Data Warehouse /Business Intelligence

Program

ISMT Meeting

October 18, 2006

Program Plan – Program VisionHighway Management Information System (HMIS)

Conceptual Framework

Microsoft SQL Server 2005 DBMS Platform

Project Data

Finance Data

Highway Data

Meta Data

Legacy System

s

Data Staging

Data Warehouse

Vertical Line of Business

Systems

Financial System

Financial Solutions

Integrated Line of Business Solutions

Operations Analysis + Planning

Ad-Hoc Analysis

Data Mining

On-Line Analytical Processing

Proposed Concept of Operations

• Populating the Data Warehouse

FinancialData

ProjectData

Others

DataCollection

SOURCEOPERATIONAL

SYSTEMS Staging /ODS

Metadata

DW/BI ARCHITECTURE VISION -- APPLICATION

DataValidation

DataCleansing

ErrorReporting

DataTransformation

DataLoading

EXTRACT, TRANSFORMATION, LOAD (ETL) PROCESSING

Data WarehouseData Aggregation and Summarization

DW / BI Methodology

• Each project in the DW/BI program will follow a standard set of processes, focused on iteratively delivering new capabilities and business value

PROJECT PLANNING

- Project Definition- Scope Definition- Project Plan and WBS- Kick-off Meeting

ANALYSIS

- Analyze Existing Environment- Requirements Analysis- Data Analysis and Metadata Management- Architecture Gap Analysis- Define Quality Plan and Process

DESIGN

- Architecture Updates- Data Sourcing- Data Modeling- Metadata Population- DW Database Design- BI Analytics

DEVELOPMENT

- ETL Processing- DW Database Build- Standard Reports- Advanced Analytics- Warehouse Management Processing

QUALITY ASSURANCE

- Transaction Tracing- Data Quality Compliance- Aggregate/Summaries- SME Validations- User Test Training- User Acceptance Testing- Parallel Processing

DEPLOYMENT

- Deployment Readiness Validation- Release to Production- Release Certification- User Training- User Report Development- Post-Project Review

COMMUNICATIONS, PROJECT/PROGRAM MGMT, SCOPE AND CHANGE MGMT, QUALITY MGMT, RISK MGMT, CONFIGURATION MGMT

ITERATIVE DEVELOPMENT

Program Vision and Scope

Project 2. Project Financial Reporting

The second project will focus on adding more data elements that will support project financial reporting.

Possible New functionality includes:

•Project-level cash flow forecasting•Highway Division-level cash flow forecasting•Highway Construction Plan•OTC Reports•Additional Performance Measures•Additional data elements to expand analysis

Project 1. Performance Management / Project Financial Reporting

The major ODOT processes that will be addressed by the first project include:

•Highway Division Quarterly Business Review Performance Measures•Highway Division Legislatively Approved Performance Measures•Drill down and Ad-Hoc analysis of Performance Measures and related data•Project and Financial Reporting and Analysis

Program Vision and Scope

• Data sources for Projects 1 and 2 may include data elements needed from the following systems:– CPS – Contractor Payment System– PCS – Project Control System– PDWP – Project Delivery Work Planning– TEAMS – Transportation Environment Accounting and

Management System– FMIS – Federal Highway Maintenance Information System– and others

Business Intelligence• Standard Reporting – Library of reports developed

and validated by the DW/BI program, ready for use by authorized users

• Ad Hoc Query – Customized real-time queries determined “on the fly” to address specific questions

• On-Line Analytical Processing (OLAP) – Summarized data viewed from multiple perspectives for potential patterns or trends, with “slicing and dicing” option available to navigate to more detailed levels of view (i.e., by region by highway by segment)

• Managed Reporting – Automated process of enterprise-wide distribution of reports, often personalized by user or user group

• Dashboarding – Presentation of important information and functions that can be personalized to each user’s specific interests, particularly the user’s Key Performance Indicators (KPIs) and other performance measures

Business Intelligence• Scorecarding – Management-level quick view of

significant benchmarks, trends and anomalies• Visualization – Graphical display of data for

easier view of trends, often in the format of graphs, charts, flowcharts, maps and other visual aids

• What-if Modeling – enables users to derive and manipulate future results based on previous experience, as well as a defined set of assumptions. Modeling includes a variety of allocation formulas to support budget projections.

• Advanced Analytics – including data mining, identifies emerging patterns early, giving ODOT the opportunity to respond to changes in its operating environment