Our Company

Company Background



Established in 2015 as QASkills, we are an Oracle Preferred Oracle BI Solution Implementation partner. We have metamorphosed into Neural Data Science and Technologies, and grown to become a global BI, Big Data & Analytics consulting service provider focused on the telecom and finance markets.


Neural Data Science & technologies (NDST) has been helping esteemed telecom clients in building enterprise data ecosystems since 20015. Our incumbent robust data engineering & business intelligence framework help us to integrate huge volumes of data from disparate sources. Our execution expertise encompasses the global best practices in data integration, analytical/ AI data modelling and analytics/ ML use-cases. Over the years, our values and commitment have made us unique and your trusted partner in delivering enterprise data ecosystem and helping decision-makers to build the ability to make data-driven decisions.


We are based out of a software development centre in Kolkata, India. We have a multi-disciplined team with mathematical science, engineering, and domain experts.


NDST ensures the successful building of an enterprise data ecosystem and managing the enterprise value chain
(information->knowledge->wisdom delivery framework). We have been the No. 1 Oracle OCDM implementer since 2015 for successful implementation of OCDM projects around the world. We worked with several clients in helping them develop a robust Oracle business intelligence and data warehouse “OCDM” framework while building a comprehensive enterprise data ecosystem.

Mission Statement

Delivering business value for telecommunication service providers by integrating Vast OSS/BSS Data into Business Intelligent Architecture, building business KPI foundation and helping Business Decision Makers to build Data-Driven-Decision making ability.

Core competencies

Data Engineering

Building “Enterprise Data Ecosystem” (EDL+EDWH+ AI Data Model)

AI Data Modelling

To realize digital twins (Customer, Business Partner, Equipment/IoT)

Machine Learning Modelling

To deliver ML business use-cases

SLA driven MSO (Managed Service Operation) and KPO Data Analytics Service

Business Assurance and Audit Consulting


Quality Policy

Neural Data Science and Technologies Private Limited aims.


  • To ensure right quality by embedding "customer engagement" in every aspect of our delivery lifecycle and associated support services that we do in our daily business focusing in the areas of Digital Integration and Automation, Revenue Management and Assurance and Data Science and Analytics including Machine Learning and Deep Learning.
  • To provide and continually improve Quality-of-Product, On-Time delivery and the overall service experience while meeting or exceeding the requirements and expectations of our customers, aiming to maximize customer satisfaction, including complying with statutory and regulatory requirements.
  • To establish an environment for continually improving the Quality Management System.


We are certified with ISO 9001:2015 Certificate No# FM708187

Our project implementation approach

We roll-out such “Building Enterprise Data Ecosystem” project into 5-phases.


  1. Data Acquisition, Classification & Standardisation
    1. Building Enterprise Data Lake (EDL)
    2. Enterprise Data Warehouse Data Model (EDWH)
    3. Analytical/ AI Data Model (AIDM)
  2. Data Collection/Integration, data enrichment and loading into EDL->EDWH->AI Data Model
  3. Data Distribution to downstream applications e.g contextual marketing
  4. Data Driven Decision Making (Descriptive->Diagnostics->Data Mining/Predictive->Prescriptive Analysis)
  5. Data Life Cycle Management (“Data Ageing”- Rule based data purging)


To ensure Data driven decision making, Business requires a standardisation of the enterprise reporting framework and the delivery of reporting of uniform business KPIs across all stakeholders. To achieve this goal, I always follow the following steps to ensure the successful delivery of such project “Building Enterprise Data Ecosystem”.

  • Define a common business lexicon across all business functions.
  • Design a KPI business matrix (KPI-business dimensions) and build KPI foundation layer with Out-of-Box customer centric & location-based 800+ KPI(s) delivery.
  • Design digital twins (Customer, Business Partner/Distributor/Retailer, Equipment/IoT)
  • Leverage AI enabled Analytic Model which supports AI/ML Use-cases like Credit Scoring, Clustering & Micro-Clustering, Anomaly/Fraud Detection, Churn Prediction etc.
  • Define standardised reports and dashboards.
  • Enable business users with Ad Hoc reporting & Self-Service Capability.
  • Define information delivery service level-agreements (SLA)
  • Define Event Data quality strategy.
  • Define change control process
  • Managing Enterprise Information Value Chain (data->information->knowledge->wisdom) through SLA driven MSO (Managed Service Operation)

Our Value Proposition

  • Bringing global execution expertise and best practices in Data Engineering & Data Science
  • Bringing Robust BI/Analytics Strategy & Framework with industry standardized KPI definition by aligning your business lexicon definition if any
  • Out-of-Box Location based 800+ KPI(s) Delivery
  • AI enabled Analytics Data Model and digital twins (Customer, Business Partner/Distributor/Retailer, Equipment/IoT) delivery
  • High quality ML models delivery - Customer Segmentation & Micro-Segmentation, Credit Scoring, Predictive Churn Modelling, Anomaly Detection, Customer Lifetime Value, Market Share, Product Affinity Modelling, forecasting and more.
  • Self-Service Capability Building on Vast Data Lake across your enterprise.
  • Critical Process Improvements – DATA Standardization including MDM, Data reconciliation & Data Quality Plus Financial Accounting Ledger based data reconciliation.
  • Attractive Pricing model and Low Total Cost (TCO) of Ownership
  • Ensuring optimum resources in terms Hardware/Server, Technology & Human
  • Quick ROI: Our "Enterprise Data Ecosystem" solution is characterized by quick deployment timelines (6-9 Months) which translate to quick ROI

View Our Leadership Team