Knowing the difference between data warehousing and data marts can be very confusing at times, especially when you see some people using both interchangeably. Both are referring to the storehouse of data. However, they differ in terms of the type of data that they are meant to house. Data warehousing is a broad central storehouse for all the historical data of a particular organization. Different data belonging to different units and departments of a company are grouped and stored in the data warehousing.
Having a data warehousing for a company will help to make a smooth decision on some matters. Data warehousing is mostly used for bigger organizations and companies. Datamart, on the other hand, is like a subset of data warehousing. It houses data belonging to a specific department in a company. This means every unit, department in an organization or company has its own data mart where necessary data pertaining to the operation of the department is kept.
In math class, you may have heard your teacher say the term “order of operations” which means that there is a certain order to doing a lengthy set of operations in a problem. If there are a number of multiplying, adding, subtracting and dividing in a math problem, then you should make sure that you work the correct parts of the problem first.
You do not simply start working a problem from left to right. You will go out of order. First, you work any part that is in parentheses. Then you work any part that has an exponent. Next, you work any multiplication or division parts whichever you see first. Then and last, you work the addition and subtraction parts whichever comes first.
The productivity on an employee can be calculated by specific metrics that is defined by you, and by consistent measurement. This is a concept of Data Management which itself falls under the domain of business management. The tasks that exist in data management contain the formation of data policies, data architecture, data identification, storage, and data security.
There are a range of different techniques that are used to ensure data control and its smooth flow. This goes from the processing, the use, and the deletion of the data. It is quite a huge area of work, which is still being researched upon.