Having data scientists collaborate with devops and engineers leads to better business outcomes, but understanding their different requirements is key Data scientists have some practices and needs in ...

For data scientists, creating a perfect statistical model is all for naught if the compute power required is prohibitive. We need tools to assess the performance impacts of modeling alternatives Big ...

Data science and machine learning are often associated with mathematics, statistics, algorithms and data wrangling. While these skills are core to the success of implementing machine learning in an ...

While the general advancement of enterprise software is often thought of as the marrying of software development and data stacks, a third consideration is essential to driving tangible advancement. It ...

Last week’s Informatica World 2016 brought out a lot of talk involving data quality, real-time live data and the automation of ingesting and analyzing data in order to turn it into something ...

Opinions expressed by Digital Journal contributors are their own. The fusion of artificial intelligence (AI), machine learning (ML), and DevOps signifies a new era of efficiency and technological ...

DevOps teams are essential in large businesses, tuned into digital transformation strategies. DevOps is an evolving process. Today those working in this function will be increasingly drawn into the ...

iRobot has used its new design, software, and data science strategies to expand into new areas, using an approach to the smart home that is different from its big tech rivals. This download provides ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

7 big data goals for 2021: AI, DevOps, hybrid cloud, and more Your email has been sent Image: iStockphoto/metamorworks Must-read big data coverage What Powers Your ...