Data Catalogs are Essential But Can they be Fun?

New technologies have permanently transformed how customers communicate, interact, research and shop for goods and services. Retail data paired with retail analytics, can assist retailers in understanding and responding with actionable retail insights to the disrupted landscape and changing customer expectations.

Cloudera’s Data Science Workbench (CDSW) is available for Hortonworks Data Platform (HDP) clusters for secure, collaborative data science at scale. During this webinar, we provide an introductory tour of CDSW and a demonstration of a machine learning workflow using CDSW on HDP.

When organizations need to move quickly to launch new, digitally transformed applications that rely on terabytes (if not petabytes) of data, they cannot afford to wait for legacy database management systems to catch up. Cloud computing platforms give organizations the ability to stand up systems quickly, but if the data layer cannot offer the linear scalability, low latency, high availability, performance, fault tolerance, security, and agility needed for today’s 24/7 applications, organizations will never realize their objectives.

Data lakes based on Hadoop technologies have proved themselves valuable in mission-critical use cases such as data warehousing, advanced analytics, multichannel marketing, complete customer views, digital supply chains, and the modernization of data management.Most Hadoop users are committed to the data lake method of managing data, but they are limited by Hadoop shortcomings in key areas such as cluster maintenance, administration cost, resource management, metadata management, and support for SQL and other relational technologies. Many view cloud-based solutions as the optimal replacement for their data lake, but they are not ready to make such a significant change. The truth is: they don't have to, as the two technologies can coexist.