Deploying AI and Machine Learning Depends on Effective Master Data and its Proper Governance

Many companies have initiated AI and ML projects only to find that they haven’t established the foundation for success.  Implementing a comprehensive data management strategy with platforms that are needed is essential to make replicable and scalable success possible. Not to mention, Machine Learning technologies require consistent, valid and trusted data. So, that makes it possible to recognize patterns and tune a company’s operating model. This leads to deriving holistic benefits from such investments.

Machine Learning and Artificial Intelligence have made an incredible impact on how companies are able to manage their data and experiences. However, businesses like ours are there to ensure that you have access to this crucial information

In this must-see webcast, Michele Goetz introduced the fundamental requirements for AI and ML deployments based on real-life successes and failures within the industry. Michele is Principal Analyst, Business Insights, Information Architecture and Artificial Intelligence, Forrester. She serves enterprise architects, chief data officers, and business analysts trying to navigate the complexities of data while running an insight-driven business. Her research covers artificial intelligence technologies and consultancies, semantic technology, data management strategy, data governance, and data integration.

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