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Deliverables in the data management maturity assessment context diagram include:
The data in Data warehouses and marts differ. Data is organized by subject rather than function
Three classic implementation approaches that support Online Analytical Processing 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.
The language used in file-based solutions is called MapReduce. This language has three main steps:
An advantage of a centralized repository include: Quick metadata retrieval, since the repository and the query reside together.
A hacker is a person who finds unknown operations and pathways within complex computer system. Hackers are only bad.
Inputs in the Data Integration and Interoperability context diagram include:
When constructing models and diagrams during formalisation of data architecture there are certain characteristics that minimise distractions and maximize useful information. Characteristics include:
A roadmap for enterprise data architecture describes the architecture’s 3 to 5-year development path. The roadmap should be guided by a data management maturity assessment.
There are numerous methods of implementing databases on the cloud. The most common are:
Normalisation is the process of applying rules in order to organise business complexity into stable data structures.
The information governance maturity model describes the characteristics of the information governance and recordkeeping environment at five levels of maturity for each of the eight GARP principles. Please select the correct level descriptions:
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.
Examples of business processes when constructing data flow diagrams include:
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.
Business activity information is one of the types of data that can be modelled.
Data Governance is at the centre if the data management activities, since governance is required for consistency within and balance between functions.
An organization will create an uncover valuable Metadata during the process of developing Data Integration and Interoperability solutions.
The Belmont principles that may be adapted for Information Management disciplines, include:
The load step of ETL is physically storing or presenting the results of the transformation in the target system.
The roles associated with enterprise data architecture are data architect, data modellers and data stewards.
Risk classifications describe the sensitivity of the data and the likelihood that it might be sought after for malicious purposes.
Analytics models are associated with different depths of analysis, including:
Select the areas to consider when constructing an organization’s operating model:
Examples of concepts that can be standardized within the data architecture knowledge area include:
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.
Functionality-focused requirements associated with a comprehensive metadata solution, include:
One of the deliverables in the Data Integration and Interoperability context diagram is:
Domains can be identified in different ways including: data type; data format; list; range; and rule-based.
Poorly managed Metadata leads to, among other, redundant data and data management processes.
Within the Data Handling Ethics Context Diagram a key deliverable is the Ethical Data Handling Strategy.
A dimensional physical data model is usually a star schema, meaning there is one structure for each dimension.
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.
Project that use personal data should have a disciplined approach to the use of that data. They should account for:
A business driver for Master Data Management program is managing data quality.
Please select the incorrect item that does not represent a dimension in the Data Values category in Data Quality for the Information age.
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.
Release management is critical to batch development processes that grows new capabilities.
All organizations have the same Master Data Management Drivers and obstacles.
Please select the correct component pieces that form part of an Ethical Handling Strategy and Roadmap.
Logical abstraction entities become separate objects in the physical database design using one of two methods.
Data governance program must contribute to the organization by identifying and delivering on specific benefits.
E-discovery is the process of finding electronic records that might serve as evidence in a legal action.
Information gaps represent enterprise liabilities with potentially profound impacts on operational effectiveness and profitability.
When assessing security risks it is required to evaluate each system for the following: