Why is it important to create short-term wins when rolling out a Data Governance initiative?
In data integration, the goal of data discovery is toc
SDLC stands for:
Technical metadata describes details of the processing and accessing of data.
Subtype absorption: The subtype entity attributes are included as nullable columns into a table representing the supertype entity
The neutral zone is one of the phases in the Bridges’ transition phases.
Operational Metadata describes details of the processing and accessing of data. Which one is not an example:
Poorly managed metadata leads to:
Normalisation is the process of applying rules in order to organise business complexity into stable data structures.
Examples of business processes when constructing data flow diagrams include:
An application DBA leads the review and administration of procedural database objects.
Small reference data value sets in the logical data model can be implemented in a physical model in three common ways:
Data professionals involved in Business Intelligence, analytics and Data Science are often responsible for data that describes: who people are; what people do; where people live; and how people are treated. The data can be misused and counteract the principles underlying data ethics.
A ‘Golden Record’ means that it is always a 100% complete and accurate representation of all entities within the organization.
Confirming and documenting understanding of different perspectives facilitate:
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?
Please select the two concepts that drive security restrictions:
Drivers for data governance most often focus on reducing risk or improving processes. Please select the elements that relate to the reduction in risk:
Lack of automated monitoring represents serious risks, including compliance risk.
Use business rules to support Data Integration and Interoperability at various points, to:
There are three basic approaches to implementing a Master Data hub environment, including:
If two data stores are able to be inconsistent during normal operations, then the
integration approach is:
Data Integration and Interoperability is dependent on these other areas of data management:
Which Data Architecture Artifact describes how data transforms into business
assets?
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.
Advantages if a centralized metadata repository include:
Obfuscating or redacting data is the practice of making information anonymous ot removing sensitive information. Risks are present in the following instances:
Which of the following answers best describes an Active Data Dictionary?
The business case for enterprise warehousing is:
Examples of technical metadata include:
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.
Project that use personal data should have a disciplined approach to the use of that data. They should account for:
When constructing an organization’s operating model cultural factors must be taken into consideration.
Data handling ethics are concerned with how to procure, store, manage, use and dispose of data in ways that are aligned with ethical principles.
Business requirements is an input in the Data Warehouse and Business Intelligence context diagram.
The roles associated with enterprise data architecture are data architect, data modellers and data stewards.
The Belmont principles that may be adapted for Information Management disciplines, include:
Machine learning explores the construction and study of learning algorithms.
A "Data Governance strategy" usually includes the following deliverables:
A control activity in the metadata management environment includes loading statistical analysis.
The data-vault is an object-orientated, time-based and uniquely linked set of normalized tables that support one or more functional areas of business.
The dependencies of enterprise technology architecture are that it acts on specified data according to business requirements.
SBA is an abbreviation for service-based architecture.
Data replication can be active or passive.
A general principle for managing metadata includes Responsibility.
Most document programs have policies related to:
An input in the data architecture context diagram includes data governance.
Data modeller: responsible for fata model version control an change control
SPARC published their three-schema approach to database management. The three key components were:
Service accounts are convenient because they can tailor enhanced access for the processes that use them.
The Data Warehouse (DW) is a combination of three primary components: An integrated decision support database, related software programs and business intelligence reports.
A data warehouse deployment with multiple ETL, storage and querying tools often
suffers due to the lack of:
According to the DMBoK2, by creating Data Management Services, IT involves the Data Governance Council:
Issue management is the process for identifying, quantifying, prioritizing and resolving data governance related issues, including:
Different levels of policy are required to govern behavior to enterprise security. For example:
Enterprise Architecture domains include:
Data Storage and Operations: The design, implementation and support of stored data to maximize its value.
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.
Part of alignment includes developing organizational touchpoints for data governance work. Some examples of touchpoints include: Procurement and Contracts; Budget and Funding; Regulatory Compliance; and the SDLC framework.
The primary goal of data management capability assessment is to evaluate the current state of critical data management activities in order to plan for improvement.
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 goals of implementing best practices around document and content management include:
What is one of the most important things about collecting data?
What are the business objectives for building a business glossary?
