Augmented Data Quality Solutions Reviews and Ratings

As we move through demoing for a new DQ tool. They have been extremely informative and helpful throughout this journey.

The overall experience with SAP Data Services has been good. It is easy to process the data and also helps in improving the data quality.

Talend Data fabric is best one as it has the great feature and easy to use.

Very customer focused organisation that see their success linked to their customers success

Oracle Enterprise data quality has proven to be a robust solution for maintaining data integrity within our organization. It's comprehensive set of tools and features ensure the data accuracy and consistency, contributing to our overall data management strategy. The benefit in terms of data quality and reliability makes Oracle Enterprise Data Quality a valuable asset for any enterprise seeking to optimize its data management practices.

The support we have received from the vendor has been exceptional. They prioritise our queries and nothing is too much trouble for them to review or consider. We have a fantastic working relationship with the Aperture technical support team

Data analysis is a need for every organization to be in the business in the current day scenario where tools like Microsoft Data Quality Services come in handy to manage your data. The tool helps in cleaning, transforming and enriching the data and helps in maintaining that the data is accurate and complete. This becomes very critical since this data is base for many business critical decisions. Users can create multiple knowledge bases/repositories of quality data (meta data creation and handling). The tool helps in matching, linking and removing any duplicate data within the data sets. It is scalable/adaptable for small/mid/large organizations. It provides excellent user interface which is easy to use for beginners and experienced professionals for data management. It integrates seamlessly with other Microsoft tools if there any pre existing Microsoft infrastructure.

Data quality delivers a collaborative environment for holistic vision of the quality of data assets. We have known it since its beginnings and with each new version they create, we have observed a tendency towards the implementation of AI that allows us to support the detection of quality problems with ease. DQLabs can integrate with our Data intelligence, expanding data quality and observability capabilities to enable a data governance and marketplace program.

We have been using Ab Initio at our organization for more than a decade and it was mainly used as a Data Integration tool for many large data intensive applications. Recently, we decided to implement a business critical Data Quality Platform for one of our ledger Transformation Initiative and Ab Initio Data Quality Platform was chosen for the same. It provides the ability for users to config real-time data quality rules, classify results into Detective, Preventive, Corrective, and take appropriate action accordingly. Platform is user friendly, ability to draft data quality rules at attribute level as well as feed level. It has a very powerful data visualization dashboard and provides integration capabilities with Tableau and Power BI. We have successfully implemented Data Discovery, Data Lineage and Data Quality under one platform which used to be three different maintenance heavy applications.

SAS Data Quality adapts to the target existing system setup. SAS Data Quality also resolves data quality issues without data relocation.

SAP Information steward is among the best tool out there for data quality solutions. We are able to control and identify risks with respect to data. It gives us a confidence as it provides information system layer for due diligence. It helps us in monitoring large amount of data in the organization.

One of the best Data Quality tools that I have used. Very small learning curve, was able to pick up and use it on the first day. Also extremely powerful, the team has been able to use it for complex data quality analysis as well as aiding document scraping activities. The ability to do a quick profile on the data for look for patterns has been invaluable too.

Very happy with this product. Offers tremendous flexibility with the vast number of connectors. Very impressed with the speed and performance. Easy for any developer to use. Very easy to handle various input and output formats and layouts. Scalable to handle a few records or billions of records.

Analyzing the data and processing it for the collection of useful insights with Precisely Data360 is very easy and hassle free. their user interface gives the best experience to analyse data with sweet and simple dashboards. their drag and drop option also feels like a very effective feature on their platform.

Great consultancy and follow up help. Reliable uptime and accuracy

great experience with vendor - pays attention to customer needs and wants. It is easy to get a hold of them if/when an issue arises and they do everything to get in resolved - troubleshooting, updating documentation, putting in escalation, etc.

Major issue with our data is duplicates which can be easily addressed by Syniti Match and I also manage territory alignment changes with this product. Its super powerful, and when it works perfectly, there is a lot that somebody can do with Syniti Match. The matching logic is by far the best feature of Syniti Match and it is better than anything I have seen from other tools.

The description of your data helps in data analysis, data prototyping, and since management. It is very easy to use.

Infosphere information analyzer goes beyond conventional data analysis tools focusing specifically on identifying and rectifying data quality issues it also excels in metadata management and thus providing a centralized repository for organizing and understanding the structure and context of enterprise data.

I always prefer MIOvantage to fulfil my data merging requirement and really a good experience with the platform. Backed by excellent support, its the go-to for businesses seeking efficient data cleanup and augmentation.