Tag Archives: Spark

Introducing Blended Learning From Cloudera University

Categories: Analytic Database Cloudera University Data Science Enterprise Data Hub Spark

Over the past decade, Cloudera University has taught more than 50,000 developers, administrators, analysts, and data scientists how to apply big data technologies. Developers are learning the APIs, so they can create new applications that were never before possible. Administrators learn to plan, install, monitor, and troubleshoot clusters. And analysts discover the power of SQL over large, diverse datasets. Training sessions are delivered…

Read More

Plotting the data-driven journey

Categories: Analytic Database Machine Learning Spark

“Becoming data-driven is a multi-year journey, not a simple implementation.” It’s one of the first things we tell our customers. Acquiring and using data in a way that simply wasn’t possible up until very recently, requires a huge cultural shift. It’s far more than just technology. Last year our CTO and co-founder, Amr Awadallah suggested…

Read More

Simplifying Big Data in the Cloud

Categories: Cloud Data Engineering Product Spark

In recent years, as public cloud adoption has accelerated and customers have started looking towards cloud for large-scale data workloads, we sought to reimagine how to most effectively offer Cloudera capabilities in the cloud. Our customers wanted to understand how to leverage the agility, scale, and ease-of-use offered by the cloud to efficiently and cost-effectively…

Read More

Omneo’s Journey to an Enterprise Data Hub

Categories: Enterprise Data Hub Success Stories

Omneo Enterprise Data Hub The Omneo team embarked on a journey into Big Data to solve a complex problem, to bring product quality intelligence to manufacturers in a complex supply chain. The challenge encompassed several primary aspects including, multiple distributed data sources, heterogeneous data sets, lack of a consistent or common industry format for data,…

Read More

What To Consider When You’re Considering Cloud

Categories: Analytic Database Cloud Data Engineering Data Science Operational Database Spark

In a blog posted earlier this week, my esteemed colleague Sean Anderson laid out a powerful argument for machine learning (ML) as a way to fuel recommendation engines, churn reduction engines, and IoT workflows. Leveraging components like Apache Spark, and its machine-learning libraries, data scientists are able to design and train complex models using troves…

Read More