DataStax today announced DataStax Enterprise 4.0, the latest version of its always-on database platform based on Apache Cassandra. DataStax Enterprise 4.0 introduces a powerful new in-memory option and enterprise search enhancements for significantly faster performance in use cases where companies must process data at the speed of business.
The analytics software category is 30 years old and about $15 billion in size. So why is it that information technology research and advisory firm Gartner has not published a standalone Magic Quadrant on the sector until this year? The answer: Gartner has meshed business intelligence with analytics for the past decade, and viewed them […]
OneFold believes that the expertise of a data scientist should be used for solving the most complex of analysis and not for the more day-to-day aspects of data extraction. The company uses a plug and play DHQL platform for automated data extraction, transformation, querying and reporting. Navneet Aron and Uday Sandhar, co-founders of OneFold, teamed up to answer our questions about this intriguing technology.
Global education giant Pearson uses data science to make their products better especially for student outcomes. The video below features a recent Cloud episode of Google Developers Live, with Felipe Hoffa hosting Pearson’s Director of Data Science Collin Sellman, to celebrate Python Pandas release 0.13 and its Google BigQuery connector. Jacob Schaer and Sean Schaefer join them to demo its capabilities, and how Pearson uses data science to improve education.
As a practicing data scientist and big data journalist, I often find myself down in the trenches on pursuit of new trends, products, and services. Earlier this week I attended a local machine learning meetup group event and I came away with a real gem. The presenter mentioned in passing a new cloud service called “Domino” and I rushed back to my office to learn more. I wasn’t disappointed.
Paradigm4 is the company behind SciDB, a scalable array database with native complex analytics. CEO Marilyn Matz is an expert in the field of big data, after co-founding Cognex Corp in 1981. Marilyn has some interesting perspectives as to why Hadoop might not always be the correct choice for big data deployments. I recently caught up with Marilyn to discuss these views.
“SAS In-Memory Statistics for Hadoop software enables multiple users to concurrently manage and prepare data stored in Hadoop, explore and visualize this data, develop accurate statistical and machine learning models quickly, as well as access, deploy and execute these models in their Hadoop ecosystem.”
Last week saw evidence for the big data industry steamroller effect as the Strata Conference 2014 in Santa Clara came and went. With thousands of attendees, an abundance of informative presentations, and a very healthy exhibitor ecosystem, the show defined the current state-of-the-art for all that is big data. If you missed the big event, O’Reilly Media has graciously made available the slides and videos for some of the presentations.