Knoldus Inc

Knoldus Data Science Platform

Discover actionable insights with a powerful, enterprise-ready platform.

Enterprises are driving real business transformation through data science and analytics

Data is everywhere and is being generated at a breakneck pace. This is creating a huge opportunity for organizations to gain new insights, make the data-driven decision and arrive at outcomes that drive success.
In the scramble to catch up, many organizations have adopted a hodgepodge of tools without a clear strategy for how each fits in the broader analytics technology stack in their environment. These dynamics affect organizations at all maturity levels; and after investing more resources in big data and data science, they are not yet realizing their anticipated return on investment.
digital economy

Unable to unleash the full potential of data from inside out

Companies invested in technology that keeps them on the cutting edge by using these powerful tools to give their data science teams a leg up in the race to deliver value. However, organizations are facing below challenges with these standalone tools and without having a data science workflow.

Focus on data not action

Organizations are focusing more on data sources over capabilities that create action from insight.



Disconnected Tools and Technology

Organizations are focusing more on data sources over capabilities that create action from insight.



Poor Collaboration

Data scientists are solving similar problems over and over again in different ways due to standalone tools or in different departments.


Poor Collaboration

Data scientists are solving similar problems over and over again in different ways due to standalone tools or in different departments.


Time Consumption in data management tasks

Data scientists spend over 60% of their time on data preparation and model refinement and managing infrastructure.

Lack of engineering support

Data scientists are expert statisticians but they often aren't qualified to deploy data models into production and therefore need engineering support.


Time Consumption in data management tasks

Data scientists spend over 60% of their time on data preparation and model refinement and managing infrastructure.


Lack of engineering support

Data scientists are expert statisticians but they often aren't qualified to deploy data models into production and therefore need engineering support.


Knoldus Data Science Platform (KDSP)

Leverage KDSP to unlock value from your data in a single, integrated environment

Knoldus Data science platform uses a structured data program for the entire data science life cycle, including data integration and exploration, model development, and model deployment. within a single integrated environment. It combines open source and commercial analytic technology together to operationalize insights, solve complex business problems, and enable descriptive, predictive and prescriptive analytics-including autonomous decision-making. The KDSP delivers the best analytic functions and engines, preferred tools and languages and support for multiple data types.
Knoldus Data Science platform enables organizations to deliver a tangible business outcomes in a short period while enforcing best practices in building data programs.

knoldus-data-science-platform

Unlock the Business Values with Knoldus Data Science Platform

Having access to many advanced analytics technologies under a single visual environment, such as a Data Science Platform, will enable you:

Centralized location for data

Centralized location for data

Eliminate the need for copying & extracting data. It simplified data access also by supporting multiple data types and format.

Quickly Operationalize Analytics

Quickly Operationalize Analytics

Operationalize analytics on an enterprise-ready platform to produce high-impact, trusted business outcomes.

Reduce Cost

Reduce Cost

Reduce expenses associated with utilizing numerous analytics tools and database warehouse appliances without compromising data access, performance, and ease-of-use

Enhance collaboration

Enhance collaboration

Enhance collaboration among departments and team and with different skill levels and locations


Technical Specification and a brief Architecture of Knoldus Data Science Platform

KDSP is a unified analytic and data framework. But under the covers, it contains a cross-engine orchestration layer that pipelines the right data and analytic request to the right analytic engine across a high-speed data fabric. The result is a tightly integrated analytic implementation that is not bound by functional or data silos.

Technical Specification

Data Science Platform Components

Knoldus Data Science platform enables all the 4 phases and operationalizes data programs to deliver a tangible business outcomes in a short period while enforcing best practices in building data programs.

Data Science Platform Components

Implementation methodology of Knoldus Data Science Platform

Sprint
Planning

Detailed stories, estimated and sprint level planning

Program
Planning

Data Org Structure



Technical
Architecture

Architecture beyond Knoldus Data Science Platform particularly integration​

Product
Definition

Feature, process and Flows


Data Org
Structure

Hierarchy and teams Customers, Suppliers, Business, Units, IT, Product, Teams

Governance
& Policies

Roles/Responsibilities/ Meta Data, - Data life-cycle, Securities

Meta Data
Management

Interpretation of Data-Schema storage,evolution,format and data association

Sprint
Planning

Detailed stories, estimated and sprint level planning


Program
Planning

Data Org Structure


Technical
Architecture

Architecture beyond Knoldus Data Science Platform particularly integration​

Product
Definition

Feature, process and Flows


Data Org
Structure

Hierarchy and teams Customers, Suppliers, Business, Units, IT, Product, Teams

Governance
& Policies

Roles/Responsibilities/ Meta Data, - Data life-cycle, Securities

Meta Data
Management

Interpretation of Data-Schema storage,evolution,format and data association

Sprint
Planning

Detailed stories, estimated and sprint level planning

Program
Planning

Data Org Structure



Technical
Architecture

Architecture beyond Knoldus Data Science Platform particularly integration​

Product
Definition

Feature, process and Flows


Data Org
Structure

Hierarchy and teams Customers, Suppliers, Business, Units, IT, Product, Teams

Governance
& Policies

Roles/Responsibilities/ Meta Data, - Data life-cycle, Securities

Meta Data
Management

Interpretation of Data-Schema storage,evolution,format and data association

How Knoldus Data Science Platform impacts our clients and discovers new ways to monetize data

We help organizations with their journey from challenges to high-performance siness outcomes and look out for ways to leverage data science technologies along with existing systems. With a single and integrated framework that enables data to flow throughout an organization to where it is needed, and when it is needed to bring insights and value.

Our Digital Team Structure

Our diverse wrokforce to challenge old practices and drive exceptional performance.

Online Lead
Architect

Online Scrum
Master

Online Lead Architect

Online Scrum Master

Offshore Lead

Sr. Engineer

Engineer

Test Engineer

DevOps Engineer

Offshore Lead

Sr. Engineer

Engineer

Test Engineer

DevOps Engineer