What is Data Management
Data management is the process of managing information through designs and policies of an organization (Rouse, M., 2010). Data managers have to make sure that their organization is in compliance with regulations at all times. Data management can be effective if the organization do the following: 1) Every individual is assigned his or her on responsibility, 2) Determine how the data will be stored and backed up, 3) Implement a data management plan, and 4) Determine how data will be modified (Penn State, n.d.). Knowing who is involved and what their job is with the data is essential for an organization in order to manage data. When managing data you have to know how ...view middle of the document...
HIPPA Privacy Rule federally protects individuals. HIPPA was designed to reduce health care fraud and abuse. HIPPA mandates health care information on electronic billing and make sure health information is protected and held confidential (California Department of Health Care Services). Information that is considered protected health information is any information from the patient's past, present, or future, including health state, provision of care, and payment information (Kangas, E., 2013). HIPAA applies to both PHI and ePHI. PHI is protected health information that is not electronic and ePHI is electronically protected health information. Anything that can identify a patient is considered PHI and need to be protected by HIPAA (Kangas, E., 2013). Identifiers are names, geographic subdivisions that are smaller than a state, dates, telephone numbers, fax numbers, electronic mail addresses, social security numbers, medical record numbers, health plan beneficiary numbers, account numbers, certificate/license numbers, vehicle identifiers, device identifiers, web universal resource locators, IP addresses, Biometric identifiers, full face photographic images, and any unique identifying numbers (HIPAA Definitions and 18 Identifiers, 2013).
Aspects of Data Management
The data model is one aspect of data management. Data modeling is an overall map of business data (Brown, C.V., Dehayes, D.W., Hoffer, J.A., Martin, E.W., and Perkins, W.C., 2012, p. 97). Data modeling is just as important for a business as a blueprint is for the actual building of a building. Data modeling shows business relationships between entities (Brown, C.V., Dehayes, D.W., Hoffer, J.A., Martin, E.W., and Perkins, W.C., 2012, p. 97). This is extremely important when an organization needs information on which salesperson process any given order. Data modeling involves methodology steps that identifies and describes the company data entries. Data modeling also involves notation to graphically show findings (Brown, C.V., Dehayes, D.W., Hoffer, J.A., Martin, E.W., and Perkins, W.C., 2012, p. 97).
Another aspect of data management is metadata. Metadata is data that describe other data (Tech Terms). Metadata is needed to understand data that is stored in the data warehouse. Metadata gives descriptive information on data sets, objects, resource, how data is formatted, and who and when the data were collected (Indiana University). Metadata describes the maximum lengths an attribute may have. An organization must have quality metadata in order to have quality data so that everyone can understand what exactly the data means (Brown, C.V., Dehayes, D.W., Hoffer, J.A., Martin, E.W., and Perkins, W.C., 2012, p. 97).
Access rights are another aspect of data...