Informatica PowerCenter, an Enterprise ETL Tool
Anonymous | TrustRadius Reviewer
December 19, 2018

Informatica PowerCenter, an Enterprise ETL Tool

Score 10 out of 10
Vetted Review
Verified User
Review Source

Overall Satisfaction with PowerCenter

Informatica PowerCenter provides a robust Extract Transform and Load (ETL) engine that is both scalable and flexible. I have implemented informatica PowerCenter for a variety of government agencies to meet a variety of different requirements. Informatica is used to integrate data, build data marts or data warehouses to support decision support systems, disseminate data or even ingest data into COTs applications. It is all about being able to move or transform your data so it is usable by your business.
  • Informatica is a proven enterprise ETL tool that scales and provides a graphical interface to code your data mappings.
  • Reading, Transforming and Loading Data to and from databases.
  • Process incoming data such as messages in real-time.
  • Data Cleansing.
  • Web Services / Services.
  • Modeling your data models.
  • Positive - Easy to maintain processes built in Informatica Power Center.
  • Positive - Rapidly build and deploy ETL data mappings.
  • Positive - Develop the overall workflow process to run all ETL processes for the project.
  • Negative - Informatica Power Center can be a bit expensive, so your application needs to warrant the enterprise support.
Alternatives:
  • Talend (open source, cheaper, longer development time, not intuitive UI, harder to troubleshoot, etc)
  • Pentaho (cheaper, better talend)
  • Oracle Integrator (similar as capabilities Informatica PowerCenter, but not as mature, similar cost)
Informatica PowerCenter is great for creating data marts or data warehouses in star schema.

Informatica PowerCenter doesn't provide native capabilities for data cleansing, such as USPS zip code validation. You must code this manually.

Informatica PowerCenter Feature Ratings

Connect to traditional data sources
9
Connecto to Big Data and NoSQL
8
Simple transformations
9
Complex transformations
9
Data model creation
5
Metadata management
8
Business rules and workflow
7
Collaboration
8
Testing and debugging
8
Integration with data quality tools
7
Integration with MDM tools
6