In this special technology white paper, The 5 Key Challenges to Building a Successful Data Science Lab & Data Team, you’ll learn how a Data Lab establishes an effort to answer business needs by making sense of raw information. Data labs are intended to create critical mass within the organization that enables them to reach the level of innovation required for new data-driven products.
World Programming, a leading industrial analytics and data science platform provider, unveiled new features for data scientists and data science teams including those working within life sciences, pharmaceuticals, and financial services.
In this special technology white paper, From Development to Production Guide – Finding the Common Ground in 9 Steps, you’ll learn how managing a successful data science project requires time, effort, and a great deal of planning. Defining the problems to solve and planning the project’s scope is just the tip of the iceberg, as team members need to fully understand all aspects of a project in order to effectively contribute.
Here’s a useful new book for data scientists looking to approach the field from a unique perspective that doesn’t include language heavyweights like R and Python. “Julia for Data Science,” by Zacharias Voulgaris, Ph.D. from Technics Publications, allows you to master the Julia language to solve business critical data science challenges. But why look to a relatively new language when you already have other commonly-used languages at your disposal?
Bigstep, the big data cloud provider, announced the launch of Bigstep DataLab, a solution designed to enable data science and analytics at scale. Bigstep DataLab is an enterprise-ready data research service that gives domain experts, data scientists and BI specialists instant access to powerful software like Apache Spark and Jupyter for easier, more flexible and collaborative ad-hoc data exploration and research.
I recently caught up with Natalia Hernandez, Data Scientist at Foodpairing, to highlight how her company’s data scientists mine public online data, which gives general trend insights to use consumer intelligence and molecular analysis of ingredients to forecast the next big flavors in the food industry.
In today’s technologically advancing world, traditional banking groups are being seriously challenged. As Google, Amazon, Facebook, Apple offer more and more banking services and financial technology startups gain traction, the banking industry must take a look at how it can stay competitive. To do this, banking needs to rely on data science.
How Breakthrough Innovations at Experian’s DataLabs Expand the Horizons of Doing Good Things with Data
In this contributed article, Eric Haller, Executive Vice President at Experian DataLabs describes how his company uses large data sets coupled with data science methodologies to solve strategic marketing and risk-management problems with an emphasis on financial services, telecommunications and healthcare.
Collibra, a leader in data governance software solutions for business users, introduced Collibra Catalog, a data catalog that helps data scientists and citizen data analysts spend less time looking for data and more time solving critical business challenges. Collibra Catalog is available as part of Collibra 5.0, a new cloud-based or on-premises data governance solution that delivers outstanding ease-of-use, performance, and flexibility for organizations that put a premium on leveraging their data to make better and smarter decisions.