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Introduction
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Search interface 20
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Analytics interface of today
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Optimised for real time
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Worked examples
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UK Housing data: percentiles
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UK Housing data: terms
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Geo as a common link between datasets: housing crime
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Connected data: Enron emails
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Recommendations: MovieLens data
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Random samples should hold no surprises
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Non random sample: people who liked Talladega nights
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Problem: avoid analysis of poorly focused sets
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How do we get a smaller, representative sample of users?
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Putting search and analytics together..
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Amazon marketplace reviews
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Anatomy of an entity indexing groovy script
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Drilling down into seller #187's fanboys
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UK car roadworthiness test: raw data
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Derived car attributes
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Miles driven vs number of days for fix
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In summary
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Questions?
Description:
Explore powerful data analysis techniques using Elasticsearch's Aggregation Framework in this 45-minute conference talk from GOTO Amsterdam 2015. Discover how to extract valuable insights from large datasets without the need for expensive data scientists. Learn through practical examples including UK housing data, crime statistics, Enron emails, and MovieLens recommendations. Understand the importance of representative sampling and how to combine search and analytics effectively. Dive into real-world applications such as Amazon marketplace reviews and UK car roadworthiness tests. Gain insights into entity indexing, derived attributes, and data visualization techniques. Master the art of wrestling with big data using Elasticsearch's out-of-the-box algorithms and optimize your data analysis workflow for real-time results.

Professional Data - Wrestling Techniques Using Elasticsearch's Aggregation Framework

GOTO Conferences
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