The U.S. Bureau of Labor Statistics predicts the demand for data scientists will grow by 22% between 2020 and 2030. The evolving nature of data itself exacerbates this talent shortage.

Data rarely comes in usable form. Data wrangling and exploratory data analysis are the difference between a good data science model and garbage in, garbage out.

Data is growing at an exponential rate, with Deloitte predicting it will reach 175 zetabytes by 2025—the equivalent of one billion one-terabyte hard drives. Our expanding data stores are helping ...

Define your data architecture: Once you understand what pieces of data are essential for your digital transformation project, then you can define how all those pieces of data must fit together to ...

Data Scientists are the life blood of your AI transformation, be it Machine Learning or the more popular Deep Learning projects. What was a field previously reserved for researchers and academia ...

Large-scale, well-organized, and open datasets are necessary for primary care–focused artificial intelligence and machine learning (AI/ML) research and development.

They include Unstructured, which helps organizations from Fortune 10 companies to the U.S. military transform raw data into the fuel for AI applications; Chainalysis, a blockchain intelligence ...

Julie Dodd, director of digital transformation and communication at Parkinson's UK, hopes her digital transformation projects helps lead to the rapid end of the charity: "We want to find a cure ...

On the lessons the bank has learned on its data transformation journey, Sinha said that with technological approaches and tools in the data realm constantly changing, it was important for data ...

The Michigan Tech Advantage The Michigan Tech Data Science MS provides a broad-based education in data mining, predictive analytics, cloud computing, data-science fundamentals, communication, and ...