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How DataOps, Data Scientists & Data Analysts collaborate more effectively!

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WeWork Moorgate

1 Fore Street

London

EC2Y 9DT

United Kingdom

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Come and learn how companies like Comcast, Pinterest, Oracle, Expedia, Activision Blizzard, Box, Thomson Reuters, Lyft, AutoDesk, Under Armour, Adobe, Roku, Reddit and Turner have made big data analytics work in the cloud. This event is for Data Architects, DataOps, Data Analysts and Data Scientists.

Key questions that will be answered:

  • What are the building blocks and best practices of the Modern Data platform?

  • How to buildout Data Lakes for creating a self-service organization?

  • How to handle the inability to scale infrastructure to meet growing volume of data?

  • What are the best practices of scaling out big data in the cloud based on real world customer experiences?

  • How to stop spending more time managing infrastructure vs. exploiting the data?

  • Enabling access to the data across the Organisation to leverage data for better decisions/insight?

First Speaker: Tom Mack from Qubole will cover several customer case studies and best practices.

Qubole has a cloud-based data platform tool that self-manages, self-optimizes and learns to improve automatically and as a result delivers unbeatable agility, flexibility, and TCO. It allows Qubole customers to focus on their data, not their data platform.

The topics covered will include:

  • Example customer journeys to the cloud from on premise Hadoop.

  • Bridging the gap between the 'data operations/data engineering teams' and the data analysis/data science teams.

  • Saving money and reducing costs in the cloud.

  • Focusing on the business value of analytics rather than the operational overhead.

  • Making Data science more accessible to more users

Second Speaker: Ajith Ramanath will provide technical depth and a demo

In 2017, Qubole saved customers $140M in cloud costs by smartly—and automatically— leveraging all the cloud resources available to business. Customers provide self service analytics for Data Analysts and Data Scientists. Use machine learning to on query and cluster metadata to make recommendations and improve efficiencies.

The topics covered will include:

  • Implications of per second billing on cluster management

  • How to scale your big data infrastructure in the cloud

  • Evolving architecture patterns in the Cloud - The advantages in separation of compute and storage

  • Persona view: Data Ops / Data Analyst / Data Scientist

  • Platform Demo - Hive, Presto, Hadoop, and Spark




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Date and Time

Location

WeWork Moorgate

1 Fore Street

London

EC2Y 9DT

United Kingdom

View Map

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