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Global Data Science Platform : Platform for AI Democratization

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Global Data Science Platform : Platform for AI Democratization

  1. 1. Nov 9, 2019 Sekhar Kalle Data Science & AI Department Rakuten, Inc.
  2. 2. 2 • Time consuming to setup environment • Difficult to access and understand data • Need to share data science knowledge • Centralized analyst environment • No machine learning knowledge • Difficult to get knowledge from tech unit about data science Data Scientist/Data Engineer Marketer/ Business Analyst 2 Personas and Key Pain Points in Data Science Ecosystem • Time consuming to setup environment • Difficult to access and understand data • Need to share data science knowledge • Centralized analyst environment • No machine learning knowledge • Difficult to get knowledge from tech unit about data science Data Scientist/Data Engineer Marketer/ Business Analyst
  3. 3. 3 • Increase Adoption by lowering barrier for Data Scientists to manage the ML pipeline • Quicker solutioning/turnaround for training/deployment cycles • Speed of data sciences team with faster business outcomes from data Knowledge sharing Scalable compute AI for business
  4. 4. 4 Preparation 54% Understand 27% Only 20% of their time spent on data science work Build AI / Data Model Environment Preparation Understand Evaluate We can reduce 90% of the preparation time
  5. 5. 5
  6. 6. 6 ML Workbench Deployment Engine Knowledge Community Data Preparation Data Discovery Training Evaluation Versioning Deployment Monitoring
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  8. 8. 8 Training Deployment Notebooks/Models Workbench Platform Runtime Environment Monitoring, Alerting and Tools for high SLA service management On-prem Platform Infrastructure (K8s) Infrastructure (Apache Mesos, GPU) Platform Runtime Environment Monitoring, Alerting and Tools for high SLA service management On-cloud Platform Infrastructure (GCP VM, GPU, TPU) Data Store (SPDB, Hadoop, etc.) Replicated Data Interface Interface Data Science Console Job/ API Existing app Existing app Job/ API
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  11. 11. 11 CustomerDNA Customer Predictive Intelligence Geo 70+ data scientists use GDSP on daily basis for their machine learning workflows Using GDSP GEO has developed and hosted model API for logistics last mile solution and RMN coverage map service CustomerDNA generated models for features prediction and automated the workflow Using GDSP Applications on GDSP CPI is building models for predicting next purchase propensity and devising Marketer action across the customer funnel Brand & Marketing Group EC Logistics DSCD + DSAID Success Story Data Science Consulting Department is using GDSP for generating insights for many external clients

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