Data Science Lifecycle

The data science lifecycle refers to the sequence of actions taken to develop, deploy, and maintain a data science product. Not all data science projects are identical, so their lifecycle may also differ. However, we can envision a general lifecycle that includes some of the most common steps in data science.


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Data Engineering Simplified.

Deliver data at the speed of business. RubiFlow is a best-in-class visual data-flow designer and orchestrator with drag-and-drop capabilities for data wrangling, blending, and analytics processes.


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12

Why RubiFlow

Provide your sales team in the field round-the-clock access to your pipeline, even without WiFi.

  • Drag-and-drop interface
  • 100+ pre-built connectors
  • Data Dictionaries
  • DataOps
  • Data Orchestration
  • Data Governance
“Our customer services data points are very complex, and with RubiSight, we could reduce the time-toinsights in interactive dashboards.” – CIO, Fortune 500l
 

Data Science Simplified.

RubiStudio is a Visual Designer (no-code/low-code/pro-code, drag-and-drop) self-service AI-ML capabilities within a flexible, centralized environment that spans the analytics life cycle.


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11

Why RubiStudio

Provide your sales team in the field round-the-clock access to your pipeline, even without WiFi.

  • Data Exploration & Wrangling
  • Auto ML & Pro-Code Modeling
  • Forecasting
  • Text Analytics
  • Deep Learning
  • Model Ops
“We run 100s of ML models built on Rubiscape & Python for monitoring and optimising our quality control and manufacturing excellence.” – VP Data Labs
 

Data Visualization Simplified.

Let the Data Lead You! RubiSight is a visual data storyteller. RubiSight provides a drag-and-drop interface for creating visually appealing interactive dashboards.


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33

Why RubiSight

Provide your sales team in the field round-the-clock access to your pipeline, even without WiFi.

  • Drag-and-Drop Interface
  • Data Preparation
  • Dynamic Dashboards
  • What-if-Analysis
  • Metadata Management
  • Automation and Scheduling
“We use Rubisight for our customer services and inventory optimisation analytics to track and monitor performance, trigger alerts and spot the trends” – Head of Digital
 

IOT

Enhance data analysis and presentation by integrating devices, sensors, and applications. Acquire data right from the source, thus, eliminating eliminate noise/errors. Deploy ML at the edge to enable decisions in real-time near the source.


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44

Why Rubithings

Provide your sales team in the field round-the-clock access to your pipeline, even without WiFi.

  • Simplified device On-boarding
  • Templatized approach
  • Structured and Un-Structured data support
  • Scalable Secure Extendable
  • Hybrid deployment Model
  • Analytics at the Edge
"Rubithings has primarily addressed our business challenges and helped in resolving key errors in unsecured database."
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