Dimensional Lifecycle Road Map

Dimensional Lifecycle Road Map

            As we know, data warehousing requires the technological knowledge as well as the knowledge of business processes to build an efficient data warehouse, we follow certain life cycle to build our data warehouse. These steps manages our workforce to develop an efficient data ware house and most likely yield greater productivity out of our data warehouse, if followed wisely. Therefore, we can conclude that the dimensional lifecycle to build data warehouse acts as a road map to successfully build an efficient data warehouse (Kimball, Page 332).

            The lifecycle starts with the project planning and goes through numerous process of figuring out the requirements that contains technical as well as analytical requirements to develop and constantly maintain and grow the data warehouse.

            The first step in data warehousing life cycle starts with project planning. We need to access readiness of our organization if they are ready to proceed ahead for the project (Kimball, Page 334).

            If we take an example of a video store that is growing day by day and we felt as if we need to create a data warehouse for the business then we also need to figure out if creating a data warehouse is feasible or not. We need to consider culture and scoping of the video store (Kimball, Page 336). We need to see the cost of building the data warehouse and benefit that we get out of it. Then, we need to see if it is worth investing money on data warehouse for our store. We can hire individuals that are passionate about videos as well as sound on the database and data warehouse technology.

            We need to develop a project plan which would ensure our progress on the project life cycle that has certain time frame to accomplish the task and the task that we already accomplished.

            The second important phase of our life cycle is requirement definition. We need to find out the information that we need from our data warehouse, so that, the top level executives would find it easier to make a smart decisions to be productive and stay at the top in the competitive market. We can look at the current database of the video store and gather information for the questions that would not be answered correctly by our current database  which would hamper our productivity for the store.

            We can also set the requirements by asking questions to the dimensional model that we create for our store. The question would be the question that the top level executives would want the answer for the store to be more productive. Example of one requirement for our store would be, "How many people come to our store with our ongoing marketing promotions?".

            We need to document the requirements we come up with. We need to have the requirements for architecture we would have for our data warehouse. We need to create a dimension table and a fact table for the requirement we come up with.  We should also find out the analytical requirements for our video store.

            We finally deploy the data warehouse and keep on performing the maintenance and growth because with time, our requirements and business process changes and we need to accommodate the change. This is a never ending process and there is always a scope for change in the data warehouse.

            Basically, data warehousing process seems to be more organized with the application of dimensional lifecycle road map that only helps the team responsible to build the data warehouse of the organization. This life cycle doesn't have a hard and fast rules and could be different for different organizations. It is just a guideline for the project team members and the project managers which proves to be yielding productivity and they are followed by many organizations. I personally, feel that this is very helpful for the members of the data warehouse team to accomplish the milestone and deliverables on time and with greater efficiency.    

Works Cited:

Kimball, Ralph, and Margy Ross. The Data Warehouse Toolkit: the Complete Guide to      Dimensional Modeling. New York: Wiley, 2002. Print.

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Goals of data warehouse

May 10, 2011

Goals of data warehouse       

            Data warehouse is a process of extracting the useful data out of massive database which is very helpful for the top level management to make decisions and get the required information for the further analysis of the business process. It looks at organization's data from the bird's eye view and gives us the clear picture of the overall organization.

            The data warehouse should present the organization's information clearly, without misleading the decision makers. For example, sales database would only look at the sales transaction of the customer and may conclude that the customer is loyal to the company but, the information about the same customer from the accounts database may show that the customer we thought loyal, actually was late on payments and is a burden for our business. Hence, the overall data, combining all the departments is very crucial and important for a business to be successful. Therefore, we need to have organization's data presented clearly to the top level management for correct decision making.  

            We need to make sure that an organization's data and information are easily accessible to the users (Kimball, Page 3). The tools that we use should be easy enough for our staffs to learn or use it. We also need to make sure that the reports we generate out of the data warehouse is not complex for the managerial staff to understand. We need to hide the complexity and show the report in simple form. This makes the information accessed easily, and we can except good decision making for the profitability of our business.

            Business process is changing and every day we have more advanced technology being introduced into the market. We can't stop the advancement in technology and the change in business process. Rather, what we can adapt is, we can make data warehouse adapt to the future change in technology and also the business processes. For example, if our business operates individually only in one location but has a mighty probability that it would expand its location in future then we must make data warehouse adaptable for many branches to operate. This would save time and money for our business, even though,  return on investment at that particular time seems to go against it.

            Once of the most important aspect of data warehousing is security. It contains reports and analysis of the overall business and this information is very sensitive. If it reaches our competitor's hand then they could use it against our business. Hence, we need to make sure there are no loop holes in our system for the hackers to enter and compromise our information.

            The main purpose of data warehouse is to provide decision making ability to the management. Therefore, it must serve as the application for the managerial staff to make decisions based on the facts given by the data warehouse. For example, the manager for sales department of a video store is confused about if he wants to introduce a sale for the videos older than four months. He should get the facts from data warehouse if it is either beneficial or not to introduce a sale. Hence, they should help make decisions that should eventually yield profit for the business.

            It doesn't matter if we build a very good data warehouse system which is very efficient, unless the users that use the warehouse accept it (Kimball, Page 4). It is very important because if they avoid using it then the data warehouse would not be able to give the results it should have given. This means that we need to build a data warehouse that would be accepted by the users using it. Therefore, in the process of making data warehouse requirement, we need to see the technical knowledge of the users of the data warehouse and make it suitable for the users to use it.

            The most important goal of building a data warehouse is to make the business owners happy.

            How can we make our business owners happy?

            The answer is not with our words but with our works, by building an efficient system that would analyze the overall data of our business which is free of problems and can be trusted. We need to constantly develop and maintain the data warehouse so that they can make important decisions based on the facts shown.

            Basically, in today's information economy, the most important goal of data warehouse is to analyze all the data in all of the database of our business and come up with a overall view of our business organization to dump some of the unnecessary information and look at the overall aspect of the organization to make better decision for better business management.

Works Cited:

Kimball, Ralph, and Margy Ross. The Data Warehouse Toolkit: the Complete Guide to      Dimensional Modeling. New York: Wiley, 2002. Print.