Open Source Data Warehouses
Roger Magoulas, Director Market Research, O'Reilly Media, Inc.
Date: Thursday, 20 October 2005
Time: 10:45 - 11:30
Location: Foyer Room
Commodity hardware, faster, cheaper disks, and open source software now make building a data warehouse more of a resource and design issue than a cost consideration for many organizations. A robust analysis infrastructure can be built using open source components with no performance or functional compromises.
This talk covers a proven analysis architecture, the open source tool options for each architecture component, the basics of dimensional modeling, and a few tricks of the trade.
Why open source? Aside from the cost savings, open source lets you leverage what your staff already knows--tools like Perl, SQL and Apache--rather than having to procure and staff for the proprietary tools that dominate the commercial space. Topics include:
Data Warehouse Architecture:
Consolidated Data Store (CDS)
Condition, correlate and transform data
Multi-topic data marts
Multi-channel data access
Open Source Components
Open Source Database Choices
Data Movement: SQL/Perl/DBI
- fast, flexible
Data Access and Presentation: AJaX/Java/Perl/Ruby/SQL
- Template toolkit for ad hoc SQL
- Perl reporting; Spreadsheet::WriteExcel
- Visualization techniques
- Graphing Tools
Analysis: R (CRAN)
Organizing data for analysis
Natural language processing for creating category hierarchies
Aggregate tables and aggregate navigation
Using statistical techniques from other disciplines
The presentation should provide you with the basic architecture, toolkit, design principles, and strategy for building an effective open source data warehouse.
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