The mission of Data Management is to define an enterprise-wide data environment to more easily and efficiently organize, identify, share, reuse, and correlate data that enables the business to consume information and maximize the value to the agency. This Data Management Process Description describes what happens within the process and provides an operational definition of the major components of the process. This description specifies in a complete, precise, and verifiable manner, the requirements, design, and behavior characteristics of Data Management process. The process description (PD) is a documented expression of a set of activities performed to achieve a given purpose. Tailoring of this process in order to meet the individual needs of each project is covered in the Tailoring Guidelines section of this document. For the purpose of this document, roles are provided to describe a set of responsibilities for performing a particular set of related activities. Roles and/or responsibilities should fit your business terminology.

The process goal describes a specific purpose or achievement toward which the efforts of the process are directed. Each process has a specific focus and when combined with the other processes, forms a comprehensive framework for delivering and managing services.
This IRM provides the fundamental knowledge and procedural guidance for employees who request the Data Management Services from Data Engineering Group.

Process objectives describe material outcomes that are produced or achieved by the process. The following is a list of objectives for this process:

Process controls represent the policies and guiding principles on how the process will operate. Controls provide direction over the operation of processes and define constraints or boundaries within which the process must operate.

The process controls are the following:

Metrics are used for the quantitative and periodic assessment of a process. They should be associated with targets that are set based on specific business objectives. Metrics provide information related to the goals and objectives of a process and are used to take corrective action when desired results are not being achieved and can be used to drive continual improvement of process effectiveness and efficiency.

Management will regularly set targets for process performance, gather quantifiable data related to different functions of the Data Management process, and review that data in order to make informed decisions and take appropriate corrective action, if necessary. All Measurements will have a defined data dictionary, map to the organizational strategic goals, and be documented in a Process Measurement Plan. The Process Measurement Plan template is available in the IT PAL.

The tailoring guidelines identify the allowable variations of the IT organization’s standard process as needed for adjustments (adding, deleting, modifying) relative to specific operational or functional needs of another organization. Process tailoring is about roles and procedures, not the standard process or major activities defined in this process. All tailoring request, with supporting rationale, must be submitted in writing to and approved by the Data Management Process owner.
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Terms and Definitions
 

Acronyms

[Identify and list the acronyms and definitions identified in this document. See example below].

To Collect structured and unstructured data from across the agency and external to the agency. By leveraging the additional data captured with e-filing and modernized residual paper processing, more data can be shared for matching and targeting the best case. Data can be collected in forms of documents, records, models, emails, processes, RDBMS, business rules, or transaction systems. There can only be 1 Role that is Responsible for a Task.

Data Consolidations: To manage data as follows: consolidate and condense disjoint data that can/should be homogenized and recognize which data is truly distinct to the relevant data is most easily identifiable and accessible. There can only be 1 Role that is Responsible for a Task.

Data Certification Certifies the designated sources, processes, projects and understand the data quality. The higher the quality of the data the Agency has, the more accurate scores can be produced. More accurate scores lead to more effective issue detection and case selection. Certification enables the governance of complete, consistent, comprehensible, correct, and authoritative sources by establishing operational metrics. There can only be 1 Role that is Responsible for a Task.

Data Connection: Connect the data to each other as well as users to the data. Building out the metadata repository helps expose data elements to a larger audience. Increasing data accessibility across the agency helps to gain the ability to measure ROI and compliance impact across the end to end process. There can only be 1 Role that is Responsible for a Task.

Data Consumption: Present the data in the proper/desired state for the recipient to efficiently make the right decision. Data is effectively turned into information, used to innovate new methods/discoveries, streamline and automate retrieval processes through renovations, and intent individuals through motivation. Tools of data consumption focus on visual representations of dashboards, scorecards, queries, reporting tools, OLAP, or data mining. There can only be 1 Role that is Responsible for a Task.