As more and more companies are embedding AI projects into their systems, attracted by the promise of efficiencies and competitive advantages, data science teams are feeling the growing pains of a relatively immature practice without widespread established and repeatable norms.
Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to Microsoft HDInsight (also powered by Apache Hive-LLAP) on Azure using the TPC-DS 2.9 benchmark.
The CDO role has been rapidly evolving over the past few years – from governance leader to data science and AI expert to digital transformation guru. And, with this change, has come a shift from a back-office focus to a focus on achieving measurable results required by the C-suite.
When evaluating your approach to analytics and BI, a common comparison is Qlik vs. Tableau. Consistently, when we have that conversation, there are some sharp distinctions that come to the fore in terms of capabilities, vision and cost.
Let's talk media buying in the data age.
Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Cloudera has found that customers have spent many years investing in their big data assets and want to continue to build on that investment by moving towards a more modern architecture that helps leverage the multiple form factors.
