Waterline Data Science Announces Product to Make Hadoop Consumable by Business Analysts and Data Scientists
Waterline Data Science has announced the launch of Waterline Data Inventory to enable data self-service on Hadoop, allowing users to find, understand, and help govern Hadoop data.
Feedzai, a data science company that uses real-time, machine-based learning to analyze big data to make commerce safe, and DataStax, the company that delivers Apache Cassandra to the enterprise, today announced a commercial partnership under which Feedzai is now part of the DataStax Partner Network.
This article is the fifth and last in an editorial series that will provide direction for enterprise thought leaders on ways of leveraging in-memory computing to analyze data faster, improve the quality of business decisions, and use the insight to increase customer satisfaction and sales performance.
I recently ran across a thought-provoking post on the USC Anneberg Innovation Lab blog – “Why Do We Need Data Science when We’ve Had Statistics for Centuries.” With all the debate of late surrounding the relatively new “data science” term, I’ve been thinking a lot about this question, so I thought I’d analyze this notion here on insideBIGDATA by picking apart the article. I’d love to hear your take on this, so feel free to leave a note. [Read More...]
In this special guest feature, Jesse Anderson from Cloudera writes about how you can succeed with a career move into programming. At a time when data science engineers are using experience in programming to carve out their place in Big Data, this could be your big opportunity. [Read More...]
All Recent News
- Waterline Data Science Announces Product to Make Hadoop Consumable by Business Analysts and Data Scientists
- Feedzai Partners with Datastax for Real-Time Fraud Analysis
- Sumo Logic Launches Transaction Analytics to Transform How Companies Learn from Business Events
- GridGain In-Memory Data Fabric
- SAS Survey: Finding the Right Balance Between Personalization and Privacy
- Data Science 101: Data Agnosticism – Feature Engineering Without Domain Expertise
- Big Data Humor: The Art of Statistics