Find out in this report how the two Data Quality solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Ataccama ONE Platform is a comprehensive data management and governance solution designed to address the challenges faced by organizations in managing and leveraging their data assets. Its primary use case is to enable organizations to gain control over their data, improve data quality, and ensure compliance with data regulations.
The most valuable functionality of Ataccama ONE includes data profiling, data quality management, data integration, master data management, and metadata management. These features allow organizations to understand the quality and structure of their data, integrate data from various sources, create a single view of their master data, and manage metadata to ensure data lineage and governance.
By leveraging Ataccama ONE, organizations can achieve several benefits. Firstly, it helps in improving data quality by identifying and resolving data issues, ensuring accurate and reliable data for decision-making. Secondly, it enables organizations to streamline data integration processes, reducing the time and effort required for data integration projects. Thirdly, it facilitates effective master data management, enabling organizations to have a consistent and accurate view of their critical data entities. Lastly, it helps organizations in complying with data regulations by providing data lineage, data privacy, and data governance capabilities.
Informatica Cloud Data Quality Radar is a cloud application that quickly identifies, fixes, and monitors data quality problems in your business applications—wherever they are, in the cloud or on-premise.
This easy-to-use, browser-based tool empowers line-of-business managers to take ownership of the data quality process so business can maximize the return on trusted data. Informatica Cloud Data Quality Radar enables you to quickly assess the strengths and weaknesses in your data, to track improvements in the data over time, and to calculate data quality scores for objects and field entities with the flexibility to filter and drill down on specific records for better detection of problems.
We monitor all Data Quality reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.