Informatica Recognized as a Leader in Gartner’s 2020 Magic Quadrant for Data Quality Solutions for 13th Time

The Department of Culture and Tourism - Abu Dhabi Drives Data-Driven Digital Transformation with Informatica

Informatica Positioned Furthest on the Completeness of Vision and Highest on the Ability to Execute Axes

Informatica, the enterprise cloud data management leader, today announced that leading IT research and advisory firm Gartner, Inc. positioned the company as a Leader in its 2020 Magic Quadrant for Data Quality Solutions. Informatica is positioned furthest and highest on the completeness of vision and ability to execute axes, respectively.

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“Data and analytics leaders are facing intensive pressure to provide ‘trusted’ data that can help business operations run more efficiently and make business decisions faster and with greater confidence,” the report states, noting that data quality is also increasingly a necessity when amplifying analytics for better insights, and making trusted, data-driven decisions.

High-quality, trusted data drives digital transformation. Events in 2020 have disrupted business as usual, driving a paradigm shift to Data 4.0, where data intelligence is the foundation for change at scale. Whether it is to drive cloud modernization, accelerate new innovations, improve customer experience and retention, or enable governed data democratization for data analytics, the common theme is the need for trusted data and the pivotal role of data quality in delivering trusted data for these initiatives. Data quality tools enable organizations to identify, understand, and correct flaws in data so they can effectively govern and analyze data across operational business processes and decision making.

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This year’s Gartner report highlights the increasing demand for data quality solutions, “As artificial intelligence (AI) technologies mature and become more widely adopted, many data quality vendors have started incorporating them into their solutions. In building augmented capabilities, they are driving better automation in areas that have traditionally relied on intensive manual tasks such as data matching, cleansing and transformation.”

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