Sharp model for data warehouse project management diana

SHARP: A MODEL FOR DATA WAREHOUSE PROJECT MANAGEMENT Diana D. Cruz*
Executive Summary

SHARP is the acronym given to the data warehousing (DW) project in San Mateo. It stands for San Mateo Human Services Agency Analytical Reporting Project.

Every project will face a degree of risks and a good project management anticipates this in order to mitigate its effects. Several concerns are addressed below regarding data warehouse solution.

• One of the risks anticipated is the implementation of CALWIN in 2004.

A data warehouse project may be considered successful if it is on time, within budget,
deliverables are of good quality, and if it gives the users what they expect. So far in Phases I and II SHARP delivered; and at time of this writing, phase III is on track.

RECOMMENDATION FOR ALAMEDA COUNTY SOCIAL SERVICES AGENCY

needs of various groups, both within and outside the organization. This has always been a reality that, often, agencies have been "collectors" of a number of automation systems used to generate data. Government managers are clearly aware that getting accurate information in real-time would help tremendously to streamline the decision-making process and give management strategic insight to make better-informed decisions.

WHY DATA WAREHOUSE?

• Is Anyone Better Off - Number and Percent. Example: Measure the percent of One Stop Works participants employed in jobs with benefits 6 months after hire.1

There is no doubt that data is available. The question is how can data be extracted and used effectively and efficiently in light of the numerous existing automation systems, some of which have seen better days. To address this issue, San Mateo County Human Services Agency has decided to implement the data warehouse solution. The goals of data warehouse are to provide:

1 County of San Mateo, Outcome-Based Management, Templates with Instructions Program and Budget, Rev 11/06/01

SHARP, or San Mateo Human Services Agency Analytical Reporting Project is the data warehouse solution that started its development in February 2001. SHARP has shown the marks of a successful data warehouse project because:

STRONG MANAGEMENT SUPPORT

A strong collaboration between the county manager, ISD, and the agency provided a solid support to the DW project in terms of adequate budget to hire good people, acquire the right hardware and contractors, and choose the right products and tools. The San Mateo Human Services Agency (agency) saw the importance of developing foundational support for the DW project by getting through the issues with the county information services department (ISD).

A significant difference in the SHARP DW process compared to other counties is the time spent on the back end of the DW process. Another county made a mistake of "dumping" data from different sources into the data warehouse and let the questions come in at the front end, making the user puzzle over numerous data "look alikes"; therefore, querying becomes a trial and error process. Spending time and effort at the back end prevents this.

To reiterate, the objective of data warehousing is to provide data extracted from diverse sources, translated into a common data model and merged with existing data. Inconsistencies and differences are eliminated and resolved at the back end of the process to make it easy for the execution of user query.

• Requirements definition, analysis, design, development and implementation of DW; and • Knowledge transfer to agency staff

The scope of the agency (ISD) is to provide management and technical support.

SHARP-DW work plan is reasonably designed to avoid 12-hour daily work for the staff to keep a healthy and balanced team.

The benefits of having a well-developed plan are an accurate budget, reasonable work plan, keeping a healthy and balanced team, and knowledge transfer.

• During the requirements sessions when business reports and performance measures are clarified and defined, and

• During the technical session when the data architecture is confirmed.

For Phase III, 39 OBM measures, 67 regular BSG reports, 8 Family-to-Family measures and 3 Phase II modifications are addressed. Phases I and II inte-grated data from the CDS and CWS, then JTA plus expansion of CDS and CWS, and in phase III, SMART, SMP, and GIS. Phase III is expected to roll out to endusers in the August 2002.

TECHNOLOGY AND KNOWLEDGE TRANSFER

One of the risks anticipated is the implementation of CALWIN in 2004. The agency takes a risk pursuing SHARP, even with the anticipated implementation of CALWIN, which will replace CDS, a system source included in phase I of DW. The concern is whether CALWIN will use the same elements as CDS or not. If not, CALWIN may be another phase in the SHARP-DW.

Since DW is new, the user may decline to use the system. In SHARP, the user is involved, from the beginning, in every step of the process, including conversion of business reports or performance measures into business questions, source data selection, data validation (through user testing), query tool selection and user training.

Data warehouse project management is a fast rising discipline. Despite this rapid growth, there is little expertise in data warehouse project management. The development and implementation of SHARP-DW is a good model for learning about data warehouse project management.

The success or failure of data warehouse lies in the effectiveness of its project management. Data warehouse projects can be considered successful if they are:

* Diana Cruz is a management analyst in the Administration & Finance unit of Alameda County Social Services Agency.