Key issues

Key issues:
Planning for your data warehouse begins with a thorough consideration of the key issues Answers to the key questions are vital for the proper planning and the successful completion of the project. Therefore, let us consider the pertinent issues, one by one,

Value and Expectations: - Some Companies jump into data warehousing without at assessing the value to be derived from their proposed data warehouse. Of course, first you have to be SON that, given the culture and the current requirements of your company, data warehouse is the most viable solution. After you have established the suitability this solution, then only can you begin to enumerate the benefits and value proposition, Will your data warehouse help the executives and managers to do Certification 70-341 better planning m make better decisions? Is it going to improve the bottom line? Is it going to increase mar kct Amy? If so, by how much? What are the expectations? What does the management accomplish through the data warehouse? As part of the overall planning process make a list of realistic benefits and expectations. This is the starting point.

Risk Assessment:- Planners generally associate project risks with the cost of the project. If the project fails, how much money will go down the drain'? But the assessment risk is more than calculating the loss from the project costs. What are the risks faced the company without the benefits derivable from a data warehouse? What losses are to be incurred'? What opportunities are likely to be missed? Risk assessment is broad and relevant to each business. Use the culture and businesses conditions of your company assess the risks. Include this assessment as part of you planning documents.

PLANNING YOUR DATA WAREHOUSE

PLANNING YOUR DATA WAREHOUSE

More than any other factor, improper planning and inadequate project management lend to result in failures. First and foremost, determine if your company really needs a data: warehouse. IS it really ready for one'? You need to develop criteria for assessing the value expected from your data warehouse. Your company has to decide on the type or data ware-house to be built and where to keep it. You have to ascertain where the data is going to come from and even whether you have all the needed data. You have to establish who will be using the data warehouse, how they will use it, and at what times.

We will discuss the various issues related to the proper Planning for a data warehouse: You will learn how a data warehouse project differs from, the types of projects you were, involved with in the past. We will study the guidelines for making your data warehouse project a success.

PLANNING AND PROJECT MANAGEMENT

CHAPTER 4 PLANNING AND PROJECT MANAGEMENT

CHAPTER OBJECTIVES

• Review the essentials of planning for a data warehouse
• Distinguish between data warehouse projects and OLP system projects
• Learn how to adapt the life cycle approach for a data warehouse project
• Discuss project team organization, roles, and responsibilities
• Consider the warning signs and success factors

As soon as you read the title of this chapter, you 'night hasten to conclude that this is a chapter intended for the project manager or the project coordinator. If you are not already a project manager or planning to be one in the near future, you might be inclined to just skim through the chapter. That would be a mistake. This chapter is very much designed for all IT professionals irrespective of their roles in data warehousing projects. It will show you how best you can fit into your specific role in a project. If you want to be part of a team that is passionate about building a successful data warehouse, you need the details presented in this chapter. So please read on. First read the following confession.

Although this conversation is a bit exaggerated, according to industry experts, more than 50°A, or data warehouse projects are considered failures. In many cases, the project is not completed and the system is not delivered. In a few cases, the project somehow gets completed but the data warehouse turns out to be a data basement. The project is improperly sized and architected. The data warehouse is not aligned with the business. Projects get abandoned in midstream.

Several factors contribute to the 1-ailures. When your company gets into data warehousing for the first time, the project will involve many organizational changes. At the present tune, the emphasis is on enterprise-wide information analysis. Until now, each department and each user "owned- their data and \yen: concerned with a set of their "own" computer systems. Data warehousing will change all of that and make managers, data owners, and end-users uneasy. You are likely to uncover problems with the production systems as you build the data warehouse.