Databases
Generative AI
Power of Asking Questions
Published: December 30, 2024
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Rudyard Kipling wrote “I Keep Six Honest Serving Men” in 1902, referring to What, Why, When, How, Where, and Who. He was exploring the importance of curiosity and questioning, and how they can be helpful if used effectively. It is interesting how Kipling saw critical questions as mortals who must always serve the individual.
Unsurprisingly, asking questions is a fundamental skill required in most trades, e.g., a teacher must question whether students understand, a doctor must question how the patient feels, a scientist must question the status quo, a journalist must question the facts, a politician must question the policies, and so on. Businesses are no different, with startups asking what pain points to address, growth-stage companies asking how to scale, and large corporates asking which markets to capture. In all cases, asking questions is critical to staying in business.
First Quarter of 21st Century
Business intelligence is the traditional go-to approach to answering business questions. The idea is to hire a set of engineers and analysts, who gather the requirements, i.e., the questions and answers the business stakeholders are looking for, collect the data needed to serve those requirements, and create dashboards to answer the business questions. The process is repeated for follow-up questions, modifications, or new requirements.
Countless tools have been built to help collect data and squeeze it into dashboards, an art that BI teams have mastered over the years. No wonder typical enterprises deal with hundreds to thousands of dashboards, each taking days to weeks to build, thus justifying massive resources and budgets. But are those helping answer the questions? Are they helping to ask enough questions? Are they helping ask the right questions?
Effectively, businesses are maintaining an actual set of “Honest Serving Men”, typically way more than six, and relying on them for their questioning needs. While this has been the prevalent practice in the last quarter of the century, it is quickly getting outdated in the new age of knowledge workers and the knowledge economy.
Entering the Knowledge Age
“Increasing the productivity of knowledge workers is the most important contribution management needs to make in the 21st century.”
Peter Drucker, 2005
Knowledge workers need to think for a living, and thinking is closely tied to questioning. Therefore, knowledge workers need to ask all the time, and outsourcing this critical function to other entities not only makes them unproductive but also risks making them irrelevant. This is not a surprise for sales, marketing, customer, revenue, finance, or other teams who are stymied by data and BI teams for critical insights and decision-making.
Asking questions is critical for knowledge workers, and it is an iterative process for making any meaningful decision. A marketing professional looking for better conversion rates needs to understand their customer micro-segments and analyze which A/B experiments are likely to produce better results. Likewise, a clinical researcher needs to understand their patient population along multiple dimensions while a banking officer needs to correlate internal trends with external data. These knowledge workers need to be able to ask questions at will and that requires them to command the power of asking questions.
Why Generative AI Matters?
Generative AI is a powerful technology for interpreting natural language, and it can help transform raw enterprise data into processed information and ultimately into actionable knowledge. With generative AI, knowledge workers can look at facts, generate analysis, draw conclusions, and iterate quickly to get their job done, without relying on tedious and cumbersome processes at each step.
Tursio helps accelerate this further by bringing generative AI to enterprise databases, without any data movement or privacy concerns. Using proprietary query processing techniques, Tursio enables knowledge workers to ask advanced questions and generate rich analyses in natural language. The goal is to keep the “Honest Serving Men” employed at all times and truly entrust the knowledge workers with the power to ask questions that they deserve.
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