We have several teams that include more than 200 engineers and nearly 100 data science experts working on projects in ML, NLP, Information Retrieval and Search at Bloomberg. We are experts in software ...

Moving data science into production has quite a few similarities to deploying an application. But there are key differences you shouldn’t overlook. Agile programming is the most-used methodology that ...

Data Science is a structured approach to extracting valuable insights from data, and it involves several key stages to ensure success. Let's explore each phase in detail: By following this structured ...

Data science can provide a high return on investment across multiple industries and use cases. Whether predicting new target customers, measuring product demand or detecting high product failures - ...

I recently moderated a webinar roundtable on behalf of Domino Data Lab called “Unleash Data Science for the Model-Driven Business You Expect.” I don’t know that everyone expects a model-driven ...

Deploying data science into production is still a big challenge. Not only does the deployed data science need to be updated frequently but available data sources and types change rapidly, as do the ...

Apache Spark and Hadoop, Microsoft Power BI, Jupyter Notebook and Alteryx are among the top data science tools for finding business insights. Compare their features, pros and cons. While data has its ...

Building deep and ongoing data science capabilities isn't an easy process: it takes the right people, processes and technology. Finding the right people for the right roles is an ongoing challenge, as ...

Discover what data science is, its benefits, techniques, and real-world use cases in this comprehensive guide. Data science merges statistics, science, computing, machine learning, and other domain ...