W8A Planning and Implementing a Data Warehouse Project - Essay Example

W8A Planning and Implementing a Data Warehouse Project ID W8A Planning and Implementing a Data Warehouse Project Project Objectives Planning and implementing an effective data warehouse project requires the application of good data analysis techniques that will develop a selective approach that separates data and ensures that its placement is done in a manner that makes it easier to access it when needed. The objectives of the study aim at supplying the decisions support system with the necessary information for the CEO to run the business in an effective manner. For an effective project, the following objectives can produce positive results. The general objective is to ensure a data system that handles data sorting through a proper classification approach that ensures easy access when needed for guiding the decisions of the CEO in running the company. The system must prove effective, efficient and economical in nature to fit the organizations resource capacity. Ensure proper, classified storage of data for easy access when needed. Proper sorting out of data in the different entry levels to ensure that each set of data goes under the right classification. To ensure an effective data system that supports the heavy data requirements of the organization in a flexible, effective, efficient yet economical manner. A data warehouse is a facility that allows the storage of data in a more improved manner that allows easy access for its consumption. Developing such a program enables decision makers find ease in their work. These objectives stated above will guide the Chief Executive Officer in ensuring that ease in data access is possible and through which the company can easily be saved. The CEO will also obtain data easily when he needs it and will develop plans easily on different aspects of the organization that will enable success in the management of the organization’s affairs. Project Planning and Initiation For the success of the project, a proper plan will need to be developed. A plan that covers the entire project ranging from the financial resources, the human resource aspect of it and the timeline within which the project will develop is necessary. The plan will guide the development of the entire project and see the project from initiation to its final stages. The preliminary stages of the project will include the identification of the general aspects that the project will cover, development of specific classification groups that will house each data in the warehouse, separation of data and filling in the different data groups developed. For ease in handling the work, each classification of data will base on the department from which the data is found. Each department will have their data organized and entered into their appropriate accounts in the data warehouse. Each member will play a role in the entry with data classified for each group supervised through entry to ensure it is placed in the right place in the warehouse. The resources for the project will include the human resource, the financial resources and the development of the equipments necessary to make the project successful. These will range from the necessary computers and software to house the data stored. The financial resources will be injected into the purchase of the requirements that may include stationery for workers that will take part in the project development. After all the necessary materials are in place, the different personnel will embark on the filtering process to ensure that the data they retain only pertains to their department. After which they will label it and give it classes that will be entered into the system in a systematic manner. Project Plan with High-Level Activities After the above process is developed and initiated, the project plan is then entered into proposed schedules with the tasks developed above identified in relation to the duration they will take to accomplish. The tasks as from above will all take different durations with different departments handling them. Tasks The major tasks of the project will include the following with their durations indicated too. Identification of the departments in the organization and the nature of information they carry. This will be allocated a week for each department to classify their data. Development of classifications for data in each department and creating a basic point of collection. The task will take three days for efficient classification. Separation of the data available and its departmentalization. Separation of data requires a longer time to ensure all the data in the company’s custody is arranged and placed in the right classification for ease in entering into the classifications. This task is allocated one week basing on the size of the company and the much information to be handled. Entry of data in each department after it is separated and organized. Based on the quantity of data existent and the team participating, this will take close to a week to ensure the data is entered in an organized way. Filtering of data: The data is then filtered and entered into the system through a system that identifies information that needs housing for longer periods and that which its use is exhausted. This activity is allocated a week. Entry of data into the warehouse will take close to a week with all the data available on the operations of the company entered. Implementation Approach and Methodology A number of implementation approaches exist for this project. These are not one time approaches but rather progressive to ensure appropriate results are obtained (PM solutions, 2014). These range from the phased approach, the big bang approach, top-down or bottom-up approach and pilot implementation approach among others. Relating to the nature of work that is at hand, the approach needs to consider all possible errors and avoid them. The approach needs to be systematic to ensure that the data is entered in an appropriate manner and none is missed. In addition, ensuring that all vital data is captured and the data not vital is discarded. The different methodologies that are applicable