Data Science and Machine Learning Platforms Resources

Artificial general intelligence (AGI) could be the best or worst thing ever happening to us.

This post is part of G2's 2023 digital trends series. Read more about G2’s perspective on digital transformation trends in an introduction from Emily Malis Greathouse, director, market research, and additional coverage on trends identified by G2’s analysts.

I recently attended the Tableau Conference, where I indulged my nerdiness for four days. As a self-described data science evangelist, I was thrilled to see autoML, natural language generation, and other advanced automation features be added to Tableau, one of the world’s leading data visualization and business intelligence platforms. 

Algorithms. Algorithmic. Machine learning. Deep learning. If you’re reading this piece, there is a good chance you have come across these terms at some point. An algorithm probably recommended this article to you. The umbrella term for all of the above is artificial intelligence (AI), which takes data of different flavors and provides you with predictions or answers based on that. There is a good chance you have benefited from this technology in some way, whether in a map application, image search from your favorite retailer, or intelligent autocomplete. 

Big data is the zeitgeist of the 21st century. The sheer volume of data available to businesses, government agencies, educational institutions, and consumers is virtually limitless compared to the days when computers were the size of computer science labs.

This post is part of G2's 2022 digital trends series. Read more about G2’s perspective on digital transformation trends in an introduction from Tom Pringle, VP, market research, and additional coverage on trends identified by G2’s analysts.

Back in 2019, I wrote my predictions of advancements we'd see in AI in 2020. In one of those predictions, I discussed the perennial problem of algorithmic explainability, or the ability for algorithms to explain themselves, and how that will come to the fore this year. Solving this problem is key to business success, as the general public is becoming increasingly uncomfortable with black-box algorithms.

Artificial intelligence (AI) is reinventing and reinvigorating the modern healthcare system by finding new links between genetic codes or driving robots that assist with surgery.

Accounting is one of the most important, yet daunting and expensive departments in almost all companies. Accountants oversee all financial operations of a business to help it run smoothly and efficiently. These include preparing and analyzing financial statements (e.g., cash flow, income statement, balance sheet), paying taxes on time, and maintaining the companies’ general ledger (GL). All these tasks require a great deal of human interaction that takes time and money; no matter how careful an employee may be, there is always the chance for human error, which could snowball and lead to devastating financial results in the future.

Automation and artificial intelligence (AI) are important, interrelated tools that help organizations streamline their processes and add intelligence to their workflows. They allow businesses to reach organizational goals by automating business processes, whereby they can increase efficiency and adapt to new business procedures. 

Remote work isn't the future. It's a current reality, with nearly 75% of U.S. workers working remotely at least some of the time, according to Owl Labs' State of Remote Work 2019 Report. Data scientists and other data professionals are no exception to the rule and are able to bring their work home with them if and when the need, or desire, arises. However, a switch to remote work isn't as straightforward as simply taking a work laptop home.

I’ll let you in on a (poorly kept) secret: The use of advanced analytics and other AI-powered capabilities that help users manage and interrogate data isn't new. The practice has been around far longer than the current bubble of hype surrounding AI has been inflating.

Forget what you may have heard. Machine learning isn’t some new concept or study in its infancy.