Building a Smart Data Lake While Avoiding the ‘Dump’
A data lake needs to be fed and governed properly before analytics can discover kernels of
Apache Hadoop, Spark and Kafka.
A data lake needs to be fed and governed properly before analytics can discover kernels of
Running Spark on the mainframe can be advantageous because data is co-located. One use is fraud
Telecoms have valuable real-time data they can sell for urban planning. The challenge: build a platform to analyze
Data governance and metadata synchronization can prevent Hadoop data from going dark.
“When we look at what's behind the dynamic growth in the big data arena, right now we see it at Apache
Modern data warehouse design often involves new platforms that can deal with new sources of unstructured and real-time data, as well as use of
Apache Spark offers fast speeds, integration with a variety of programming languages, and flexibility. But Spark vs. Hadoop MapReduce is not an either-or
Enterprises looking to support streaming analytics often turn to Apache Storm and Apache Spark Streaming, two popular open-source projects. Here, RTInsights …
There's a lot of technology wizardry floating around these days and everyone is expected to get on board. However, that often becomes an expensive mistake for …