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Which of the following would NOT be an interest of Data Governance?
A successful Data Governance program requires that all enterprise data be certified.
What are the components of a Data Governance Readiness Assessment?
If two data stores are able to be inconsistent during normal operations, then the
integration approach is:
Media monitoring and text analysis are automated methods for retrieving insights from large unstructured or semi-structured data, such as transaction data, social media, blogs, and web news sites.
Please select the types of DBA specializations:
The target of organizational change is expedition.
Content refers to the data and information inside a file, document or website.
A goal of reference and master data is to provide authoritative source of reconciled and quality-assessed master and reference data.
Enterprise data architecture description must include both [1] as well as [2]
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?
A ‘Golden Record’ means that it is always a 100% complete and accurate representation of all entities within the organization.
All metadata management solutions include architectural layers including:
Governance ensures data is managed, but is not include the actual act of managing data.
A metadata repository is essential to assure the integrity and consistent use of an enterprise data model across business processes.
Integrating data security with document and content management knowledge areas.
guides the implementation of:
A Global ID is the MDM solution-assigned and maintained unique identifier attached to reconciled records.
All DMM and Data Governance assessments should identify its objectives and goals for improvement. This is important because:
'Planning, implementation and control activities for lifecycle management of data and
information, found in any form or medium', pertains to which knowledge area?
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 security internal audits ensure data security and regulatory compliance policies are followed should be conducted regularly and consistently.
Data Governance is at the centre if the data management activities, since governance is required for consistency within and balance between functions.
CIF stands for:
Quality Assurance Testing (QA) is used to test functionality against requirements.
The accuracy dimension has to do with the precision of data values.
One of the first steps in a master data management program is to:
Data science depends on:
What types of data are considered Technical Data?
Domains can be identified in different ways including: data type; data format; list; range; and rule-based.
Structural Metadata describe srealtionships within and among resource and enables identification and retrieval.
ISO 8000 will describe the structure and organization of data quality management, including:
RACI is an acronym that is made up of the following terms.
Enterprise data architecture influences the scope boundaries of project and system releases. An example of influence is data replication control.
Poorly managed Metadata leads to, among other, redundant data and data management processes.
Examples of business metadata include:
Several global regulations have significant implications on data management practices. Examples include:
Please select the answer that best fits the following description: Contains only real-time data.
Please select the correct types of data stewards:
Please select the user that best describes the following description: Uses the business glossary to make architecture, systems design, and development decisions, and to conduct the impact analysis.
Which of the following is a Data Quality principle?
A goal of metadata management is to manage data related business terminology in
order toc
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?
Issue management is the process for identifying, quantifying, prioritizing, and resolving Data Governance issues. Which of the following are areas where that issues might arise:
A catastrophic system failure due to processing attachments that are too large may
be solved by:
Examples of transformation in the ETL process onclude:
Time-based patterns are used when data values must be associated in chronological order and with specific time values.
Data Integration and Interoperability is dependent on these other areas of data management:
The Data Governance Council (DGC) manages data governance initiatives, issues, and escalations.
A Data Management Maturity Assessment (DMMA) can be used to evaluate data management overall, or it can be used to focus on a single Knowledge Area or even a single process.
Service accounts are convenient because they can tailor enhanced access for the processes that use them.
An advantage of a centralized repository include: High availability since it is independent of the source systems.
Critical Data is most often used in
Different storage volumes include:
Identify indicative components of a Data Strategy.
Enterprise data architecture project-related activities include:
Please select the two concepts that drive security restrictions:
What model is the highest level model within the enterprise data model?
The advantage of a decentralized data governance model over a centralized model is:
SOA stand for Service Orchestrated Architecture
A change management program supporting formal data governance should focus communication on:
Obtaining buy-in from all stakeholders
If data is not integrated with care it presents risk for unethical data handling. These ethical risks intersect with fundamental problems in data management including: Limited knowledge of data’s origin and lineage; Data of poor quality; Unreliable Metadata; and Documentation of error remediation.
Basic profiling of data involves analysis of:
JSON is an open, lightweight standard format for data interchange.
With respect to health data, what is the difference between the privacy and the security of the data?
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:
Inputs in the data quality context diagram include:
The four A’s in security processes include:
Data management professionals who understand formal change management will be more successful in bringing about changes that will help their organizations get more value from their data. To do so, it is important to understand:
The acronym CMDB stands for:
Master data is an aggregation of:
The acroymn ACID stands for.
