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The ability to effectively deploy AI into production rests upon the strength of an organization’s data strategy because AI is only as strong as the data that underpins it. Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models.
Access to high-qualitydata can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good dataquality.
Ben Fox has worked with data-driven organizations such as Toyota Financial, Washington Mutual, Disney, Activision Blizzard, and Electronic Arts, and has authored the book, Cooking with BusinessIntelligence. His major takeaway?
Enterprise data analytics integrates data, business, and analytics disciplines, including: Data management. Business strategy. Data engineering. DataOps. … In the past, businesses would collect data, run analytics, and extract insights, which would inform strategy and decision-making.
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