With over 2.5 quintillion bytes of data getting generated every day, it is imperative for enterprises to leverage this data in the right way to get insights that will help them make smarter decisions.

Manually culling out relevant information from different sources and reviewing lengthy excel sheets can be a humongous task. But with NAllianceTech’ Business Intelligence and Data Visualization tool, getting insights from different data sources is just a click away. This Business Intelligence and Data Visualization tool allows you to create your own interactive dashboards from any device even when you are not connected to the internet.

TruBI offers an enterprise-ready business intelligence platform that provides a modern & responsive user interface. It supports self-service analysis, 360 degree view of a single-version-of-truth, and provides an intuitive & interactive experience in a secure and scalable environment. With all this, our BI tool provides business users with definite advantages in terms of 99.99% up-time and increased employee productivity by almost 60%.


Some of the features of the BI Tool

Cloud Ready

Available both on premise and in cloud

Cloud ready architecture is both vertically and horizontally scalable for managing sudden data surges

DIY Mechanism

Self-service pick & choose feature, allows end users to create and personalize dashboards using the data visualization tool and mobile devices any time anywhere

Productivity Tools

Enterprise-grade reporting provides a complete set of productivity tools, report wizards, pre-built templates & reports, and end user report designers

DIY Query Building

Smart query builder empowers users with self-data preparation as well as query building options without writing any SQL statements

Schedule Timer

Scheduler for scheduling and publishing near real-time dashboards at pre-defined times across wider collaborating teams

Multi-dimensional View

Drag & drop business intelligence report feature to get a multi-dimensional view with the ability to slice and dice information efficiently towards 360 degree data analysis

Data Discovery

Enhanced drill-down & data filtering features help users discover intelligence from huge volumes of data and explore specific KPIs in more detail using the data visualization tool

Collaboration Platform

Sharing & collaboration feature allows users to publish the developed dashboards and share them with other business users along with their analysis, annotations, and history

Intuitive & Interactive

Modern & responsive user interface creates interactive dashboards for the web as well as mobile devices for which no coding is required


Centralized Management Platform

Helps in managing small as well as large deployments from a single point over the web

Enhanced Security Features

Provide centralized and customizable role-based security to ensure that stakeholders can only view their own data

Hybrid Architecture

Enhances performance that enables faster analysis leading to quicker insights

Data Connectors

Help in connecting with different types of data sources and create a highly compressed snapshot

Enterprise Scalability Features

Allow working with high data volumes and large numbers of users


Make it flexible for the dashboards and reports to be extended into other apps and web portals

OLAP Architecture

Offers high performance and in memory caching for Non-EDS and Non-OLAP


Offers a robust architecture for thousands of concurrent users

Rich Visualization Objects

Offers business insights through interactive visualization

Frequently Asked Questions

Artificial Intelligence solutions enable the automation of medium to complex processes and take Robotic Process Automation to the next level. It powers predictive maintenance of heavy machines thus reducing operational costs. AI enables pattern identification with vast data volumes thus augmenting human intelligence and decision making. It improves the analytics domain to the nth extent. While Natural Language Programing (NLP) algorithms read and augmedata nt to produce analytical reports, Natural Language Generation (NLG) algorithms write sentences.

AI joins the dots from disparate data sources and discovers interesting patterns that are less visible to the human eye and intellect. Consistent variations, clustering of data points, dependencies, etc., bring forth interesting stories from the stagnant data resources. Using data, AI-enabled information mining generates hypotheses, verifies them, and deduces information. Information Mining forms the basis of Predictive Analytics and Machine Learning.

AI-powered Data Mining enables users to perform different levels of tasks –

  • Anomaly detection, where unusual patterns or outliers are thrown up, which may be errors or require deeper investigation
  • Associations, where the relationship between two or more variables are brought forth, and is frequently used in forensic investigations
  • Clustering, where data points that are similar in more than one ways are discovered
  • Classification, where known structures are generalized in order to apply to new data points; for example: Records or File Classification
  • Regression, where a function is found, which models the data and estimates the relationship between different data points
  • Summarization, where a concise summary is generated based on weighted keywords. It is popularly used for generating audit reports and executive summaries.

AI simplifies Document Management to a great extent. It enables automatic file classification or categorization as well as summarization. The files may include spreadsheets, documents, emails, PDFs, video files, audio files, social media, news, and other data types.

AI algorithms generate intelligence from high data volumes by correlating disparate data points. This data may comprise structured, unstructured, and multi-structured data.

A recent feature is AI-enabled Topic Modelling. It allows screening of huge data sets, such as reviews, emails, social media snippets, etc., and segregating them as per the predominant sentiment.

AI algorithms use weighted keywords and correlate them to generate concise summaries of lengthy documents, news articles, research papers, agreements, books, tweets, etc.

It uses two methods – Extractive and Abstractive. Extractive Summarization extracts several portions of the text and stacks them to create a summary. Abstractive Summarization uses NLP algorithms and generates a new summary.

AI-powered document summarization is used in audits, research study scenarios, social media listening, government services, etc.

Amit Mahajan
N Alliance Tech Commercial Director

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