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Artificial intelligence is reshaping how we work — but not in one single, unified way. Beneath the surface of the current hype, two very different AI waves are unfolding. The first is visible and noisy. It is filled with influencers, prompt guides, and off-the-shelf tools promising instant productivity gains. The second is quieter but far
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As we enter 2025, artificial intelligence (AI) will continue to be a major theme. From foundational readiness to advanced applications, organizations are both excited by and challenged with integrating AI into their operations. Based on our research at TDWI, here are four trends that I see shaping the AI landscape in 2025. 1. Preparing for
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AI enters the mainstream AI is on the mind of many organizations, and for good reason. It can provide a lot of value in terms of cost efficiencies and innovation. Generative AI has certainly added visibility to AI work that has been going on for decades. In a 2024 TDWI survey, for instance, generative AI
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As organizations compete with analytics, more often they realize that structured data alone isn’t enough. Unstructured data — i.e., data sets that have not been structured in a pre-defined manner — such as text data, audio data, image data, and video data can provide a lot of value. For example, unstructured data can help to
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At TDWI, we’re seeing that organizations are dealing with complex data environments. In our surveys we see that more than half of the respondents are already managing 10s or 100s of TB of data. Of that group, 15% are already managing petabytes of data. That data includes legacy data and primarily structured data, but also new
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It’s been a while since I’ve posted here. I plan to do that more regularly. So, stay tuned! Recently, TDWI published one of our Best Practices Reports on Responsible Data and Analytics. These are primary research reports that examine important topics in data and analytics. Responsible data and analytics considers the ethical, societal, compliance, legal,
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Advanced analytics is being deployed in a range of use cases across business units and industries, especially as data types and volume increase. One of the top use cases for advanced analytics we see at TDWI is predictive analytics to understand customer or operational behavior. Statistical as well as machine learning models are used to
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There are organizational and technology components critical for a business to succeed in becoming data-driven. On the organizational side, a key component to succeeding with data and analytics is to create a culture that supports these efforts. Companies that succeed are typically goal-driven, transparent, empowering, and collaborative. They have strong leadership that believes in data
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TDWI research indicates that if users stuck to their plans around predictive analytics, adoption would be at 75–80% versus the 35–40% we currently see. Predictive analytics is on the cusp of widespread adoption. Many organizations are excited to make use of the power of predictive analytics (including machine learning) because they understand the
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Since joining TDWI about six years ago, I have been following and reporting on our salary survey. The report quantifies and interprets the compensation, roles, responsibilities, skills, and experience of individual BI and IT professionals. It also provides detailed profiles of the 10 most common BI and data warehousing roles, examining age, gender, education, salary
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Fern Halper's data makes the world go 'round 