Companies are increasingly recognizing the value of data mining for deeper insights. According to a NewVantage poll, 97.6% of major global firms are investing in big data and artificial intelligence.However, obstacles to using big data analytics exist. According to a recent research, 65% of firms believe they have “too much” data to examine.
BigQuery Studio, a new tool within BigQuery, Google’s fully managed serverless data warehouse, provides a unified experience for editing programming languages like as SQL, Python, and Spark to run analytics and machine learning workloads at “petabyte scale.”
BigQuery Studio is now in preview mode as of this week.
“BigQuery Studio is a new experience that really puts people who are working on data on one side and people who are working on AI on the other side in a common environment,” Gerrit Kazmaier, VP and GM of data and analytics at Google, told TechCrunch over the phone. “It basically provides access to all of the services that those people need to work — there’s an element of simplification on the user experience side.”
BigQuery Studio is intended to let users discover, explore, analyze, and forecast data. Users can begin by validating and prepping data in a programming notebook, then open that notebook in other services, such as Vertex AI, Google’s managed machine learning platform, to continue their work with more specialized AI infrastructure and tooling.
BigQuery Studio allows teams to access data directly from wherever they are working, according to Kazmaier. In addition, measures for “enterprise-level” governance, regulation, and compliance have been included.
“[BigQuery Studio] demonstrates how data is generated, processed, and used in AI models, which sounds technical but is extremely important,” he noted. “You can push machine learning model code directly into BigQuery as infrastructure, which means you can evaluate it at scale.”
BigQuery Studio is a natural extension of Google’s broader plan to transfer AI-assisted businesses to the cloud. With global spending on public cloud services expected to rise 21% to $592 billion this year, according to one estimate, the IT behemoth is plainly bent on seizing as large a share of the pie as possible — as are its competitors.
It’s hardly an ill-advised strategy. According to Gartner, AI will be one of the top workloads driving IT infrastructure decisions through 2023. Tractica, a market research organization, predicts that AI will account for up to 50% of total public cloud services revenue by 2025.
“Generative AI really has the potential to unlock all of these hidden insights,” Kazmaier added. “What we’ve found is that AI really makes sense when combined with [a company’s] data.” AI is a method, if you will, of dealing with data… to maximize value.”