The Bureau of Labor Statistics estimated in 2021 that employment in data science-related jobs would grow 36 percent by 2031 as various industries look to use data to streamline day-to-day operations.To meet the growing demand for data professionals, education policy advocates are lauding the recently proposed Data Science and Literacy Act, which aims to strengthen and expand data literacy and science programming in K-12 schools and higher education nationwide.

Data analytics can provide a huge competitive advantage for companies, and any technology that delivers analytical capabilities more broadly within organizations presents a lot of potential value.That's exactly what self-service analytics is designed to do.Self-service analytics tools allow business users who are not trained in analytics or data science to perform queries and generate reports on their own, with minimal or no need of support from the IT department.

IMARC Group has recently released a new research study titled " Data Science Platform Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028 ", offers a detailed analysis of the market drivers, segmentation, growth opportunities, trends and competitive landscape to understand the current and future market scenarios.

News from eight different companies shows analytics, data management, streaming data and AI are increasingly intermingled, all in the cloud.

It's easy to think of LLMs (large language models) as just 'hallucinating' or mere generators of text.A glorified LSTM so to speak.While there are some limitations of LLMs (and indeed they are evolving), a far more interesting question to explore is: How can LLMs be used in enterprise applications?In many ways, enterprise applications of LLMs can overcome some of the problems.

The Future of Data Science Lies in Automation
Parts of data science can be automated today, and more may be automated soon.Data science is a wide-ranging field that has been successfully applied in both scientific and business domains.Companies have been heavily investing in all things data in their quest to become data-driven.

Data analytics is a powerful tool for procurement professionals to unlock value in their data - but it's far from a one size fits all.By understanding the different types, and their relevance to procurement, leaders and professionals can make informed decisions that lead to more optimised processes and better outcomes.

Are you eager to learn about data science and machine learning but need more confidence to get started?You're not alone!Data science and machine learning can be overwhelming topics for anyone just getting going with very little background knowledge.But don't give up hope - it's totally possible to become an expert in this area even if you are a beginner, with enough time, effort, and useful resources.

As data scientist hiring continues to boom, many organizations report sustained difficulty finding, attracting and retaining data science talent.Even as initiatives to upskill quantitative professionals grow, machine learning literacy remains low in many organizations.Chief data and analytics officers, or CDAOs, must build development paths that support budding citizen data scientists with the right tools, training and structure.