At many organizations, critical data resides on mainframe computers that could be of great value if it were more easily accessible. Traditionally, the best way to access non-relational legacy data like this was to perform an extract, transform and load (ETL) to a data mart.
Arbutus offers two alternatives that provide improved accuracy, faster access and fewer headaches - at a fraction of the cost - of using any popular ETL solution on the market.
The Problem: Mainframe Data ETL = Business Counter-Intelligence
The ETL process is costly, time-consuming and invites in errors. That's not an acceptable solution for today's executives and decision makers, who require real-time access to accurate data in order to make intelligent choices.
Here are just some of the risks associated with ETL:
- Most business intelligence (BI) and data profiling tools cannot directly or accurately access legacy data, so project managers start blind, guided only by source documentation and subject matter experts, if available
- Undocumented changes to the data format or field contents can be hard to identify and address, causing delays
- Data quality can be worse than expected, necessitating extensive ETL testing and data cleansing
- Legacy data can include unexpected or undocumented transaction types, or other anomalies, resulting in changes to the ETL and mapping
- Because the ETL process is time-consuming for both people and computers (i.e., mainframe cycles), often just slices of data are accessed, instead of all the necessary data, which can necessitate repeating the entire process all over again in order to obtain data missed the first time around
The bottom line is simply this: for many project managers, accessing and using legacy data is synonymous with risk, complexity and cost.
The Solution: Minimize the Challenges, Risks & Costs Associated with Mainframe Legacy Data
Arbutus technology offers two alternatives for a dramatic improvement over standard ETLs:
1) Use Arbutus prior to an ETL to reduce errors, project hours and risk
Arbutus uses a read-only copy of the actual source data - not test data - so you can identify and correct data quality issues immediately. This data-driven methodology reduces the costs and risks of ETLs.
Find out how Arbutus can increase efficiency while lowering your ETL costs
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2) Use Arbutus instead of performing an ETL, and get equivalent results at a fraction of the cost
Arbutus can read source data, such as relational or non-relational legacy mainframe, AS/400 (iSeries) or Oracle data, providing SQL and query access within standard Windows apps (e.g., Excel, Access or Crystal Reports), so you don't have to perform ETL.
Find out how Arbutus provides mainframe data access from your desktop
