ETL

The basic reasons organizations implement data warehouses are:

  • To perform server/disk bound tasks associated with querying and reporting on servers/disks not used by transaction processing systems
  • To use data models and/or server technologies that speed up querying and reporting and that are not appropriate for transaction processing
  • To provide an environment where a relatively small amount of knowledge of the technical aspects of database technology is required to write and maintain queries and reports and/or to provide a means to speed up the writing and maintaining of queries and reports by technical personnel
  • To provide a repository of "cleaned up" transaction processing systems data that can be reported against and that does not necessarily require fixing the transaction processing systems
  • To make it easier, on a regular basis, to query and report data from multiple transaction processing systems and/or from external data sources and/or from data that must be stored for query/report purposes only
  • To provide a repository of transaction processing system data that contains data from a longer span of time than can efficiently be held in a transaction processing system and/or to be able to generate reports "as was" as of a previous point in time
  • To prevent persons who only need to query and report transaction processing system data from having any access whatsoever to transaction processing system databases and logic used to maintain those databases

Data Warehouse applications are designed primarily to support executives, senior managers, and business analysts in making complex business decisions. Data Warehouse applications provide the business community with access to accurate, consolidated information from various internal and external sources.

The Data Warehouse functions as a Decision Support System (DSS) and an Executive Information System (EIS), meaning that it supports informational and analytical needs by providing integrated and transformed enterprise-wide historical data from which to do management analysis. A variety of sophisticated tools are readily available in the marketplace to provide user-friendly access to the information stored in the Data Warehouse.

Data Warehouses can be defined as subject-oriented, integrated, time-variant, non-volatile collections of data used to support analytical decision making. The data in the Warehouse comes from the operational environment and external sources

  • Subject Orientation
  • Integration and Transformation
  • Time Variance
  • Non-Volatility
  • Data Warehouse Configurations
  • Business Case Development
  • Business Question Assessment
  • Architecture Review and Design
  • Tool Selection

Tools may be categorized according to the following data, technical, application, or support functions:

  • Source Data Extraction and Transformation
  • Data Cleansing
  • Data Load
  • Data Refresh
  • Data Access
  • Security Enforcement
  • Version Control / Configuration Management
  • Backup and Recovery
  • Disaster Recovery
  • Performance Monitoring
  • Database Management
  • Platform
  • Data Modeling
  • Metadata Management

Our employees are trained and experienced in the following ETL tools:

  • Informatica
  • Datastage
  • Ab Initio
  • ETI and others...