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EVENT DETAILS |
Free food, caviar, cheese, chocolate & fun drinks PLUS win an Oculus Rift!
Presented by:
Joydeep Sen Sarma, Co-Founder & Head of Qubole India
Data is moving from on-premise to the cloud at a pace that is faster than ever before. However, the cloud presents its own challenges.
To succeed with data in the cloud, there are numerous decisions that a data expert is faced with - to choose a data warehouse or a data lake or both? What is the right way to architect a cloud data lake & how does it differ from on-premise? And how to reduce the time to value by making this data available for analytics & machine learning?
Creating a sustainable competitive advantage using data goes beyond business intelligence to applications ranging from interactive, streaming & clickstream analytics, machine learning, deep learning & more. Data lakes provide an optimal architecture for such new applications of data. However, achieving success with data lakes depends on many factors. In this presentation, we will describe how cloud data lakes provide a future-focused, enterprise-grade solution to achieve sustainable competitive advantage using data.
We will specifically discuss:
Common use cases for data lakes
Differences between data lakes & data warehouses & perils of using them interchangeably
Data lake architecture best practices covering data ingestion, data layout, governance, data processing, security & financial governance
Joydeep Sen Sarma, Co-Founder & Head of Qubole India
Prior to co-founding Qubole, Joydeep worked at Facebook where he bootstrapped the data processing ecosystem based on Hadoop.
Joydeep started the Apache Hive project & led Facebook's Data Infrastructure team. He was also a key contributor on the Facebook Messages architecture team, & brought the power of Apache Hbase to Facebook & to the transactional & reporting backends for Facebook Credits.
Swag giveaway + food/drinks at 6:30pm
Power-Networking at 6:35pm
Presentation starts at 6:40pm
A Database Month event http://www.DBMonth.com/database/cloud-data-lake
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