Big Data

Traditional warehouses, ETL lifecycles and modelling methods are struggling to cope with the growing demands of the V’s of big data, increasing volume, variety, veracity and velocity. The traditional warehousing marketplace has after decades of slow and steady growth being transformed by the maturing of new paradigms in this space: scale-out architectures based on Hadoop or NoSQL; in memory execution engines; streaming technology; source-based modelling, schema-less architectures; low-cost storage; separation of data and compute; elastic scalability. These services typically considered batch oriented and for OLAP only now available as a real-time service with OLTP and cube capabilities. Smarter data is about introducing this technology to save money, improve efficiencies and get results faster.