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.
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?
Creating the CDM involves the following steps:
Activities that drive the goals in the context diagram are classified into the following phases:
Data science depends on:
Content needs to be modular, structured, reusable and device and platform independent.
Change Data Capture is a method of reducing bandwidth by filtering to include only data that has been changed within a defined timeframe.
Emergency contact phone number would be found in which master data
management program?
The acronym ETL most commonly stands for:
In a SQL injection attack, a perpetrator inserts authorized database statements into a vulnerable SQL data channel, such as a stored procedure.
Decentralized informality can be made more formal through a documented series of connections and accountabilities via a RACI matrix.
Data lineage is useful to the development of the data governance strategy.
Please select the transition phases in Bridges’ Transition process:
A data model that consists of a single fact table linked to important concepts of the
business is a:
The Data Model Scorecard provides 10 data model quality metrics
The scope and focus of any data governance program depend on organizational needs, but most programs include:
While the focus of data quality improvement efforts is often on the prevention of errors, data quality can also be improved through some forms of data processing.
The steps followed in managing data issues include:
Business Intelligence, among other things, refer to the technology that supports this kind of analysis.
The goals of Data Integration and Interoperability include:
In the Abate Information Triangle the past moves through the following echelons befor it comes insight:
Reference and Master Data Management follow these guiding principles:
Barriers to effective management of data quality include:
An image processing system captures, transforms and manages images of paper and electronic documents.
Because Data Governance activities require coordination across functional areas, the DG program must establish an ___________ that defines accountabilities and intersections.
The best DW/BI architects will design a mechanism to connect back to transactional level and operational level reports in an atomic DW.
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.
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?
An advantage of a centralized repository include: Quick metadata retrieval, since the repository and the query reside together.
Within the Data Handling Ethics Context Diagram a key deliverable is the Ethical Data Handling Strategy.
Malware refers to any infectious software created to damage, change or improperly access a computer or network.
Logical abstraction entities become separate objects in the physical database design using one of two methods.
Master data management includes several basic steps, which include: Develop rules for accurately matching and merging entity instances.
The most informal enterprise data model is the most detailed data architecture design document.
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.
Which of the following is NOT a responsibility of a Data Steward?
Data Governance requires which of the following?
Compound authorization groups provide a means to:
A critical step in data management organization design is identifying the best-fit operating model for the organization.
A System of Reference is an authoritative system where data consumers can obtain reliable data to support transactions and analysis, even if the information did not originate in the system reference.
MPP is an abbreviation for Major Parallel Processing.
Modeling Bid data is a non-technical challenge but critical if an organization that want to describe and govern its data.
DAMA International’s Certified Data Management Professional (CDMP) certification required that data management professionals subscribe to a formal code of ethics, including an obligation to handle data ethically for the sake of society beyond the organization that employs them.
Different storage volumes include:
JSON is an open, lightweight standard format for data interchange.
Temporal aspects usually include:
Deliverables in the data quality context diagram include:
DMMA ratings represent a snapshot of the organization’s capability level.
Data parsing is the process of analysing data using pre-determined rules to define its content or value.
Following the rollout of a data issue process, there have been no issues recorded in the first month. The reason for this might be:
The term data quality refers to only the characteristics associated with high quality data.
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.
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?
Two risks with the Matching process are:
Business rules describe why business should operate internally, in order to be successful and compliant with the outside world.
Taxonomies can have different structures, including:
Validity, as a dimension of data quality, refers to whether data values are consistent with a defined domain of values.
Location Master Data includes business party addresses and business party location, as well as facility addresses for locations owned by organizations.
A content strategy should end with an inventory of current state and a gap assessment.
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:
Please select the 2 frameworks that show high-level relationships that influence how an organization manages data.
GDPR came into affect in May. 2018. What organization is responsible for awarding compliance certificates for organizations?
Data management organizational constructs include the following type of model.
Issues caused by data entry processes include:
For each subject area logical model: Decrease detail by adding attributes and less-significant entities and relationships.
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:
When constructing models and diagrams during formalisation of data architecture there are certain characteristics that minimise distractions and maximize useful information. Characteristics include:
Sample value metrics for a data governance program include:
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.