CMDB provide the capability to manage and maintain Metdata specifically related to the IT assets, the relationships among them, and contractual details of the assets.
Some common data quality business rule types are:
Business rules describe why business should operate internally, in order to be successful and compliant with the outside world.
Veracity refers to how difficult the data is to use or to integrate.
When constructing models and diagrams during formalisation of data architecture there are certain characteristics that minimise distractions and maximize useful information. Characteristics include:
When starting a Data Governance initiative it is important to understand what the Business cannot achieve due to data issues because:
A node is a group of computers hosting either processing or data as part of a distributed database.
ETL is the basic process which is central to all areas in Data Integration and Interoperability. It is an abbreviation for extract, transition and load.
Data Governance Office (DGO) focuses on enterprise-level data definitions and data management standards across all DAMA-DMBOK knowledge areas. Consists of coordinating data management roles.
Considerations for whether to integrate two data stores should include all except
the:
Data security issues, breaches and unwarranted restrictions on employee access to data cannot directly impact operational success.
The goals of Metadata management include:
Adoption of a Data Governance program is most likely to succeed:
What position is responsible for the quality and use of their organization's data
assets?
The key architecture domains include:
A sandbox environment can either be a sub-set of the production system, walled off from production processing or a completely separate environment.
A data model that consists of a single fact table linked to important concepts of the
business is a:
Data models comprise and contain metadata essential to data consumers.
The biggest business driver for developing organizational capabilities around Big Data and Data Science is the desire to find and act on business opportunities that may be discovered through data sets generated through a diversified range of processes.
A point to point interface architecture will, in general, have more or less interfa
formats than a service oriented architecture?
An organization can enhance its Data Governance program and thereby improve its approach to enterprise data management. This is important for the following reason:
Those responsible for the data-sharing environment have an obligation to downstream data consumers to provide high quality data.
The Data Model Scorecard provides 10 data model quality metrics
The need to manage data movement efficiently is a primary driver for Data Integration and Interoperability.
A critical step in data management organization design is identifying the best-fit operating model for the organization.
The CAP theorem states that at most two of the three properties: consistency, availability and partition tolerance can exist in any shared data system.
Practitioners identify development of staff capability to be a primary concern of Data Governance. Why would this be a main concern?
Three data governance operating models types include:
The first two steps in the data science process are:
One common KPI of e-discovery is cost reduction.
Achieving security risk reduction in an organisation begins with developing what?
Business requirements is an input in the Data Warehouse and Business Intelligence context diagram.
A goal of Data warehouse and business intelligence is to support and enable ineffective business analysis and decision making by knowledge workers.
What is the most critical task for a new Data Governance team?
There are three basic approaches to implementing a Master Data hub environment, 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:
A hacker is a person who finds unknown operations and pathways within complex computer system. Hackers are only bad.
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.
The standard for a strong password is set by the:
Reference and Master Data Management follow these guiding principles:
Preparation and pre-processing of historical data needed in a predictive model may be performed in nightly batch processes or in near real-time.
Please select the answer that does not represent a machine learning algorithm:
Decentralized informality can be made more formal through a documented series of connections and accountabilities via a RACI matrix.
Information architecture is the process of creating structure for a body of information or content. It includes the following components:
Examples of concepts that can be standardized within the data architecture knowledge area include:
The repeated implementation of different CRM technologies with different data
structures is mostly a failure of:
Data Governance focuses exclusively on:
The goals of data storage and operations include:
Data Governance requires which of the following?
Type of Reference Data Changes include:
Changes to reference data do not need to be management, only metadata should be managed.
Data asset valuation is the process of understanding and calculating the economic value of data to an organisation. Value comes when the economic benefit of using data outweighs the costs of acquiring and storing it, as
Compound authorization groups provide a means to:
A deliverable in the data security context diagram is the data security architecture.
Primary deliverables of the Data Warehouse and Business Intelligence context diagram 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].
The categories of the Data Model Scorecard with the highest weightings include:
A completely distributed architecture maintains a single access point. The metadata retrieval engine responds to user requests by retrieving data from source systems in real time.
The data in Data warehouses and marts differ. Data is organized by subject rather than function
The business glossary should capture business terms attributes such as:
The goals of data security include:
Two risks with the Matching process are:
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 term data quality refers to only the characteristics associated with high quality data.
When trying to integrate a large number of systems, the integration complexities can
be reduced by:
Modeling Bid data is a non-technical challenge but critical if an organization that want to describe and govern its data.
