Leveraging Big Data technology is a major competitive advantage. Completing that data analysis faster and more efficiently than rivals creates significant ROI potential, regardless of industry. Apache Spark is an open source cluster computing framework that is quickly gaining traction among enterprises due to its ability to complete flexible large-scale data analysis.
Here are 7 ways that Spark can provide business value for your organization:
- Real-Time Queries – Executes super-fast queries against data in Hive, HDFS, HBase and Amazon S3.
- Event Stream Processing – Aggregates, analyzes and alerts event-intensive applications like algorithmic trading, fraud detection and sensor data.
- Iterative Algorithms – Accelerates repetitive processing required by iterative algorithms.
- Complex Operations – Supports operations such as joins, group-by, and reduce-by to quickly model and execute complex data flows.
- Big Data Graphics – Has the power to manage large graphics, common in applications like geo-location and targeted advertising.
- Faster Batch Processing – Completes batch-processing jobs 10 to 100 times faster than the Hadoop MapReduce engine.
- Unified Big Data Analytics – Has the advantage of reducing the need to build, manage and maintain separate processing systems for different computational needs.
With Apache Spark combined with Qubole Data Service, users overcome latency issues associated with MapReduce and are able to perform ad hoc queries that offer new insights to boost ROI. To learn more about how Qubole with Spark can benefit your business, click here.