Subject Area Goals (Reverse) Flashcards
Discover relationships between data and the business.
<p><strong>Big Data and Data Science</strong></p>
Support the iterative integration of data source(s) into the enterprise.
<p><strong>Big Data and Data Science</strong></p>
Discover and analyze new factors that might affect the business.
<p><strong>Big Data and Data Science</strong></p>
Publish data using visualization techniques in an appropriate, trusted, and ethical manner.
<p><strong>Big Data and Data Science</strong></p>
Develop a governed approach to make data fit for purpose based on data consumers’ requirements.
<p><strong>Data Quality</strong></p>
Define standards, requirements, and specifications for data quality controls as part of the data lifecycle.
<p><strong>Data Quality</strong></p>
Define and implement processes to measure, monitor, and report on data quality levels.
<p><strong>Data Quality</strong></p>
Identify and advocate for opportunities to improve the quality of data, through process and system improvements.
<p><strong>Data Quality</strong></p>
Provide organizational understanding of business terms and usage.
<p><strong>Metadata Management</strong></p>
Collect and integrate metadata from diverse sources.
<p><strong>Metadata Management</strong></p>
Provide a standard way to access metadata.
<p><strong>Metadata Management</strong></p>
Ensure metadata quality and security.
<p><strong>Metadata Management</strong></p>
To build and maintain the technical environment and technical and business processes needed to deliver integrated data in support of operational functions, compliance requirements, and business intelligence activities.
<p><strong>Data Warehousing and Business Intelligence</strong></p>
To support and enable effective business analysis and decision making by knowledge workers.
<p><strong>Data Warehousing and Business Intelligence</strong></p>
Enable sharing of information assets across business domains and applications within an organization.
<p><strong>Reference and Master Data</strong></p>
Provide authoritative source of reconciled and quality-assessed master and reference data.
<p><strong>Reference and Master Data</strong></p>
Lower cost and complexity through use of standards, common data models, and integration patterns.
<p><strong>Reference and Master Data</strong></p>
To comply with legal obligations and customer expectations regarding Records management.
<p><strong>Document and Content Management</strong></p>
To ensure effective and efficient storage, retrieval, and use of Documents and Content.
<p><strong>Document and Content Management</strong></p>
To ensure integration capabilities between structured and unstructured Content.
<p><strong>Document and Content Management</strong></p>
Provide data securely, with regulatory compliance, in the format and timeframe needed.
<p><strong>Data Integration and Interoperability</strong></p>
Lower cost and complexity of managing solutions by developing shared models and interfaces.
<p><strong>Data Integration and Interoperability</strong></p>
Identify meaningful events and automatically trigger alerts and actions.
<p><strong>Data Integration and Interoperability</strong></p>
Support business intelligence, analytics, master data management, and operational efficiency efforts.
<p><strong>Data Integration and Interoperability</strong></p>
Enable appropriate, and prevent inappropriate, access to enterprise data assets.
<p><strong>Data Security</strong></p>
Understand and comply with all relevant regulations and policies for privacy, protection, andconfidentiality.
<p><strong>Data Security</strong></p>
Ensure that the privacy and confidentiality needs of all stakeholders are enforced and audited.
<p><strong>Data Security</strong></p>
Manage availability of data throughout the data lifecycle.
<p><strong>Data Storage and Operations</strong></p>
Ensure the integrity of data assets.
<p><strong>Data Storage and Operations</strong></p>
Manage performance of data transactions.
<p><strong>Data Storage and Operations</strong></p>
To confirm and document an understanding of different perspectives, which leads to applications that more closely align with current and future business requirements, and creates a foundation to successfully complete broad-scoped initiatives such as master data management and data governance programs.
<p><strong>Data Modeling and Design</strong></p>
Identify data storage and processing requirements.
<p><strong>Data Architecture</strong></p>
Design structures and plans to meet the current and long-term data requirements of the enterprise.
<p><strong>Data Architecture</strong></p>
Strategically prepare organizations to quickly evolve their products, services, and data to take advantage of business opportunities inherent in emerging technologies.
<p><strong>Data Architecture</strong></p>
Enable an organization to manage its data as an asset.
<p><strong>Data Governance</strong></p>
Define, approve, communicate, and implement principles, policies, procedures, metrics, tools, and responsibilities for data management.
<p><strong>Data Governance</strong></p>
Monitor and guide policy compliance, data usage, and management activities.
<p><strong>Data Governance</strong></p>
To define ethical handling of data in the organization
<p><strong>Data Ethics</strong></p>
To educate staff on the organization risks of improper data handling
<p><strong>Data Ethics</strong></p>
To change/instill preferred culture and behaviors on handling data.
<p><strong>Data Ethics</strong></p>
To monitor regulatory environment, measure, monitor, and adjust organization approaches for ethics in data.
<p><strong>Data Ethics</strong></p>
Understanding and supporting the information needs of the enterprise and its stakeholders, includingcustomers, employees, and business partners
<p><strong>Data Management</strong></p>
Capturing, storing, protecting, and ensuring the integrity of data assets
<p><strong>Data Management</strong></p>
Ensuring the quality of data and information
<p><strong>Data Management / Data Quality</strong></p>
Ensuring the privacy and confidentiality of stakeholder data
<p><strong>Data Management</strong></p>
Preventing unauthorized or inappropriate access, manipulation, or use of data and information
<p><strong>Data Management / Data Security</strong></p>
Ensuring data can be used effectively to add value to the enterprise
<p><strong>Data Management</strong></p>