The DW encompasses all components in the data staging and data presentation areas, including:
When assessing tools to implement master data management solutions, functionality
must include:
GDPR and PIPEDA are examples of:
Normalisation is the process of applying rules in order to organise business complexity into stable data structures.
Data replication has two dimensions of scaling: diagonal and lateral
Data quality issues cannot emerge at any point in the data lifecycle.
The independent updating of data into a system of reference is likely to cause:
Most document programs have policies related to:
The advantage of a decentralised Data Governance model over a centralised model is:
When data is classified as either security data or regulatory data, the result will be:
Data mining is a sub-field of supervised learning where users attempt to model data elements and predict future outcomes through the evaluation of probability estimates.
Consistent input data reduces the chance of errors in associating records. Preparation processes include:
Some document management systems have a module that may support different types of workflows such as:
Taxonomies can have different structures, including:
An enterprise's organisation chart has multiple levels, each with a single reporting
line. This is an example of a:
Data parsing is the process of analysing data using pre-determined rules to define its content or value.
A lineage data tool provides:
Reference and Master Data Management follow these guiding principles:
Discovering and documenting metadata about physical data assets provides:
Confidentiality classification schemas might include two or more of the five confidentiality classification levels. Three correct classifications levels are:
A goal of a Reference and Master Data Management program include enabling master and reference data to be shared across enterprise functions and applications.
Examples of interaction models include:
You have completed analysis of a Data Governance issue in your organisation and have presented your findings to the executive management team. However, your findings are not greeted warmly and you find yourself being blamed for the continued existence of the issue. What is the most likely root cause for this?
Latency can be:
The Data Warehouse (DW) is a combination of three primary components: An integrated decision support database, related software programs and business intelligence reports.
Data quality rules and standards are a critical form of Metadata. Ti be effective they need to be managed as Metadata. Rules include:
Which of these is not a goal of Data Governance and Stewardship?
You are a reporting Data Analyst. A new Management Report has been requested. What is the most effective way to ensure you receive the appropriate data at the correct level of accuracy to meet the business need?
Please select valid modelling schemes or notations
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:
The data warehouse and marts differ from that in applications as the data is organized by subject rather than function.
Business metadata focuses largely on the content and condition of the data and includes details related to data governance.
Big data primarily refers specifically to the volume of the data.
DBAs exclusively perform all the activities of data storage and operations.
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:
Please select correct term for the following sentence: An organization shall assign a senior executive to appropriate individuals, adopt policies and processes to guide staff and ensure program audibility.
An organization has a legitimate interest in commercializing data. So why is the economic value of data a core concept of data handling ethics?
Data management organizational constructs include the following type of model.
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:
Data modelling tools and model repositories are necessary for managing the enterprise data model in all levels.
Machine learning explores the construction and study of learning algorithms.
Oversight for the DMMA process belongs to the Data Quality team.
Data Integrity includes ideas associated with completeness, accuracy, and consistency.
The second stage of Kotter’s eight stage process is:
A communication plan includes an engagement model for stakeholders, the type of information to be shared, and the schedule for sharing information.
The Belmont principles that may be adapted for Information Management disciplines, include:
What is the main purpose of developing a Data Architecture Roadmap?
Which Data Architecture artefact contains the names of key business entities, their
relationships, critical guiding business rules and critical attributes?
Access to data for Multidimensional databases use a variant of SQL called MDX or Multidimensional expression.
Data governance requires control mechanisms and procedures for, but not limited to, identifying, capturing, logging and updating actions.
A general principle for managing metadata includes Responsibility.
SOR Stands for:
Within the Data Handling Ethics Context Diagram a key deliverable is the Ethical Data Handling Strategy.
Looking at the DMBoK definition of Data Governance, and other industry definitions, what are some of the common key elements of Data Governance?
Data profiling is a form of data analysis used to inspect data and assess quality.
In designing and building the database, the DBA should keep the following design principles in mind:
Customer value comes when the economic benefit of using data outweighs the costs of acquiring and storing it, as well we managing risk related to usage. Which of these is not a way to measure value?
A data warehouse deployment with multiple ETL, storage and querying tools often
suffers due to the lack of:
Self-service is a fundamental delivery channel in the BI portfolio.
An advantage of a centralized repository include: Quick metadata retrieval, since the repository and the query reside together.
Within each area of consideration mentioned in question 13, they should address morale adversity as per Ethical Risk Model for Sampling Projects.