9 reasons why developers and data scientists are primed to spark insight with Spark

Post Comment
Big Data Evangelist, IBM

Data is being generated in unimaginably huge volumes every day in many formats. Everything from tweets and videos to data generated by connected cars, fitness trackers and even this listicle is contributing to the data deluge. An open-source software platform called Apache Spark is growing rapidly in popularity as an essential platform for rapidly modeling, exploring and analyzing data. Here are nine reasons why developers and data scientists are primed to #SparkInsight with Spark.

1. Developers are passionate about Spark.











2. Spark’s simplicity accelerates data scientists’ productivity.











3. The Spark ecosystem is innovating at a feverish pace.











4. Spark is the emerging power tool for development of big data analytics.











5. Spark enables fast, in-memory, distributed computation.











6. Spark can be a standard tool for diverse teams of data scientists.











7. Spark is an interactive development tool well-suited to demonstrations and proofs of concept.











8. Spark enables fast prototyping of sophisticated analytic applications.











9. Spark is unbelievably fast.










What are you waiting for? Sign up for IBM’s forthcoming Apache Spark as a Service on Bluemix and see for yourself.