in this scenario include the phased approach and the top-down or bottom-up approach. According to the other approaches of big bang approach, which only aims at making one complete selection once, handling the whole work in once. The pilot implementation may also work for the project indicating the need to identify a sample of the whole data to invest into the pilot plan for a trial of the way the whole plan would work. The pilot implementation would work well in this scenario too allowing for the testing of the project to see any weak areas and have them eliminated. The phased approach is also applicable for the project. The phased approach applies the breakdown of the implementation into small phases manageable that would ensure all the data is managed well and classified to create a better option. The phases are then allocated time and each implemented at a time within a given schedule to ensure the work is all handled well. The bottom-up approach applies the implementation of the plan from the bottom level moving upwards. These indicate the movement that allows the data handled from the least centers of occurrence to the top. Based on the level of data handled and the effectiveness needed in the project, the phased methodology approach is applied in conjunction with the pilot implementation. The pilot implementation will be the first allowing for the identification of weaknesses in the project followed by phase approach that will allow data to be entered in manageable phases. Subjects Selected and Their Implementation Sequence The different subjects for the development of the project will involve all major aspects of the company including sales, customers, production sheets, supply chain information, records of systems and their maintenance aspects distribution schedules, defects in products, and the general accounting records. These subjects require consideration to give the new CEO the necessary information on leading the company to better performance and they will determine the size of the data warehouse created (Data Mining and Analysis, LLC, 2000). The implementation sequence will require a start with the accounting information that will provide the previous income statements, balance sheets, cash flow statements and budgets. These will reveal the performance of the company in the previous years and help in developing sales targets. This is followed by production schedules and sheets that will help follow on the production levels of the company. Through these, the CEO will rule out any dilution aspects and the production defects and help improve product quality. The products and services that are not performing well become easily identified and dealt with leaving the company with only products that make good revenue hence increasing the financial strength of the company. Through this, the defects in the products also become handled. The supply chain information provides the CEO with ability to understand the supply of materials for production and rule out any defects in that area. The records that pertain to the systems used in the company provide the CEO with a better understanding of any difficulties that the systems may pose to the development and productivity of the company. Based on these, the sequence will include the accounting information coming first followed by production schedules and sheets, supply chain information and finally the records on the systems that the company has employed in the management of all operations that range from production, distribution and marketing of the company products and services. Gathering Of Business Requirements for the Data Warehouse The business requirements in developing the warehouse for data will include the data storage tools such as computers that to host the data, the different software requirements for the warehouse and the personnel that will provide the human resource need to the warehouse. These are gathered from the end users for the development of the project (Data Warehousing Project Requirements, 2014). The different techniques will involve the examination of the different items on the market to identify the best for the job. Scaling through different computers and identifying their specifications to identify if they match those that the company has will help identify the necessary items for the warehouse. In selecting the participants in the exercise, the interview methods will be employed to identify the appropriate personnel to aid in the development and maintenance of the data warehouse. These will be selected on merit and level of experience in handling the different data aspects that the company requires. Their duration in the company will play a role in identifying their knowledge in the old system of data management. Application of these selection procedures will ensure an effective system of gathering requirements that will enable data aspects that will provide vital support to the entire project. Architecture and Tools Selected The architect and tools selected for the development of a data warehouse requires the development of a business model that favors the business environment that the company thrives in. the architecture will apply data mart as the tool to implement data warehouse development. The development of a data mart for each subject selected provides room for easy and manageable selection and storage of data based on the consideration of the most vital data first with the least vital last. A data mart refers to a form of a data warehouse that focuses on an identified functional area that includes a data mart for each of the subjects such as accounting data, sales production information, supply sheets and more (Oracle, 2007). These data marts out together will provide data in a warehouse. The Extract, Transform and Load approach will require the application of various tools in developing a data house that is consistent with the data mart requirements. The selection criteria will include the aspect of ease of usage and the effectiveness of the aspect employed. The application of tools that fit the ETL such as Data stage and Informatica Powercenter tools will provide an effective technique in managing