Enterprise IT groups must support business needs in a variety of functional areas while running computing, software, and communications infrastructure, managing software updates, and ensuring security. Advanced analytics applications  requires rigorous development and implementation of analytics concepts as well as verification and validation of the software. Using our Analytics Engines allows achieving desirable business outcomes with less effort. 

Deployment of Advanced Analytics

Data Science groups are focused of obtaining knowledge from the data, they are not development shops. The existing data analytics software provides tools for in-house development of the value added functions; the development itself remains the bottleneck. Mitek Analytics helps to span the gap between advanced analytics knowledge and operationally deployed software by providing solutions centerd on use of our Analytics Engines. The Analytics Engines have open architecture; they ingest big data sets, performs data cleansing, do analytical processing, and generate the results. Value added advanced analytics applications can be built by integrating automated value-added functions provided Analytics Engines with Data Science models, data management platform, and interactive BI visualization platform.

Our Analytics Engines include MapReduce computing pipeline for big data cluster scalability, and ability to do distributed localized preprocessing. The Analytics Engines can be integrated with existing data platforms as microservices, as edge node applications on Hadoop cluster, or through Apache Spark.

In an initial proof-of-concept project, Analytics Engine can be tested as stand-alone backend software by using report generation logic provided by Mitek Analytics. The portable HTML pages of the reports can be viewed on any web-based system.