Systems | Development | Analytics | API | Testing

July 2018

Computing with Power Not Previously Possible with BigQuery & Compute Engine (Cloud Next '18)

Jul 26, 2018 By Google BigQuery In Google BigQuery
Learn how the top research universities are utilizing tools such as Google Compute Engine, BigQuery, and preemptible virtual machines to drastically reduce the time from idea to discovery, run millions of simulations at lightning-fast speed, and scale research capabilities with ease.
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Serverless Big Data Analytics at Traveloka (Cloud Next '18)

Jul 26, 2018 By Google BigQuery In Google BigQuery
In this session, we willl talk about the high level data architecture at Traveloka, Southeast Asia's leading online travel company. There are many existing solutions for big data analytics, both offered as managed services or open source. At Traveloka, we are going as serverless as possible.
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Serverless Data Warehouses Powered by Google Cloud Platform (Cloud Next '18)

Jul 26, 2018 By Google BigQuery In Google BigQuery
Topmost challenges that data warehouses have faced over the years are coping with storage requirements for ever-growing data and increased demand for compute to process this data. Google Cloud Platform has enabled creation of a completely serverless, scalable, flexible, and resilient data warehouse at Vuclip.
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Firebase & BigQuery - Do Mobile App Analytics Easily & at Scale - Queries Included (Cloud Next '18)

Jul 26, 2018 By Google BigQuery In Google BigQuery
In this session, we'll explain how your analytics data is stored in BigQuery and then show you some important tips on working with this data as we create queries to answer your burning mobile analytics questions.
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Data and Analytics Platform Overview and Customer Examples (Cloud Next '18)

Jul 26, 2018 By Google BigQuery In Google BigQuery
Using examples from the finance and retail industries we will walk through the core products in GCP data platform. The session will cover BigData analytics services such as: BigQuery, Dataflow, Pub/Sub, Dataproc, Dataprep, Datalab, and Datastudio.
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BigQuery Nested and Repeated Fields: Dig Deeper into Data (Cloud Next '18)

Jul 26, 2018 By Google BigQuery In Google BigQuery
Are you ready to take your knowledge of SQL to its final frontiers? Join this session to learn how you can use BigQuery and its SQL 2011 compliant features to tap deep into insights locked away in your spreadsheets, JSON files, and other semi-structured data formats.
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Building the World's Largest Enterprise Data Warehouse with BigQuery (Cloud Next '18)

Jul 26, 2018 By Google BigQuery In Google BigQuery
This talk, by one of the founders of the BigQuery team and a founder and current CTO of Looker, will make the case that BigQuery is not just another Enterprise Data Warehouse. It will show how BigQuery's unique properties follow from its technical architecture.
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Diving into Your Billing Data with BigQuery and DataStudio (Cloud Next '18)

Jul 26, 2018 By Google BigQuery In Google BigQuery
Many large organizations build custom dashboards and reporting around their cloud usage to track that usage across teams and applications, and to understand cost drivers. In this session, the Billing team and Vendasta will show you how to export your detailed billing data to BigQuery, write useful queries around that data, and create custom dashboards based on those queries in Data Studio.
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How BuzzFeed Built A Great Data Experience Using BigQuery and Looker (Cloud Next '18)

Jul 26, 2018 By Google BigQuery In Google BigQuery
This talk will focus on how BigQuery and Looker allowed a small data team at Buzzfeed to manage the data needs of 800 users, and how migrating from AWS Redshift to BigQuery gave us the performance we needed to allow interactive querying of large datasets by non-technical people.
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bigquery

Bridging the gap between data and insights

Jul 25, 2018 By Sudhir Hasbe In Google BigQuery

Today, we want to share a number of updates that will make data analytics easier and more accessible to all businesses. Our goal is to help you focus on data analysis instead of infrastructure management, give you the freedom to orchestrate workloads across clouds, use machine-learning in a way that's integrated with your data analytics operations, and take advantage of open source data processing innovation.

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