The data integration leader
November 19, 2019

The data integration leader

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with Informatica PowerCenter

Informatica Powercenter is widely used as an integration tool, very commonly across projects as well as across organizations. It addresses a whole suite of data problems, starting with data integration, data quality management, master data management, data masking, data virtualization, etc. The tool is extremely popular for its ability to gather data from disparate sources and homogenize it for consumption. There are several models it can be used in: Integrate data from data sources and landing it in a staging area for consumption, in data migration projects for moving data from legacy systems to newer infrastructure.
  • Data integration - Informatica has always been a leader in the data integration space. The company has maintained its position by innovative solutions, keeping pace with technology development, providing connectors to most of the common platforms, and improving on services with time. It has the ability to integrate data from multi-cloud, hybrid, on-premise infrastructure setup. The data integration can happen in batch or in real time. The performance of Informatica data integration is among the best in class.
  • Data migration - Informatica is widely used as a data migration tool. Lots of enterprises run their software on legacy infrastructure and at some point run into limitations associated with them. The large databases they use at that time make it extremely difficult to switch to the latest infrastructure and have a list of challenges. Informatica is great at addressing these challenges. It allows developers to create rule-based workflows that can be used to migrate any amount of data from old to the new infrastructure. Since Informatica is so successful at this, there is always use cases for reference and trained resources for executing a project.
  • Application Integration - The corporate world is full of mergers and acquisitions which lead to one company's IT assets being moved/merged to another one. This requires a huge amount of work to homogenize the two systems so they can co-exist without breaking each other. Informatica is great at building pipelines to integrate many disparate applications.
  • Data warehousing - Informatica is very commonly used for building data warehouse systems to fulfill the needs of enterprises and data marts to service requirements of individual requirements. This helps organizations' ability to use data sets for driving decision making. For example, Sales teams can decide how their previous sales efforts have performed in various geographies by analyzing the data warehouse data for sales.
  • Tool Management - Informatica over time has become a behemoth of data integration and warehousing world. It has built a vast array of tools to address various user needs. This does not bode well for the future looking at all the newer technologies which do not have so much of tech burden. Most new tools have a great cloud version where you can hop onto a URL, do your work and deploy it in minutes. With Informatica, you still have multiple client tools just to be able to deploy a single workflow and monitor as it runs. This can be both confusing and overwhelming to users.
  • Only commercial data integration - There is no open-source version of Informatica PowerCenter so it is not the most useful for small enterprises or individuals that wish to use it but can't afford the maintenance fee that can be quite a burden. Such users head over to open-source competitors that provide data integration services.
  • Lack of integration with other technologies - It is not very easy to blend in code from other languages like Java, Python, R, etc. Most of the tools these days provide such functionality making lives of users easier. Lack of such capability may cause users to build multiple hops in a data pipeline.
  • Inbuilt reporting - Although Informatica has been around for the longest time, it has not made the best use of all the data capabilities it has. With the amount of data flowing through power center, it should have been easy to provide some sort of reporting features that add immense value to a user's work. However, Informatica has not made great use of this opportunity.
  • In large implementation projects, the biggest contribution of Informatica has been to standardize the way things are done, get everyone across the organization on the same page in terms of what to expect, how long will the data processing takes, what data quality is to be expected, etc.
  • In projects with hundreds of data pipelines, Informatica makes it easy to define data pipelines that can be auto-configured instead of building one for each table. This greatly reduces the development effort and enables flexibility in massive data migration projects.
  • Informatica provides connectors to a multitude of database systems. It's connectors with Redshift, SAP/HANA have gone a notch beyond in order to tailor the data as per the needs of target systems and makes use of their strengths.
  • A negative impact has been that departments across the boards are highly dependent on the Informatica setup to deliver their data. Given the usually large scope of projects, the lead time for delivery of a solution can be significant causing losses, monetary or otherwise.
Informatica is a mature enterprise data integration platform for ETL jobs. Informatica has a suite full of tools other than PowerCenter that can be used for various use cases. It makes sense to know what the entire suite offers rather than just power center so large organizational needs can be better tailored to fit them. It provides great abilities to connect the maximum number of data sources irrespective of being SQL or no-SQL based. Informatica is also database agnostic and can work as well with a legacy database as with the latest ones. The range of connectors it provides enable fast processing speeds which are critical with the increasing amount of data being processed every day. we selected Informatica for all these benefits and to give the client organization a base to have a great data warehouse for years and not just for the short term.
Informatica power center is a leader of the pack of ETL tools and has some great abilities that make it stand out from other ETL tools. It has been a great partner to its clients over a long time so it's definitely dependable. With all the great things about Informatica, it has a bit of tech burden that should be addressed to make it more nimble, reduce the learning curve for new developers, provide better connectivity with visualization tools.

Do you think Informatica PowerCenter delivers good value for the price?

Yes

Are you happy with Informatica PowerCenter's feature set?

Yes

Did Informatica PowerCenter live up to sales and marketing promises?

Yes

Did implementation of Informatica PowerCenter go as expected?

No

Would you buy Informatica PowerCenter again?

Yes

Informatica PowerCenter, being a very mature technology leader, is well suited for large data integration projects where many different data sources exist and multiple departments need to use the data. In such cases, it is best to use a tool like power center to create a data warehouse and datamarts. These organizations usually can have in-house Informatica admins that can take care of software maintenance, contribute to performance improvement, troubleshooting, etc. They are also looking for a long term solution rather than a quick fix for data access issues. The tool may not be well suited for smaller organizations that tend to be more nimble and prefer more flexibility in building their technology landscape rather than being tied to a single tool that may define their overall data warehousing strategies. This also means that organizations do not have to maintain large software and employ dedicated people for doing that.

Informatica PowerCenter Feature Ratings

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