO 8000 will describe the structure and the organization of data quality management, including:
Drivers for data governance most often focus on reducing risk or improving processes. Please select the elements that relate to the improvement of processes:
The target of organizational change is expedition.
In a data warehouse, where the classification lists for organisation type are
inconsistent in different source systems, there is an indication that there is a lack of
focus on:
Please select the answers that correctly describes where the costs of poor quality data comes from.
Some document management systems have a module that may support different types of workflows such as:
Data warehouses are often loaded and serviced by a nightly batch window.
The DW encompasses all components in the data staging and data presentation areas, including:
When presenting a case for an organization wide Data Governance program to your Senior Executive Board, which of these potential benefits would be of LEAST importance?
What is the most critical task for a new Data Governance team?
Data stewardship is the least common label to describe accountability and responsibility for data and processes to ensure effective control and use of data assets.
Repositories facilitate the collection, publishing and distribution of data in a centralized and possibly standardized way. Data is most often used to:
Data modelling tools and model repositories are necessary for managing the enterprise data model in all levels.
Effective data management involves a set of complex, interrelated processes that disable an organization to use its data to achieve strategic goals.
A goal of data architecture is to identify data storage and processing requirements.
The term data quality refers to both the characteristics associated with high quality data and to the processes used to measure or improve the quality of data.
All metadata management solutions include architectural layers including:
Three data governance operating models types include:
The acroymn ACID stands for.
The best way to validate that a database backup is working, is to:
Gathering and interpreting results from a DMM or Data Governance assessment are important because:
Types of metadata include:
A ‘Golden Record’ means that it is always a 100% complete and accurate representation of all entities within the organization.
In an information management context, the short-term wins and goals often arise from the resolution of an identified problem.
Where is the best place to find the following metadata: database table names,
column names and indexes?
Improving data quality requires a strategy that accounts for the work that needs to be done and the way people will execute it.
Enterprise data architecture description must include both [1] as well as [2]
The CAP theorem asserts that the distributed system cannot comply with all the parts of the ACID. A distributed system must instead trade-off between the following properties:
The loading of country codes into a CRM is a classic:
Which of the following provides the strongest tangible reason for driving initiation of a Data Governance process in an enterprise?
Please select the 2 frameworks that show high-level relationships that influence how an organization manages data.
Examples of transformation in the ETL process onclude:
Poorly managed Metadata leads to, among other, redundant data and data management processes.
A "Data Governance strategy" usually includes the following deliverables:
Integrating data security with document and content management knowledge areas.
guides the implementation of:
When doing reference data management, there many organizations that have standardized data sets that are incredibly valuable and should be subscribed to. Which of these organizations would be least useful?
The steps followed in managing data issues include:
Three classic implementation approaches that support Online Analytical Processing include:
Security Risks include elements that can compromise a network and/or database.
A goal of reference and master data is to provide authoritative source of reconciled and quality-assessed master and reference data.
A Metadata repository contains information about the data in an organization, including:
Examples of the ‘Who’ entity category include: employee; patient; player; and suspect.
Most document programs have policies related to:
What position is responsible for the quality and use of their organization's data
assets?
Device security standard include:
Which of the following is not a step in the 'document and content management
lifecycle'?
Operationality and interoperability depends on the data quality. In order to measure the efficiency of a repository the data quality needs to be:
The accuracy dimension of data quality refers to the degree that data correctly respresents ‘real-life’ entities.
A complexity in documenting data lineage is:
A deliverable in the data security context diagram is the data security architecture.
The process of building architectural activities into projects also differ between methodologies. They include:
Value is the difference between the cost of a thing and the benefit derived from that thing.
The implementation of a Data Warehouse should follow these guiding principles:
Data security issues, breaches and unwarranted restrictions on employee access to data cannot directly impact operational success.
A Global ID is the MDM solution-assigned and maintained unique identifier attached to reconciled records.
Corrective actions are implemented after a problem has occurred and been detected.
In the Information Management Lifecycle, the Data Governance Activity "Define the Data Governance Framework" is considered in which Lifecycle stage?
Data replication can be active or passive.
Technical Metadata provides data about the technical data, the systems that store data, and the processes that move between systems.
In data modelling practice, entities are linked by:
Deliverables in the Metadata Management context diagram include:
The ISO 11179 Metadata registry, an international standard for representing Metadata in an organization, contains several sections related to data standards, including naming attributes and writing definitions.
Triplestores can be classified into these categories:
One common KPI of e-discovery is cost reduction.
