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Leadership prefers to utilize third-party tools, such as Snowflake, which has both storage and ELT features.
The stability and performance remain issues.
Compared to Collibra Catalog, where the value is noticeable within six months.
It also plays a vital role in revenue calculations, net asset valuations, and other key factors that support customer data and investment data pipelines.
The investment we have made is tremendous; it has saved a lot of time and effort, and fewer people are needed.
The return on investment is very good, as I previously mentioned, because the development team has been reduced to half, and it has saved us around one hour per day since we switched to Informatica PowerCenter.
Consequently, we adjusted our processes to use Matillion Data Productivity Cloud only for extraction and ingestion, while Snowflake handled all transformations and jobs.
Due to the tool's maturity limitations, solutions are not always simple and often require workarounds.
Even after going out of service support, they still reached back to me whenever I raised tickets.
We expect more responsive assistance because they have the expertise since Informatica is their tool, but I don't see enough expertise on the Informatica support side.
The documentation is thorough, and anyone with minimal knowledge of ETL can easily understand it and work through errors.
I like the technical support provided by Informatica.
I have occasionally needed to communicate with the technical support of Informatica PowerCenter, especially when raising cases for complex mappings and performance optimization to identify bottlenecks in transformations.
They communicate effectively and respond quickly to all inquiries.
I have used the product over multiple systems and was able to write reports for large data sets without any performance issues.
As a SaaS platform, IDMC is quite scalable and provides complete flexibility.
There are many options available, and the licensing model is quite good, supporting our needs effectively.
In the cloud, scaling up and down becomes easy when working with cloud providers.
The scalability of Informatica PowerCenter is tremendous because we can install it on any of our employees' systems, and it handles each and every task very swiftly.
We can easily scale the memory and also the workflows.
Depending on the nature of data sets, volume, and mixture of different data, the scalability could be improved as manual code writing is still required.
The autoscale process works well, allowing the system to start another node automatically if the first machine reaches 80% capacity.
Stability is crucial because IDMC holds business-critical data, and it needs to be available all the time for business users.
There are substantial stability issues with Informatica Cloud Data Quality on the cloud.
I find the stability to be good, with occasional restarts required every two to three months due to glitches.
We are getting 100% uptime every day.
Informatica PowerCenter is stable and can scale well.
The product is very stable with very few issues encountered in production.
I feel whatever the tool does not have now, there is a feedback loop allowing us to request new features, and we continually ask for different ways to do things as we have a pipeline into the product management team.
The tool needs to mature in terms of category-specific attributes or dynamic attributes.
The current solution requires code-writing and tweaking, while other solutions offer material-level matches.
With Informatica PowerCenter, I am looking for an AI interface that looks at the underlying data model of the databases and the metadata of the tables, allowing the developer to provide instructions on what data sources to connect to and how to apply or create Transformations.
Utilizing more stored procedures from Oracle databases in an easy way would significantly boost performance.
Informatica Cloud and its support becomes quite expensive for the organization compared to peers such as SnapLogic or Netezza, which offer lower pricing.
Connections to BigQuery for extracting information are complex.
The main areas for improvement are AI features and scalability.
It ranges from a quarter million to a couple of million a year.
Informatica Intelligent Cloud Services is affordable for my specific use cases, with the pricing being rated three or four on a scale where one is very cheap.
Regarding pricing, compared to other tools I have worked with, Informatica offers competitive pricing, which I find not high in terms of starting strategy.
I find that the pricing and licensing for Informatica PowerCenter align with its quality.
The price of Informatica PowerCenter is high, especially for small and medium-sized businesses.
We haven't paid for it; our client had paid for this tool.
Matillion Data Productivity Cloud offers discounts and special deals, especially when dealing with high-volume clients or fewer existing clients in specific regions, like Spain.
The pricing is moderate, neither expensive nor cheap.
The platform's ability to pull in data from other platforms without the need for an additional integration tool enhances its appeal.
The connectors serve as the main functionality, making data integration processes more efficient by saving time and effort.
We could run data quality rules as part of Service Bus, which ensured the integrity of customer information before it was entered into our database.
The system supports real-time integration, which is essential for many of my tasks.
Informatica monitors can be used to monitor the jobs that we run, and if there is any kind of failure, we can diagnose it right away.
Another valuable feature is the use of Mapplets; if we have one mapping created that we want to use again and again for other workflows, we can create a Mapplet and save it so that we can reuse the mapping, reducing our workload.
The predefined connectors eliminate the need to write code for connectivity.
Matillion Data Productivity Cloud is effective for ingest functions, particularly when moving information to Snowflake and performing many transformations.


| Company Size | Count |
|---|---|
| Small Business | 51 |
| Midsize Enterprise | 27 |
| Large Enterprise | 155 |
| Company Size | Count |
|---|---|
| Small Business | 15 |
| Midsize Enterprise | 11 |
| Large Enterprise | 75 |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 10 |
| Large Enterprise | 11 |
Informatica Intelligent Data Management Cloud (IDMC) offers seamless integration of master data management, data quality, and data integration with a cloud-native architecture supporting multiple data management styles, optimizing data governance through metadata management.
IDMC enhances data synchronization and mapping tasks, utilizing a broad range of connectors to interact efficiently with data sources. Its precise address validation via AddressDoctor and intuitive navigation bolster user empowerment, delivering agility, scalability, and security in data governance. Despite its strengths, areas like ease of use, SAP integration, and reporting could benefit from enhancements. Connectivity issues and workflow complexities are noted, needing improvements in performance, support, and licensing cost. Users demand expanded ETL capabilities, real-time processing, and broader data source support to address growing data needs.
What are the key features of IDMC?In industries such as banking, healthcare, and telecom, IDMC is implemented for data integration, cloud migration, and enhancing data quality. Its capabilities are crucial for metadata management, lineage tracking, and real-time processing, ensuring high data quality and streamlined operations.
Informatica PowerCenter is known for its robust data integration, scalability, and user-friendly interfaces. It simplifies data processing with real-time capabilities, handling large datasets efficiently. Its adaptability with diverse sources makes it suitable for complex data environments.
Informatica PowerCenter offers extensive transformation options with features like flow designer, mapping, and error handling, enhancing development efficiency. Its GUI interface allows seamless integration across different platforms, making it suitable for managing extensive datasets. Traceability and support cater to evolving data requirements, while adaptability with multiple sources aids in driving strategic data outputs. Some areas for improvement include a more robust cloud strategy, better documentation, and improved API integrations. Enhanced automation and setup processes could further refine the experience.
What are the key features of Informatica PowerCenter?Informatica PowerCenter plays a vital role in data integration and ETL processes for building data warehouses. Industries like banking, insurance, and healthcare utilize it for extracting, transforming, and loading data into target systems, supporting analytics, reporting, and compliance. Companies often transition to cloud environments for enhanced scalability and efficiency.
Matillion Data Productivity Cloud offers a user-friendly platform for seamless integration and dynamic data handling, favored for simplifying ETL processes with minimal coding and ensuring robust performance in complex data tasks.
Matillion Data Productivity Cloud integrates effortlessly with platforms like AWS, Snowflake, and SQL databases, providing tools for efficient data migration, transformation, and cloud warehousing. It supports large datasets with swift management, making it valued for its graphical interface that eases ETL processes for non-technical users. Automation features ensure scalability and dynamic data handling across diverse sources, while security and cost-effectiveness enhance its appeal. Enhancements in database connectivity, interface design, and multi-environment support would refine user experience, with growing demands for real-time data capture, SAP connectivity, and frequent API updates.
What are the most important features?In industries like finance, healthcare, and retail, Matillion Data Productivity Cloud is implemented for transforming data operations. Companies leverage it for its speed in data processing and integration capability, facilitating rapid adaptation to data-driven insights crucial in these sectors.