Big Data Analytics
Data Analytics provides valuable insights into unstructured data within your CommCell environment, enabling you to quickly assess the status of your big data sources and take necessary steps to free up storage space while also reducing compliance risks. With the potential for operational improvement and new revenue streams across various industries, Big Data Analytics is a valuable tool for businesses seeking to leverage hidden insights within their data. Use cases range from customer personalization to risk mitigation, fraud detection, and internal operations analysis, with new use cases emerging regularly. As a result, companies are investing in cutting-edge analytics operations to uncover the value hidden in their data.
Big Data Analytics Competencies
Wide Range of Engines for Efficient Task Execution
Select the most suitable engine from a vast range of options, including Hive, Spark, Presto, and TensorFlow, for optimized task execution.
Optimized Performance and Scaling for Each Workload
Efficiently manage and scale workloads with automated cluster management, including managed autoscaling for Spark, Hadoop, and Presto workloads. Simplify administration and provide self-service access to users through various interfaces for improved performance and scalability.
Flexible and User-Friendly Development Environment
Choose your preferred development environment and interface to start coding instantly, with a variety of options, including Dashboards, Notebooks, command line, API, and more. Enjoy a flexible and user-friendly development experience tailored to your preferences and needs.
Seamless Integration with Big Data Ecosystem
Integrate seamlessly with the big data ecosystem using a variety of tools, including Talend, Informatica, Oozie, Azkaban, and Apache AirFlow for scheduling and ETL, Looker, Tableau, Apache Superset, Periscope, and Qlik for BI software, and Apache Atlas, Apache Ranger, SSO integrations, Encryption in Motion and at Rest for security and governance.