nEX Analytics

Niche Enterprise Xaccelerator

nEX is the next Generation Analytical Platform which mitigates the GAP between Analytical Platform and Visual Analytics for generation to come.


nEX Quad


nEX Box

Core fundamental and feature of nEX is based on the following:

Visualization Platform

Different product range of nEX has being developed post consideration of growing usage and enhancement of Enterprise requirement. So, Start with Basic foundation of BI segment. Let nEX help to climb up next level of Analytical platform without taking pain of Data migration.

Embedded Analytics

This feature holds the base for nEX Box or nEX Quad – once dashboard or Analytical Pane opens and takes the shape of Graphical or Tabular view, you can embed those into the third-party portal seamlessly or publish a Public link for temporary action.

Data Pipeline

Data pipeline is a simple-to-use and extract the value from API / Data Source / Kafka Topic and store or flow data to the Analytical engine. Further, Data Wrangling transforms the data while we fetch data for Analysis.

Data Governance

Governing data is prime concern that is taken care of by nEX platform. So, before translation of data ,Raw data gets held inside the Staging system to ensure Batch processing of Data, in this run, we also maintain proper pipeline ensuring requisite Data Validity. Additionally, streaming data is stored for Analytics to-be built in Future.


nEX performs Dimensional Analysis, could be Embedded with other Third Party Portal (for an instance , Ecommerce ). Also, the platform is flexible enough to show Prediction outcome and monitor IoT-based asset platforms.

Data Management

A single source of truth is vital for agile performance. This gets handled without writing a single code on Scala, Python or R. The platform integrates with robust query platform like Apache Drill and Apache Presto; which is the silent feature behind nEX architecture.

Simple Integration

Simple to integrate with most of the BigData platform including Amazon Redshift, Druid, Google Big Query, MongoDBapart from Standard structured SQL RDBMS data bases.

Version Control

For every change made to any plotted Analytical group, Revision history helps to administrate and provide further monitoring. On the top of this, Developer receives Test approval from Business users on the KPIs, thus, collaboration and test version control is unique essence of this application.

Data Exploration

Once data is populated or merged inside the nEX, Business users or Developer gets Full control to monitor and explore data for separate Data sets. Here, AI-based Metadata anomaly can be detected out-of-the-box.