Organizational level Collaboration
Experience real-time Collaboration when using Sparkflows to build your Data Science projects. Simplify onboarding team members and sharing data and workflows across your team members. Extend the power and flexibility of Sparkflows beyond individuals and teams to everyone in your organization.
Sparkflows creates a common real-time updated workspace for the project team ensuring that all functions, be it a Data Engineer, Data Analyst , Data Scientist or Subject Matter Expert , all have a common view and are able to speak the same business language.
Visual Collaboration
Sparkflows visual drag and drop interface helps the Data Science project teams to build complex processes more clearly while also fostering engagement. This visual collaboration scales agility, connects hybrid teams, and increases organizational efficiency.
Build your ETL and data pipeline, create your visualizations and dashboards, build predictive models, analyse model and business metric outputs, all of these as part of the same project where your Data science team across various roles, all work seamlessly and collaborate efficiently.
Technical and Business Teams Collaborate across the Stack
A business user creates and defines a business problem in a Sparkflows project, a data engineer then builds a data pipeline on which a data analyst can build data visualizations and do their analysis, A data scientist then builds a model, validates and verifies it and marks it for production deployment from where the MLOps team takes over.
Sparkflows improves productivity of teams who can now focus on building and solving real business problems with the low-code/no-code approach and collaborate effectively to build and deploy advanced analytics projects
Versioning
Sparkflows provides traceability of all changes and modifications made to a given project with its built-in version control. With Sparkflows, be able to retrieve a specific version of the entire project which aids in reproducibility for you when referring to older runs or for root cause/forensics analysis.
Manage source code and assets, serve as a single source of truth across teams with the version control capabilities of Sparkflows.
