Metrics That Should Be Developed To Measure The Performance Of A Data Warehouse In The Following Environments: 1) Health Care, 2) Retail And 3) Pharma.

1525 words - 6 pages

In most of the Database guide papers, eight performance-based metrics were used to communicate areas of concern to the data warehousing vendor. Also, the ninth one was developed as a weighted average measure using four of the eight metrics, which were deemed the most critical to the organization assessing data warehouse performance to determine how the vendor stacked up relative to data quality and systems quality.The nine metrics that were developed to measure Solectron's, which is a major contract manufacturer in the electronic industry, data warehouse performance are;1. CompletenessTotal Complete = [((#Recordsi)/(Total #Records Expectedi) x (#Records Expectedi/Total #Records in all tables)) x 100.This metric is supposed to serve the firm better than a simple binary yes/no in measuring the weighted average of each table in the data warehouse. It also measures the percentage completion during an Extract -Transfer- Load (ETL) and/or refresh process. This metric also, and helps identify any possible SQL problems within a particular table.2. ConnectivityResponse Time = #Users x (RTD% + TR%)Where Run Time Duration (RTD) in minutes = Hardware/DW sizeTransfer Rate (TR) = Actual Transfer Rate/Optimal Transfer RateThis metric measures connectivity by enabling the firm to identify and isolate underlying issuesincluding ISP transfer rates, data sources, and hardware issues.3. Data IntegrityData Quality Tool Rate/Manual = % AccuracyThis metric measures the avoidance of the tedious, resource intensive method done in the past.4. Usage Data from the Data WarehouseUsage Rate on Data = Most frequently used/TotalThis metric tracks the usage rate of tables, reports, and the overall data warehouse to identify any trends and/or problems that may occur, particularly during peak operating times.5. On-Time deliveryThis current metric is defined as: tables are on time if they are delivered by 7:00AM local time atthe sites to which they apply.6. Ticket Cycle TimeAverage of the number of days a ticket stayed open; that is how long was an issue unresolved bythe IT/data warehouse vendor before completion?7. User Hits on the DatabasesThe number of times per day (broken out by hour, and averaged for a week) that users "hit" thedata warehouse databases.8. Run-TimeThe number of minutes required to produce all extracted tables, by site.9. Weighted Performance MetricData Warehouse Performance = (0.40 X Data Integrity) + (0.10 X Completeness) + (0.30 X Connectivity) + (0.20 X Run Time)This metric is developed to determine how the vendor stacked up relative to data quality and systems quality.In investigations of many organizations that implemented data warehouses, it is concluded that perceived net benefits are associated with system quality and data quality. Management support and resources also contributed to organizational implementation success; however, organizational, project and technical implementation did not impact data quality. Database system's, hence data...

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