the data warehouse development. Justification for Important Decisions and Selections: The decision to employ the phased implementation methodology is based on the ability of the methodology to ensure that the different data sets considered are selected in order and none of the vital data is left out. The use of phases will help break the work down into small manageable portions that prove easy for the data systems manager to handle. This approach ensures that no vital data is left out and the process is as effective as possible. The selection of data stage and Informatica tools provides the ETL process with a better data warehouse management system that will cover many aspects in relation to the partitioning of data, development of user interfaces, data encryption among many other options (Laureate, 2012). The application of these data management tools will ensure the simplicity of accessing data that will help the CEO in making decisions with regard to the development and proper management of the company. Current IT Infrastructure And Impact Due To The Implementation: Considering the current IT system that the company has applied, there have developed difficulties in the data management that have made it difficult for the CEO to make decisions basing on this system hence requiring the development of a data warehouse project that seeks to improve the ability of the management to obtain data fro decision making in the company. The existing infrastructure will be impacted by the implementation in a number of ways. The current infrastructure will require elimination to pave way for the consumption of the new system. The system seems to have embraced poor data management means that made the reporting aspect difficult hence the difficulty in making decisions using the system in place. The CEO seeks to enhance the current system with a better one to ensure that the system works well and provides him with the necessary support through easy application and development of vital reports for decision-making. The current systems do not prove effective in capturing the necessary data or seem to provide difficulty in access hence the need to discard them after the new project is fully implemented. Deployment (Roll-Out) Approach The development rollout will require the preparation of the different company departments on the usage of the different data warehouse aspects expected. The production environment is these departments of the company and rolling out the project requires that each department is equipped with the necessary machinery for application of the data warehouse project. The ultimate users of the company will require obtaining some training for their effectiveness in the management of the project and its effective application in the data management aspect in the organization. Training in usage of the data warehouse system will start from the department heads then followed by the department workers that will be equipped with the necessary skills to handle the project more effectively to avoid project failures. Anticipated Issues and Problems A number of issues arise during the implementation of the data warehouse project. These range from the over budgeting aspect of the project to the unhappy users. These are as detailed below. Some projects are considered failures starting from the points where the actual expenditure varies with the budgeted expenditure. These will require more resources applied that could prove the project more expensive than anticipated. The failure to implement some functions and applicability’s in the project may also prove the project a failure. In developing the project, agreements and plans to integrate a specific part of the company’s aspects into the project may not prove achieved that could lead to considerations of ineffectiveness of the project. Failure to meet the schedule could also pose a challenge to the project and its implementation. Another challenge attributed to the failures of the projects rotates around the unhappy users that may find the project as a waste of resources due to the challenges that may involve difficulties in using it and the different aspects that may make the users fail to apply the new system. These could result into poor resource application aspects that could lead to consideration of the project as a failure. For any project to successfully be integrated into the system of employees, a good number of employees should appreciate them and consume them. Among other challenges that the project could face include, unacceptable performance, poor availability of the project and meeting the schedules of the work program of the company, the inability of the project to expand into other areas (Adelman & Moss, 2000). The difficulty in application in other departments of the company, poor quality data reports, the lack of cost justification of the project, the complicated nature of the project to users and the failure of the management to realize the benefits of the project highlights the project failures. Addressing these failures will require effective project implementation process that will monitor the project at each phase to ensure that the project is actively managed. Consideration of all user needs of the organization in the development will also cover the user aspects and the training provided to the employees will support their understanding of the whole project. References Adelman, S. & Moss, L. (2000). Data Warehouse Failures. Retrieved from http://www.tdan.com/view-articles/4876/ Data Mining and Analysis, LLC. (2000). Data Warehousing Services. Retrieved from http://www.donmeyer.com/art2.html Data Warehousing Project Requirements, (2014). Task description. Retrieved from http://www.1keydata.com/datawarehousing/requirement.html Laureate, D. (2012). Data Warehouse Concepts. Retrieved from http://dwhlaureate.blogspot.com/2012/08/informatica-versus-datastage.html Oracle, (2007). Data Mart Concepts. Retrieved from https://docs.oracle.com/html/E10312_01/dm_concepts.htm PM Solutions, (2014). Project Management Methodology Implementation. Retrieved from http://www.pmsolutions.com/services/pmo-services/project-management-methodology/ Read More