Input in the Big Data and data science context diagram include:
What key components must be included in the Implementation Roadmap?
Operational reports are outputs from the data stewards.
Malware types include:
Issue management is the process for identifying, quantifying, prioritizing and resolving data governance related issues, including:
Top down' and "bottom up' data analysis and profiling is best done in concert
because:
The goals of Data Integration and Interoperability include:
Inputs in the Data Integration and Interoperability context diagram include:
Business glossary is not merely a list of terms. Each term will be associated with other valuable metadata such as synonyms, metrics, lineage, or:
What are some of the business drivers for the ethical handling of data that Data Governance should satisfy?
It is unwise to implement data quality checks to ensure that the copies of the attributes are correctly stored.
Data science merges data mining, statistical analysis, and machine learning with the integration and data modelling capabilities, to build predictive models that explore data content patterns.
CMA is an abbreviation for Capability Maturity Assessment.
Data security includes the planning, development and execution of security policies and procedures to provide authentication, authorisation, access and auditing of data and information assets.
Which of the following is a Data Quality principle?
The IT security policy provides categories for individual application, database roles, user groups and information sensitivity.
There are numerous methods of implementing databases on the cloud. The most common are:
An input in the data architecture context diagram includes data governance.
CIF stands for:
The best DW/BI architects will design a mechanism to connect back to transactional level and operational level reports in an atomic DW.
Document and content management is defined as planning, implementation and control activities for storage management of data and information found in any form or medium.
The advantage of a decentralized data governance model over a centralized model is:
Critical Data is most often used in
Which of the following is a type of data steward?
Enterprise service buses (ESB) are the data integration solution for near real-time sharing of data between many systems, where the hub is a virtual concept of the standard format or the canonical model for sharing data in the organization.
The most important reason to implement operational data quality measurements is to inform data consumers about levels of data effectiveness.
Identify indicative components of a Data Strategy.
Data flows map and document relationships between data and locations where global differences occur.
Please select the correct General Accepted Information Principles:
The load step of the ETL is physically storing or presenting the results of the transformation into the source system.
What is the best definition of Crowdsourced data collection?
Improving an organization’s ethical behaviour requires an informal Organizational Change Management (OCM) process.
In a global organization which must operate under many local jurisdictions, each with their own legislative and compliance laws, which type of Data Governance Operating Model Type would best apply?
A metadata repository is essential to assure the integrity and consistent use of an enterprise data model across business processes.
Please select the two classifications of database types:
Data architect: A senior analyst responsible for data architecture and data integration.
Consistent input data reduces the chance of errors in associating records. Preparation processes include:
Hierarchical database model is the newest database model
All DMM and Data Governance assessments should identify its objectives and goals for improvement. This is important because:
Deliverables in the data quality context diagram include:
Achieving security risk reduction in an organisation begins with developing what?
Metadata is described using three sets od categories, including:
Master data is an aggregation of:
The creation of overly complex enterprise integration over time is often a symptom
of:
What are the business objectives for building a business glossary?
Once the most critical business needs and the data that supports them have been identified, the most important part of the data quality assessment is actually looking data, querying it to understand data content and relationships, and comparing actual data to rules and expectations.
The impact of the changes from new volatile data must be isolated from the bulk of the historical, non-volatile DW data. There are three main approaches, including:
Examples of technical metadata include:
Various Regulations require evidence of clear data lineage and accuracy. How can we as data managers best serve our enterprises in achieving this goal?
The ethics of data handling are complex, but is centred on several core concepts. Please select the correct answers.
One of the key differences between operational systems and data warehouses is:
According to the DMBoK, Data Governance is central to Data Management. In practical terms, what other functions of Data Management are required to ensure that your Data Governance programme is successful?
Examples of transformation include:
Reference and Master Data Management follow these guiding principles:
The advantage of a decentralised Data Governance model over a centralised model is:
A synonym for transformation in ETL is mapping. Mapping is the process of developing the lookup matrix from source to target structures, but not the result of the process.
How can the Data Governance process in an organisation best support the requirements of various Regulatory reporting needs?
To mitigate risks, implement a network-based audit appliance, which can address most of the weaknesses associated with the native audit tools. This kind of appliance has the following benefits:
Your organization has many employees with official roles as data stewards and data custodians, but they don't seem to know exactly what they're supposed to be doing. Which of the following is most likely to be a root cause of this problem?
Data parsing is the process of analysing data using pre-determined rules to define its content or value.
Typically, DW/BI have three concurrent development tracks:
The 'Data Governance Steering Committee' is best described as:
