It should be no surprise that today’s insights-driven organizations have high demands on data and analytics. How do you broaden the reach of BI to make it easy for non-technical business users to get more answers on larger and more varied data sources, including to questions they may not have thought to ask?
Many organizations are adopting advanced technologies such as AI and machine learning (ML) as part of an all-encompassing analytics strategy to recognize patterns in bigger and more varied data volumes, uncover automated insights, and guide people through decision-making cycles. So, what’s next for AI and how will it impact your data-to-insights pipeline?
Check out the brand new TDWI Checklist Report to learn how:
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AI uncovers deeper insights that give users new perspectives on business questions
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Organizations apply AI to enable more efficient and relevant data discovery
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New use cases are made possible with these technologies
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AI, NLP, and search are used to broaden the reach of BI to non-technical business people
Analytics applications more often include built-in AI/ML algorithms to make it easier for business analysts and users to find insights
