Reshaping Telecommunications With AI and Dataiku

Top telecommunications organizations use Dataiku — the world’s leading data science, machine learning, and AI platform — to make data accessible across the organization, allowing non-data experts like support engineers, field service teams, and more to make faster and better decisions with the support of AI systems.

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AI Applications and Use Cases in Telecommunications

Sales & Marketing

This guidebook provides marketing leaders, data leaders, and practitioners with a comprehensive end-to-end framework for getting started (and succeeding) with marketing AI.


Delivering Seamless Services

Service downtime and failure can be solved by using machine learning to predict what might cause service failures and prevent them from happening.


Predictive Maintenance

Reduce unplanned downtime & optimize maintenance plans for your equipment with this Dataiku Solution.


Process Mining

Create a visual map of your processes based on readily available process logs. Quickly deep-dive into specific processes, analyze outliers, and apply powerful statistical techniques to enable remediation & optimization efforts.


Supply Chain

Dataiku’s integrated REST API allows analysts to create robust supply chain analytics on both structured and unstructured data in the supply chain.


Delivery Dock Optimization

Leverage tracking data of incoming trucks to manage their allocation to your warehouse’s docks throughout the day and optimize yard management efficiency.


Do Even More With Dataiku

Generalized Linear Models

This plugin makes it possible to train, score, and deploy Generalized Linear Models from the VisualML interface.

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The Neo4j plugin allows DSS users to read and write from/to the Neo4j graph platform. Neo4j offers a popular database and language (Cypher), which lets users query and analyze graph data structures.

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Text extraction and OCR

This plugin provides recipes to perform Optical Character Recognition (OCR) using the Tesseract engine

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Model Fairness Report

Get insight about the fairness metrics of a model

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