This article was originally posted by Tom Smith Research Analyst and Business Stratgist, DZone, Inc on their website and is being shared here with permission.
Doug Cutting, Chief Architect at Cloudera, shares how the company uses open-source software to help companies use data to improve their business.
What does your company use open-source software to accomplish?
Everything we do.
This is a guest blog post from Jasper Pult, Technology Consultant at Lufthansa Industry Solutions, an international IT consultancy covering all aspects of Big Data, IoT and Cloud. The below work was implemented using Director’s API v9 and certain API details might change in future versions.
Cloud computing is quickly replacing traditional on premises solutions in all kinds of industries. With Apache Hadoop workloads often varying in resource requirements over time,
We are excited to announce the general availability of Cloudera Altus SDK for Java to programmatically leverage the Altus platform-as-a service for ETL, batch machine learning, and cloud bursting. Altus empowers customers and partners alike, to run data engineering workloads in the cloud, leveraging cloud infrastructures such as AWS. Cloudera Altus also provides the ability to create data engineering pipelines using both a web console and CLI.
Cloudera Altus SDK for Java was developed to provide easier programmatic access with the popular Java programming language so that users can automate their data engineering workloads.
Many types of business problems boil down to making recommendations, and machine learning is the special sauce that makes these problems solvable. Machine learning for recommendations is a challenging endeavor in its own right, but it is just one part of the recommendation system, which must move, store, process, and update data, in production, across several different components. In this post we show how to use Cloudera’s distribution of open source software to build a production scale recommendation system,
Self-service BI and exploratory analytics are some of the most common use cases we see our customers running on Cloudera’s analytic database solution. Over the past year, we made significant advancements to provide a more powerful user experience for SQL developers and make them more productive for their everyday self-service BI tasks and workflows. Leveraging Hue as the SQL development workbench, we continue to see usage of the platform increase and the number of analytic use cases grow –