Organizations today, especially in the oil and gas sector, are swimming in data [1] but most of them manage to analyze only a fraction of what they collect. To help build a stronger data-driven culture, many organizations, starting with technology companies, are adopting a new approach called self-service analytics. In this paper, we present our big data and analytics architecture that has enabled our in-house and outsourced engineering, and data science teams, to develop self-serving AI models and data pipelines. Our architecture is presented to the reader in such a way that he/she can apply it using the cloud provider of their choice by translating the concepts presented here, either to native cloud PaaS or using open source products.

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