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Louisiana DOTDEnterprise Data Warehouse
2007 Transportation Engineering Conference
Louisiana DOTDFebruary 13th, 2007
(Meeting Room 1)
Business Intelligence at DOTD
Overview
• Louisiana Department of Transportation and Development
• The Challenge
• Solution Area Business Case
• Source Systems
• Data Repository
• Reports and Queries
• Tools
• Summary
Louisiana DOTD
The Louisiana Department of Transportation and Development (DOTD) develops, implements, and administers programs and projects that impact the State’s highways, bridges, airports, waterways, rail and public transportation systems and administers an annual budget of over $2.3 billion.
DOTD needs to analyze information to manage its complex activities, but finds that the data needed for analysis is located in different systems, stored in different formats, and often difficult to access.
Louisiana DOTDTo meet this challenge, DOTD implemented
technology to enable:
• A more feasible mechanism to retrieve, report, export, or perform analysis on ad-hoc queries
• A “checkbook” view that shows the status of financial transactions
• Improved decision support for cash management practices, such as scheduling of expenditures
• Ability to easily generate key reports and query results for decision-makers.
The Challenge
• Disparate data sources
• Operational data stored in very “functional” silos
• Difficult for users to access
• Little integration between financial and project systems
• Manual process to extract and integrate data for reports when data from multiple systems required
• Data is not “clean”
The Challenge DefinedThe Data Warehousing system must provide:
• A more feasible mechanism to retrieve, report, export, or perform analysis on ad-hoc queries of relevant data, updated on a frequent basis to meet our increased reporting requirements due to the hurricanes
• The Process Improvement Initiative (Team 1) on Performance Measurements requirement for an automated method to generate an easy-to-retrieve and easy-to-understand representation of department performance on key indicators
What is a Data Warehouse?
• Historical data repository for reporting and analysis across time
• Combines data from multiple systems• Builds on dimensional data model that facilitates
analysis across different subject areas• Extracts data from operational systems, does not
change operational systems• Transforms operational data into meaningful
information• Applies business rules to data and eliminates bad
data• Single version of the truth, one common data
repository for all users
What is a Data Warehouse?Operational vs. Analytical
Operational
• Functionally Oriented
• Disparate
• Time Specific
• Volatile
• Redundant
• Incompatible
Analytical
• Subject Oriented
• Integrated
• Time Variant
• Non-volatile
• Detail Data
The Data Warehouse Architecture Separates Operational Systems and Analytical Systems
Operational
Data
Store
Operational
Environment
ETL
Analytical
Environment
Enterprise
Data
Warehouse
Business
Applications
ETL
Report
Queries
ETL
Data Flow
Solution Area Business Case
• Reporting around projects is very high priority• Complete “picture” of a project• Aggregate views with ability to “drill” to detail views
• Finances (expenses)• Project costs• Departmental Costs
• Cash management• Outlays and funding
• Human Resources• HR related to projects and finances
Solution Area Business Case
• Major Focus Areas• Finance
• Projects
• Source Systems• Eight systems
• Integrates data from major functional areas
• Satisfies needs identified during interviews
Source SystemsSOURCE DESCRIPTION FOCUS AREA
DAJR Daily Journal of Financial Transactions
Finance
SMGR/ESTI Construction Projects Projects/Finance
PMFS Capital Outlay Financing
Project/Finance
TOPS Project Master File Project
LETS Project Letting Schedule
Project/Finance
PCST Project Cost History Project/Finance
FAID Federal Aid Finance
Data Repository
• Utilize existing DB2 installation on z/OS
• Create two new databases• Staging – Data transformation and load
activities
• Production – End user production environment for reporting
• Managed by LaDOTD DBA’s
• No additional software acquisition required
Reports and Queries
Data Warehouse delivers reports designed to answer the questions defined and agreed upon in the business requirements phase.
Those questions were:• How was a project funded?
• For capital outlay funds, what are the budgeted, committed, encumbered, expended and balance remaining amounts?
• How much does/did a project cost?
• How were the funds spent?
• When were the funds spent?
ToolsReports were created and delivered
using Information Builders Web Focus. Tool benefits include:
• Managed report caching and delivery
• Security mechanisms and end user management
• Integration with the Web Focus Dashboard
• Simplified administration
• Ease of use for end users
• Report delivery via common web browser
• No additional software acquisition costs were required
Tools continued
• For ETL processes, custom SQL language scripts are run via our scheduling system. The ETL process document details the exact order the scripts must be run in and any exception processes associated with the scripts.
• While custom scripts were not recommended for long-term data warehouse projects with high volumes of data, they would suffice for our needs at this time.
• No additional software acquisition costs were required.
Future PlansIn FY 2005, we worked with consultants in
developing the base system; in FY2006, IT personnel continued adding to the architecture and adding additional data sources; in FY2007, we plan to use consultant assistance.
Expansion areas to be addressed include implementing additional performance indicators, more detailed payroll information and including maintenance data sources.
We will also plan to include additional operational data stores.
SummaryThe Data Warehouse project has provided the
platform to facilitate the analysis and reporting requirements that occurred as a result of hurricanes and process improvement.
Having a designated area (data warehouse) on the Intranet has eliminated the “where do I find it” search for DOTD employees.
With regard to timing, the Data Warehouse was able to address several high priority needs and heightened awareness for continued expansion.
The demands for data continue to increase while the tolerance to wait for results continues to dwindle.
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