Big Data

  • A load balanced OLAP architecture to scale up processing capability.
  • In-memory computing and custom pagination to project large datasets to the end user IN-MEMORY CACHE.
  • Fast Cache grid implementation using Redis.
  • Stores large datasets for the MDX queries.
  • Significant improvement in performance when data is preloaded as part of the BoD/EoD ETL run NoSQL based OLAP.
  • Move past the OLAP engine constraint of querying RDBMSes by implementing NoSQL querying capability.
  • MDX to NoSQL translation will bring to the table the Big Data framework benefits.
  • MongoDB document stores and HBase based solutions.
  • Hadoop/Spark frameworks used to aggregate large data-sets, to service end user queries.