IT Project – Data warehouse Or Decision Support System – Complete Project Plan Answer

Section 1: Project Summary

Project Purpose

To create a decision support system at an organization level which will meet the reporting and data needs of majority of ket stakeholders e.g. Top and Middle Management, CFO, Finance and Accounting Department, Planning and Strategy group.

Business Case

MIS has served the company for the past five years. This has served the purpose of the organization so far. But, with the growing competition and globalization, there is a need to do better and faster reporting which will help the company to bring its products into the market quickly and thus create a niche for the company’s products and services. We’ll be embracing a new data warehousing technology that will aggregate data from multiple sources and provide a single version of truth of the data and meet the reporting needs of all our key stakeholders within the company. We’ll be replacing the servers with six new multiprocessor servers loaded with RAM, redundant drives, and faster, reliable tape arrays which mean faster, more reliable, more productive work for us all.

Project Results

  • Data warehouse system
  • 200 Report and cubes implemented for the company
  • All implementation complete by January 2013

Basic Milestone Timeline

1.1 Project planning and evaluation. 5-15-12 5-25-12
1.2 Infrastructure 5-15-12 06-10-2012
1.3 Phase 1 – Analysis 5-26-12 06-04-2012
1.4 Phase 2 – F2F Validation 06-03-2012 6-23-12
1.5 Phase 3 – Design 6-17-12 08-10-2012
1.6 Phase 4 – Development 6-24-12 11-02-2012
1.7 Phase 5 – Validation & Testing 11-03-2012 12-05-2012
1.8 Phase 6 – MTP 12-06-2012 12-23-12
1.9 Phase 7 – Transition & Documentation 12-24-12 01-03-2013

Project Resources

  • Budget: $130600 (2008 servers, client access licenses, consultants, training, Software and people cost)
  • On-site consultant

Project Constraints, Assumptions, and Risks

  • The project must be completed by January 31, 2013.
  • The project must not exceed $1, 50,000.
  • Our preferred vendors should be able to deliver our new workstations and servers on time without affecting the project schedule.
  • The learning curve for our employees to learn Cubes and Reports could affect productivity and efficiency.

Sections 2: References:

 Fairley, Richard (2009). Managing and Leading Software Projects. Published by John Wiley & Sons, Inc., Hoboken, New Jersey.

Verification and Validation Plan. IEEE Standard for Software Verification and Validation Plans, IEEE Standard 1012, ©2004.

Sections 3: Definitions of technical terms

Business dimension – The part of a business dimensional model that diagrams the business abstraction of data elements or attributes used to describe the major categories of reference data, such as customer or product.

Business intelligence (BI) – The collection of one or more reports or analyses, using data from the data warehouse, that provide insight into the performance of a business organization. These reports and analyses are typically interactive to enable further understanding of specific areas of interest. They are used to support business professionals in their decision‐making processes.

Business measures – The complete set of facts, base and derived, that are defined and made available for reporting and analysis.

Data cleansing – The process of verifying and correcting data using a series of business rules for validation, and specifying how to handle cases that fail the checks.

Data model – An abstraction of how individual data elements relate to each other. It visually depicts how the data is to be organized and stored in a database. A data model provides the mechanism to document and understand how data is organized.




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