Since the release of Cloudera Data Visualization (DV) back in Oct 2020, our primary mission has been to expand access to data analytics and predictive insights across enterprise businesses.
Recommendation systems have become a cornerstone of modern life, spanning sectors that include online retail, music and video streaming, and even content publishing. These systems help us navigate the sheer volume of content on the internet, allowing us to discover what’s interesting or important to us. The classic modeling approaches to recommendation systems can be broadly categorized as content-based, as collaborative filtering-based, or as hybrid approaches that combine aspects of the two.
Data and analytics have become second nature to most businesses, but merely having access to the vast volumes of data from these devices will no longer suffice. Leading enterprises realize that the speed of data presents a new frontier for competitive differentiation. It is imperative for organizations to reduce time-to-insights to gain a competitive advantage by responding decisively to competitors, fine-tuning operations, and serving fickle customers.
Companies today are faced with an analytics conundrum. On one hand, there’s a higher demand than ever for actionable business insights, but on the other there’s limited resources to deliver BI content to on-technical business end-users. To fill this gap, the industry is increasingly turning to the next generation of self-service analytics tools. These tools reduce time to insight, speed up insight to action, and also allow BI teams to focus on more strategic analytics work.
Customer success is much more than a function.
