Predictive Analytics for Retail

whitePaper | September 20, 2022

Self-service is without question no longer an option for successful businesses. Find out how Alation can accelerate data-driven decisions with our Self-Service Data Intelligence white paper.

whitePaper | December 22, 2022

We live in a digital world in which data analytics and artificial intelligence significantly impact our daily lives. They influence what we wear, what we eat, where we travel, and how we spend our free time. In medicine the impact of data has much more drastic effects, as access to high-quality medical data is a matter of life or death for patients every day. In this particular area, the desire to save human life by discovering modern methods of therapy and diagnostics often contradicts another fundamental right of the patient - the right to privacy and the right to dispose of one’s data.

whitePaper | March 12, 2020

This point of view is an exploration of the possibilities engendered by rethinking the role of data scientists in the wake of industrial revolution. It might be claimed that current trends in industrial revolution reflect a paradigm shift towards data centric processing with data science playing an increasingly critical role. This point of view also explicitly highlights the potential role of Data scientists as an emerging phenomenon, and then to show some of the benefits that this role can bring as we move towards industrial disruption

whitePaper | October 13, 2022

Generally, data-driven companies mainly struggle with data quality issues. Massive amounts of data, changing data storage requirements due to changing company regulations, and the various types of data sources and formats do make data management quite difficult for companies. Hence, the need for robust DataOps took to automate and simplify data life-cycle phases is of utmost importance at this point. Here are, some of the most important DataOps took that professionals can use in 2022.

whitePaper | November 18, 2022

It’s time to treat data like a product, not an afterthought. A new paradigm has emerged among forward-thinking data teams: treat your data like a product. This may sound easy in theory, but it’s far from it! Product development processes have become incredibly sophisticated, with resources dedicated to reliability, adoption, feature roadmaps, and more.

whitePaper | February 7, 2020

The problem is that growing volumes of data can lead to data paralysis, because no one knows quite where to begin or how to use it. Siloed information sources, no data management strategy, disconnected spreadsheets or analytical tools and poor data quality all work to compound the issues you’re facing.