Fleet Management

Data Insights

Prepare, Contextualize, and Normalize the enterprise data to build a robust engine and be a data-driven enterprise. Data insights, both real-time and historical, are of paramount importance in order to facilitate proactive measures, generate prompt responses, and take timely decisions.

The digital transformation is a technological revolution that will change the industry dynamics forever irrespective of the type and nature of the industry. This digital transformation process entails the utilization of enormous digital data, connectivity, and processing. It encompasses every aspect of the industry such as rapid prototyping and R&D, production & performance, existing product enhancements, and new product creation.

The digital revolution has resulted in generating a huge amount of data and it is important to leverage the right insights from it. Aximind’s Data Journey helps clients amass the relevant information whether it is to know the customer’s satisfaction, the procurement process, optimizing the inventory & route for transportation or to find faults & gaps in the system.

Aximind’s Data Journey helps clients encompass the rightful information from creating data lakes to leveraging AI algorithms for analyzing the data through machine learning and deep learning concepts. Some of our critical projects included – Customer Segmentation for New Product Market Analysis, Sensitivity & CSAT analysis, Fraud Detection in Invoice and cash flows, Image Processing through vector analysis, Text Analytics for Document Processing as a part of an RPA (Robotics Process Automation) process.

Using Statistical Modelling, Aximind creates business-ready insights in various applications and dashboards for an easy understanding of our clients. Aximind works top-notch to leverage process excellence and automation through RPA and lean process to make organizations enhance their operation efficiency, increase flexibility, and deliver fast services to their customers.

Data Acquisition:

Acquiring the data from various disparate sources and consolidating it in ML ready formats from -

  • Enterprise Data
  • ERP/Teradata/Databases
  • Web Servers/Logs
  • Sensors/RFIDs


Cleanse & Transform Data

  • Remove Inconsistent Data
  • Remove Null Values
  • Misspelled Attributes

Exploratory Data Analysis

  • Create ER diagram & data dictionary
  • Normalize the data
  • Find the common set of terms, units, and vocabulary
Data Analytics & Modelling:

Applying the rules engine and train the domain-driven ML models, which best fits the business problem.

  • Cluster Analysis - KNN
  • Decision Trees
  • Random Forest
  • Bayesian Theorem
Visualization & Deployment:
  • Visual data representation through graphs and charts representing the story behind the data
  • Deploying the models, dashboard and applications to the client’s server or cloud applications to be accessible in real-time for insight-driven decisions

Do you want to work with us?

Developing a plan that is custom-built for your business.