Reliability, Availability, Manageability Analysis for ETL - Data Warehouse ETL Toolkit

A datawarehouse can have the best dimensional data model, a best-of-breed business-intelligence tool, and sponsorship fromthe highest executives. But it is not a proven solution until it is considered a dependable source for corporate analytical information.

The goal of a new data warehouse is to build a reputation for being a consistent, reliable data source to support corporate data analysis to empower the business. To be a success, the ETL and the data warehouse teams must fulfill three key criteria:

  • Reliability. The ETL process must run consistently, without fail. The data within must be trustworthy at any level of granularity.
  • Availability. The data warehouse must be up, running, and available for use as promised by the data warehouse manager during initial kick-off meetings with the sponsors and users. ETL jobs must execute and complete within the allocated load window.
  • Manageability. Remember that the data warehouse is never finished. It must have the capability to change and expand as your company grows. The ETL processes must evolve gracefully with the data warehouse. To achieve extensibility, keep processes as simple as possible; break down complex routines into smaller, simpler components. At the same time, avoid an upsurge of jobs to carry out processes. Moreover, a crucial part of designing the execution strategy is ensuring the ability to support the ETL. The ETL team must provide metadata for all components of the ETL and document recovery procedures for every failure scenario. If you are hand-coding your system, make sure you have the management skills and perspectives to control a long-term software development environment.

The ETL manager must appraise each phase of the data warehouse by using the Reliability,Availability, and Manageability (RAM) criteria to score the project. The jobs and scheduling approach must pass each of the three criteria to get a perfect score and earn the right to deploy. If no metadata or recovery documentation exists, points are deducted and the processes must be revisited and enhanced or corrected. Jobs that are overly complex making them virtually impossible to maintain must be streamlined to progress to the next stage of the lifecycle. Each deployment of the data warehouse must achieve a perfect RAM score before it is rolled into production.

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