Business intelligence systems enable users to interactively view and analyze their data to make timely, accurate, information-based decision.
They give you in-depth knowledge of your business, at your fingertips; at the exact moment you need it. It transforms your data to help you make better decisions, lower expenses and increase your competitive advantage.
Denver Public Schools (DPS) provides K-12 education to the residents of the City and County of Denver, Colorado. DPS employs over four thousand teachers in over 150 schools, and educates approximately 74,000 students.
Our most recent project involved the development of a complete Microsoft centric Business Intelligence infrastructure, ranging from the architecture of a Data Warehouse and OLAP cubes through the development of a web based analytics and reporting portal. The system captures key student, employee, and financial data and provides performance metrics and analytical insight to all levels of the organization.
CarpeDatum also completed the development of a cash flow forecasting system for a teacher compensation trust fund known as “ProComp” using TM1. The system projects cash flow and provides sensitivity analysis based on a variety of inputs including; employee salary and incentives, employee turnover, interest rates, inflation, and tax collections. DPS uses the system during negotiations with the teachers union to determine changes that can be made to teachers compensation while ensuring the solvency of the trust fund.
CarpeDatum, Inc. was asked to create a robust financial planning and analysis solution for the ProComp project. Using the TM1 OLAP system to improve existing processes and tackle each ProComp challenge, CarpeDatum’s solution provided:
The main challenges of this project were the ability to share information and utilize the same system tool to calculate salaries and funding requirements, for both contract negotiations and maintenance of the ProComp trust fund solvency.
Calculating and tracking the movement of participants from the traditional pay system to ProComp, and computing their salaries in a two-dimensional worksheet was problematic due to the number of metric variables and the volume of data. The inherently multi-dimensional problem was simplified using an OLAP database. OLAP combined the ease of use and end user programmability of the spreadsheet, with the data handling and data-integrity strengths of a relational database.