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.
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.
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.
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
Quickly Operationalize Analytics
Reduce Cost
Enhance collaboration
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.
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.
Implementation methodology of Knoldus
Data Science Platform
Sprint
PlanningDetailed stories, estimated
and sprint level planningProgram
PlanningTimelines and
GoalsTechnical
ArchitectureArchitecture beyond Knoldus
Data Science Platform
particularly integrationProduct
DefinitionFeature, process
and FlowsData Org
StructureHierarchy and teams
Customers, Suppliers,
Business, Units, IT,
Product, TeamsGovernance &
PoliciesRoles/Responsibilities/
Meta Data, -
Data life-cycle,
SecuritiesMeta Data
ManagementInterpretation 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
Offshore Lead
Sr. Engineer
Engineer
Test Engineer