Ataccama ONE vs. IBM InfoSphere QualityStage

Usage for enterprise wide data management and governance across wide range of user group. Ataccama ONE enables achieving higher data quality amongst the data products. It is a powerful platform that supports integration of several checks on different data sets that can be also consolidated in reports later on. Data discovery works quite fast and easy.

Incentivized

Standardization of data using rules for names and addresses. Possibility of building our own rules to standardize other data. Contruction of complex rules of matching and consolidation of data. Native integration with ETL tools and data governance.

Incentivized

• It is one of the leading data quality tools in the industry, in our opinion.
• Offers free data profiling.
• Integrates with other tools for complete end-to-end lineage.

• Create rules
• Standardization and normalization of data
• Integration with DataStage

Incentivized

• Performance in loading
• Reduction of pop-up messages

Incentivized

• Should include all the data profiling functionality
• Better features to tune matching capability
• Include AI to automatically recommend actions to improve processes

Incentivized

One of the key factors in our choice to onboard Ataccama was its usability - general end users have everything at their fingertips, it is not difficult for IT developers to setup the tool, and it has been an overall pleasure.

Support has been excellent to date - very user friendly and knowledgeable to help support our needs and issues as they arise.

Ataccama ONE is a designated tool for Data quality monitoring. Supports end to end. Quite easy to deploy. Alteryx is more about coding or almost as complicated while Ataccama ONE is a bit easier to use. Different interfaces. Many views automatically available for data sets in Ataccama ONE. Output is vizualized in the tool. While more data transformation is required in Alteryx.

Incentivized

It is a robust tool. It can be integrated with several DB. It works very well with DS. You can create your rules, and define the percentage of standardization or normalization

Incentivized

• Less data inconsistencies in the system enable processes to run smoother without interruptions

Incentivized

• Improving Data Quality
• Reducing costs due to better Data Quality
• Single view of customer / product
• Better data governance

Incentivized