Analytics models are associated with different depths of analysis, including:
Examples of business metadata include:
The independent updating of data into a system of reference is likely to cause:
The disclosure of sensitive addresses may occur through:
Poorly managed Metadata leads to, among other, redundant data and data management processes.
When we consider the DMBoK2 definition of Data Governance, and the various practitioner definitions that exist in the literature, what are some of the key elements of Data Governance?
The load step of ETL is physically storing or presenting the results of the transformation in the target system.
Examples of interaction models include:
The Data Warehouse encompasses all components in the data staging and data presentation areas, including:
The IT security policy provides categories for individual application, database roles, user groups and information sensitivity.
The loading of country codes into a CRM is a classic:
Corporate Information Factory (CIF) components include:
Three data governance operating models types include:
The database administrator (DBA) is the most established and the most widely adopted data professional role.
Database monitoring tools measure key database metrics, such as:
As an often-overlooked aspects of basic data movement architecture, Process controls include:
The four A’s in security processes include:
When assessing security risks it is required to evaluate each system for the following:
Hierarchical database model is the newest database model
To build models, data modellers heavily rely on previous analysis and modelling work.
Which of the following is a type of data steward?
What ISO standard defines characteristics that can be tested by any organisation in the data supply chain to objectively determine conformance of the data to this ISO standard.
Information architecture is the process of creating structure for a body of information or content. It includes the following components:
Common understanding of the core business concepts and terminology is the objective of which deliverable?
Considerations for whether to integrate two data stores should include all except
the:
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?
Which of the following is not a step in the 'document and content management
lifecycle'?
Please select the types of DBA specializations:
The operational data quality management procedures depend on the ability to measure and monitor the applicability of data.
Data Warehouse describes the operational extract, cleansing, transformation, control and load processes that maintain the data in a data warehouse.
The most common drivers for initiating a Mater Data Management Program are:
The goals of Metadata management include:
The difference between warehouses and operational systems do not include the following element:
Data quality management is a key capability of a data management practice and organization.
Type of Reference Data Changes include:
Inputs in the Data Integration and Interoperability context diagram include:
Architecture is the fundamental organization of a system, embodied in its components, their relationships to each other and the environment and the principles governing its design and evolution.
Key processing steps for MDM include:
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.
A dimensional physical data model is usually a star schema, meaning there is one structure for each dimension.
Some ways to measure value of data include:
Which of the following is NOT a goal of Data Quality?
Communications are essential to the success of a DMM or Data Governance assessment. Communications are important because:
Characteristics that minimise distractions and maximise useful information include, but not limited to, consistent object attributes
In the Information Management Lifecycle, the Data Governance Activity "Define the Data Governance Framework" is considered in which Lifecycle stage?
A business driver for Master Data Management program is managing data quality.
The minority of operational metadata is generated as data is processed.
An organization will create an uncover valuable Metadata during the process of developing Data Integration and Interoperability solutions.
Different types of metadata include:
Organizations are legally required to protect privacy by identifying and protecting sensitive data. Who usually identifies the confidentiality schemes and identify which assets are confidential or restricted?
Principles for data asset accounting include:
Please select the correct name for the PDM abbreviation when referring to modelling.
Examples of the ‘What’ entity category include the following nouns:
Please select the four domains of enterprise architecture:
What business function is best aligned to deliver oversight to data architecture ?
Critical success factors throughout the BI/DW lifecycle include:
The data warehouse and marts differ from that in applications as the data is organized by subject rather than function.
It is unwise to implement data quality checks to ensure that the copies of the attributes are correctly stored.
The CAP theorem states that at most two of the three properties: consistency, availability and partition tolerance can exist in any shared data system.
Operational reports are outputs from the data stewards.
The business glossary application is structured to meet the functional requirements of the three core audiences:
How can the Data Governance process in an organisation best support the requirements of various Regulatory reporting needs?
Possible application coupling designs 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?
In data modelling practice, entities are linked by:
A limitation of the centralized metadata repository approach is it may be less expensive.
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