HR analytics enables companies to use people data to drive success in hiring, retention, total rewards and employee satisfaction.

As businesses scale to meet the demands of their customers, so do their need for efficient products to collect, manage and analyze data to meet their business goals. Whether you are building a multi-player game or a global e-commerce platform, it's critical to ensure that data can be stored and queried at scale with strong consistency and then processed for analysis to deliver real-time insights.

Geographical data is one of the critical datasets for data-driven organizations to make informed business decisions. As the data is growing more than ever before, it’s becoming more challenging to manage and analyze mammoth datasets using traditional databases, this is true for geographical data as well as it requires significant computational power to process. Esri has been one of the leading companies in Geospatial software development since 1969.

Amazon Redshift is one of the world’s most popular cloud data warehousing solutions. Along with other Amazon Web Services offerings, such as Amazon S3 and Amazon EMR (Elastic MapReduce), Redshift can help enhance your data workflows and manage your enterprise data. With the right expertise, Redshift can help you integrate all of your data sources, from operational databases and data lakes to third-party files and websites.

Here are five key takeaways about data mining: Data mining techniques draw from a wide range of subjects, from database management to machine learning and everything in between. In this article, updated for 2022, we discuss the most important data mining techniques and how to employ them to maximize your data investments.

Still waiting for ML training to be over? Tired of running experiments manually? Not sure how to reproduce results? Wasting too much of your time on devops and data wrangling? Spending lots of time tinkering around with data science is okay if you’re a hobbyist, but data science models are meant to be incorporated into real business applications. Businesses won’t invest in data science if they don’t see a positive ROI.

A feature store provides a single pane of glass for sharing all available features across the organization. When a data scientist starts a new project, he or she can go to this catalog and easily find the features they are looking for. But a feature store is not only a data layer; it is also a data transformation service enabling users to manipulate raw data and store it as features ready to be used by any machine learning model.

We asked 39 experts to share their best advice for setting up Google Analytics eCommerce tracking. Here’s what we’ve learned.