Data is Fundamental** |
A solid knowledge of the real world things or events is critical to recording them correctly. When these things or events are not familiar or understood, or even out of context, then their representation will surely be flawed. Also, the more removed from reality the capture of data and its context, the higher probability for errors. Second-hand or third-hand knowledge is a very big risk, as is the case when data is not captured directly from reality, but from another representation of reality that was captured from yet another representation of reality, and so forth. This would be like taking a photograph from a photograph of a photograph leading to a much distorted image.
Technology often takes on a life of its own, especially when it ends up driving the organization, like the tail wagging the dog. When deep in the weeds of technology, it can be extremely difficult to look up and realize what it’s all about and what we are really doing. It all boils down to the data that represents the real world in order to manage the current reality, look at past reality and/or to predict future realities. So it is really “all about the data,” not the technology. Technology is great, but it is still only the vehicle for the capturing, manipulating, managing and delivering the data. “If the data isn’t right, nothing is.” There cannot be a truer statement. As data professionals, we especially need to get back to basics and understand data from this real world perspective, outside the confines of computer technology, if we are ever going to have any hope to tame the data chaos.
Technology often takes on a life of its own, especially when it ends up driving the organization, like the tail wagging the dog. When deep in the weeds of technology, it can be extremely difficult to look up and realize what it’s all about and what we are really doing. It all boils down to the data that represents the real world in order to manage the current reality, look at past reality and/or to predict future realities. So it is really “all about the data,” not the technology. Technology is great, but it is still only the vehicle for the capturing, manipulating, managing and delivering the data. “If the data isn’t right, nothing is.” There cannot be a truer statement. As data professionals, we especially need to get back to basics and understand data from this real world perspective, outside the confines of computer technology, if we are ever going to have any hope to tame the data chaos.
Enterprise Data Model
"An Enterprise Data Model is an integrated view of the data produced and consumed across an entire organization. It incorporates an appropriate industry perspective. An Enterprise Data Model represents a single integrated definition of data, unbiased of any system or application. It is independent of "how" the data is physically sourced, stored, processed or accessed. The model unites, formalizes and represents the things important to an organization, as well as the rules governing them.
An Enterprise wide data model facilitates business integration. It enables the identification of shareable and/or redundant data across functional and organizational boundaries. Integrated data provides a "single version of the truth" for the benefit of all. It minimizes data redundancy, disparity, and errors; core to data quality, consistency, and accuracy.
The Data Model is the "starting point" for all data system designs. The model can be thought of much like an architectural blueprint is to a building; providing a means of visualization, as well as a framework supporting planning, building and implementation of data systems.
Data is one of an organization's most valuable assets. All current and future business decisions hinge on data. An Enterprise Data Model is essential for the management of an organization's data resource. The core principle of data management is order; applying order to the vast universe of data. To manage data is to apply order. According to the second law of thermodynamics; the universe and everything in it, continually heads toward chaos; it takes energy to bring order. The same holds true for data, left alone, it continually deteriorates to a state of disorder. It takes concerted effort to keep data in order.
There's a saying, "the journey counts more than the destination." The process of creating the Data Model, in itself, is important because it provides opportunities for the business to work together in understand the meaning, inter-workings, dependency and flow of its data across the organization. In the day-to-day operations, many never get an opportunity to "look up" and see the bigger picture; see the enterprise data view; where data comes from, its transformation, where it goes, what happens to it, and where they fit in. The modeling process gives this opportunity; bringing focus to data's importance. The "big picture" understanding and support from the business are essential in establishing a data quality program, data ownership, and data governance; all necessary within an enterprise data environment.
The process also provides the opportunity to build relationships and trust between Information Technology (IT) and the business. Often times the business feels IT doesn't understand. The data designers, representing IT, work closely with the business in the development of a Data Model,, gaining trust and providing assurance of IT's understanding and partnership. If the business is presented an EDM where they were not involved, the model has little meaning; resulting in a lack of ownership and commitment. The opportunity to build the IT-business relationship is lost. The Data Model and the process to create it, is essential for any organization that values its data resource."
An Enterprise wide data model facilitates business integration. It enables the identification of shareable and/or redundant data across functional and organizational boundaries. Integrated data provides a "single version of the truth" for the benefit of all. It minimizes data redundancy, disparity, and errors; core to data quality, consistency, and accuracy.
The Data Model is the "starting point" for all data system designs. The model can be thought of much like an architectural blueprint is to a building; providing a means of visualization, as well as a framework supporting planning, building and implementation of data systems.
Data is one of an organization's most valuable assets. All current and future business decisions hinge on data. An Enterprise Data Model is essential for the management of an organization's data resource. The core principle of data management is order; applying order to the vast universe of data. To manage data is to apply order. According to the second law of thermodynamics; the universe and everything in it, continually heads toward chaos; it takes energy to bring order. The same holds true for data, left alone, it continually deteriorates to a state of disorder. It takes concerted effort to keep data in order.
There's a saying, "the journey counts more than the destination." The process of creating the Data Model, in itself, is important because it provides opportunities for the business to work together in understand the meaning, inter-workings, dependency and flow of its data across the organization. In the day-to-day operations, many never get an opportunity to "look up" and see the bigger picture; see the enterprise data view; where data comes from, its transformation, where it goes, what happens to it, and where they fit in. The modeling process gives this opportunity; bringing focus to data's importance. The "big picture" understanding and support from the business are essential in establishing a data quality program, data ownership, and data governance; all necessary within an enterprise data environment.
The process also provides the opportunity to build relationships and trust between Information Technology (IT) and the business. Often times the business feels IT doesn't understand. The data designers, representing IT, work closely with the business in the development of a Data Model,, gaining trust and providing assurance of IT's understanding and partnership. If the business is presented an EDM where they were not involved, the model has little meaning; resulting in a lack of ownership and commitment. The opportunity to build the IT-business relationship is lost. The Data Model and the process to create it, is essential for any organization that values its data resource."
**About Noreen Kendle
Noreen was the Senior manager of Data Architecture for the Home Depot. With over 25 years of experience in information technology, primarily within data architecture, she has worked within the communication, financial, manufacturing, health, non-profit, retail, graphics, and travel industries. Noreen has extensive industry experience leading the development and implementation of data architectural initiatives including: enterprise modelling methodology, master data, enterprise data management, data ownership, enterprise data integration, data quality, enterprise business intelligence, metadata, data governance, and physical design.