BACKGROUND: MI Drilling Fluids is the world's largest drilling and completion fluids supplier to the oil drilling industry. Headquartered in Houston, the company is a joint venture between Smith International and Schlumberger. In 1998, our 3,300 employees serviced 8,700 wells in 70 countries, generating total revenue of $11.82 billion dollars.

PLATFORMS: We installed NoetixDW by Aris Software directly into our test Oracle Applications ERP: Oracle Applications version 10.7, Oracle database version 7.34 and an HP-K570 Server running HP-UX 10.2.

PROBLEM SOLVED: NoetixDW creates objects that enabled us to design, create and populate a custom Oracle Financials data warehouse subject area in less than two days. After having the Aris Software, Inc. (ASI) consultant guide us through the process once, I believe that any experienced developer or functional super-user could use the NoetixDW objects to design, build and populate custom data warehouse subject areas after one or two days of training. Last December as part of a data warehouse proof-of- concept, an ASI consultant arrived on our site, installed NoetixDW and designed, created and populated our customized data warehouse subject area within two days. It took me half a day to create the target report in Cognos, and the report ran in less than 30 minutes due to the data warehouse schema design. After some performance tuning by our DBA, the report now runs in less than two minutes. This report previously took a consultant eight weeks to create.

PRODUCT FUNCTIONALITY: When NoetixDW installs in an Oracle Financials database, it detects and stores Oracle Applications configuration meta data. NoetixDW then uses that captured meta data to generate functional help files, data warehouse DDL and views. By reviewing the NoetixDW help file with the ASI consultant, we easily determined which fact tables to include in our data warehouse subject area design. Next we drilled down in the help file to determine the desired fact table columns and associated dimension tables. We then edited and ran the data warehouse DDL generated by NoetixDW to physically create our data warehouse subject area. Finally, we used SQL scripts and the NoetixDW generated views to populate the data warehouse subject area tables.

STRENGTHS: The strength of NoetixDW is that users can roll out an Oracle Financials data warehouse subject area by subject area without needing to know much about the Oracle Financials schema or about data warehouse design. The process is very straightforward.

WEAKNESSES: Currently, NoetixDW only includes objects for the Oracle Financials General Ledger, Accounts Payables and Accounts Receivables modules. Order Entry is under development, but I'd like to see more modules.

SELECTION CRITERIA: We chose NoetixDW based on our requirements for an open technology that enables us to easily create and run financial analysis and trending reports against our customized Oracle Financials data warehouse subject areas. Also, this product is not expensive or time- consuming to install or learn.

DELIVERABLES: NoetixDW includes customized help files, data warehouse DDL, views, an Installation Guide and a Data Warehouse Designer's Guide. NoetixDW works with any extract, transform and load (ETL) tool, and ASI has partnered with Informatica. The Data Warehouse Designer's Guide provides logical schemas of the basic NoetixDW subject areas. It's useful to get a generic idea of what the product can do, but only after you install NoetixDW and get a look at the configuration-sensitive help file can you see the large number of choices available for designing customized subject areas.

VENDOR SUPPORT: Pre- and post-installation support have been excellent. Before ASI came to our site, we told them that we needed an additional subject area. They added new views and DDL to their product after determining that our request added value. They have returned phone calls and delivered on their promises.

DOCUMENTATION: The generic schemas in the Data Warehouse Designer's Guide are useful for users to develop ideas about the composition and priority of a data warehouse subject area roll out.

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