Data Warehousing
description
Transcript of Data Warehousing
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