Power trusted AI/ML Outcomes with Data Integrity


Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation. That’s why over 75% of enterprises prioritize AI and ML over other IT initiatives.

But before AI/ML can contribute to enterprise-level transformation, organizations must first address the problems with the integrity of the data driving AI/ML outcomes. The truth is, companies need trusted data, not just big data. According to Data Trends survey, 47% of newly created data has at least one critical error. That’s why any discussion about AI/ML is also a discussion about data integrity.

There are many steps toward trusted data. Breaking down data silos and integrating that data, ensuring data quality with accurate and inclusive data, and adding third-party data for critical context to the organization’s internal data. AI is increasingly becoming important for the environmental, social, and governance (ESG) initiatives as well. Assessing and automating the ESG data supply chain, making recommendations for data enrichment such as with wildfire data, demographics data, or with datasets for underrepresented groups are important for use cases in insurance, financial services, for non-profits, and more importantly help organizations remove bias from their data. Taken together, these steps — data integration, data quality and governance, location intelligence, and data enrichment — ensure access to data with maximum accuracy, consistency, and context driving trusted business insights derived from AI/ML.

Join Dr. Tendü Yoğurtçu, Precisely Chief Technology Officer (CTO), as she explores this critical relationship between data integrity and artificial intelligence (AI).

Find out:
- Steps to successfully manage data integrity and drive better AI/ML outcomes
- Why location intelligence and data enrichment is critical for trusted business insights
- Strategize and drive your AI/ML initiatives with a business outcome driven approach


Tendü Yoğurtçu, Ph.D., is the Chief Technology Officer (CTO) at Precisely. In this role, she directs the company’s technology strategy and innovation, leading all product research, and development programs.

Prior to becoming Chief Technology Officer, Tendü served as General Manager of Big Data for Syncsort, the precursor to Precisely, leading the global software business for Data Integration, Hadoop, and Cloud. She previously held several engineering leadership roles at the company, directing the development of the Integrate family of products.

Tendü has over 25 years of software industry experience, with a focus on Big Data and Cloud technologies. She has also spent time in academics, working as a Computer Science Adjunct Faculty Member at Stevens Institute of Technology.

In 2019, Tendü was named CTO of the Year at the prestigious Women in IT Awards, and in 2018 was recognized as an Outstanding Executive in Technology by Advancing Women in Technology (AWT).

Tendü received her Ph.D. in Computer Science from Stevens Institute of Technology, NJ, a Master of Science in Industrial Engineering, and a B.S. in Computer Engineering from Bosphorus University in Istanbul.

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