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Explore about Google BigQuery, this presentation was featured as a talk at Google DevFest 2014, Mumbai presented by me.
Exploring BigData with Google BigQuery
Exploring BigData with Google BigQuery
Dharmesh Vaya
An short introduction on Big Query. With this presentation you'll quickly discover : How load data in BigQuery How to build dashboard using BigQuery How to work with BigQuery and, at last but not least, we've added some best practices We hope you'll enjoy this presentation and that it will help you to start exploring this wonderful solution. Don't hesitate to send us your feedbacks or questions
BigQuery for Beginners
BigQuery for Beginners
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As part of Treasure Data CDP, We use Trino for the following two purposes: ・As a query engine for direct access to data stored by custom SQL ・As a query engine to execute auto-generated SQL based on the logic from GUI Although some restrictions are placed on the functionality of Trino as our service, the former enables customers to execute queries freely, similar to Trino as a Service or Amazon Athena. By introducing the usage of Trino at Treasure Data, I will show what you should expect when you open Trino to your users.
Learn from Case Study; How do people run query on Trino? / Trino japan virtua...
Learn from Case Study; How do people run query on Trino? / Trino japan virtua...
Toru Takahashi
This is an introductory presentation given at DevFest Madrid 2010 by Google Developer Advocate Chris Schalk. It introduces new Google cloud technologies: Google Storage, Google Prediction API and BigQuery.
Intro to new Google cloud technologies: Google Storage, Prediction API, BigQuery
Intro to new Google cloud technologies: Google Storage, Prediction API, BigQuery
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At teowaki we are using Google BigQuery to get analytics from our API usage. Learn how you can benefit from BigQuery to have Big Data analytics.
Big Data Analytics with Google BigQuery. By Javier Ramirez. All your base Co...
Big Data Analytics with Google BigQuery. By Javier Ramirez. All your base Co...
javier ramirez
Google Cloud Bigquery, um jeito novo de fazer Analytics e Datawarehouse
TDC2016SP - Trilha BigData
TDC2016SP - Trilha BigData
tdc-globalcode
BigQuery is Google's columnar, massively parallel data querying solution. This talk explores using it as an ad-hoc reporting solution and the limitations present in May 2013.
How BigQuery broke my heart
How BigQuery broke my heart
Gabriel Hamilton
A quick guide to the simple UDF functionality now exposed in Google Big Query.
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Explore about Google BigQuery, this presentation was featured as a talk at Google DevFest 2014, Mumbai presented by me.
Exploring BigData with Google BigQuery
Exploring BigData with Google BigQuery
Dharmesh Vaya
An short introduction on Big Query. With this presentation you'll quickly discover : How load data in BigQuery How to build dashboard using BigQuery How to work with BigQuery and, at last but not least, we've added some best practices We hope you'll enjoy this presentation and that it will help you to start exploring this wonderful solution. Don't hesitate to send us your feedbacks or questions
BigQuery for Beginners
BigQuery for Beginners
Better&Stronger
As part of Treasure Data CDP, We use Trino for the following two purposes: ・As a query engine for direct access to data stored by custom SQL ・As a query engine to execute auto-generated SQL based on the logic from GUI Although some restrictions are placed on the functionality of Trino as our service, the former enables customers to execute queries freely, similar to Trino as a Service or Amazon Athena. By introducing the usage of Trino at Treasure Data, I will show what you should expect when you open Trino to your users.
Learn from Case Study; How do people run query on Trino? / Trino japan virtua...
Learn from Case Study; How do people run query on Trino? / Trino japan virtua...
Toru Takahashi
This is an introductory presentation given at DevFest Madrid 2010 by Google Developer Advocate Chris Schalk. It introduces new Google cloud technologies: Google Storage, Google Prediction API and BigQuery.
Intro to new Google cloud technologies: Google Storage, Prediction API, BigQuery
Intro to new Google cloud technologies: Google Storage, Prediction API, BigQuery
Chris Schalk
At teowaki we are using Google BigQuery to get analytics from our API usage. Learn how you can benefit from BigQuery to have Big Data analytics.
Big Data Analytics with Google BigQuery. By Javier Ramirez. All your base Co...
Big Data Analytics with Google BigQuery. By Javier Ramirez. All your base Co...
javier ramirez
Google Cloud Bigquery, um jeito novo de fazer Analytics e Datawarehouse
TDC2016SP - Trilha BigData
TDC2016SP - Trilha BigData
tdc-globalcode
BigQuery is Google's columnar, massively parallel data querying solution. This talk explores using it as an ad-hoc reporting solution and the limitations present in May 2013.
How BigQuery broke my heart
How BigQuery broke my heart
Gabriel Hamilton
A quick guide to the simple UDF functionality now exposed in Google Big Query.
Google Big Query UDFs
Google Big Query UDFs
David Gloyn-Cox
Session presented at Big Data Spain 2012 Conference 16th Nov 2012 ETSI Telecomunicacion UPM Madrid www.bigdataspain.org More info: http://www.bigdataspain.org/es-2012/conference/crunching-data-with-google-bigquery/jordan-tigani
Crunching Data with Google BigQuery. JORDAN TIGANI at Big Data Spain 2012
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Get some insight into the evolution of open source databases, broadening use cases, and choosing the right solutions for the future.
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Vadim Solovey is a CTO of DoiT International has helped to implement Google BigQuery as a cloud data warehouse for many medium and large sized data and analytics initiatives. BigQuery’s serverless architecture had redefined what it means to be fully managed for hundreds of Israeli's startups. Recently, Google announced an update to BigQuery that dramatically advances cloud data analytics for large-scale businesses such as BigQuery now support Standard SQL, implementing the SQL 2011 standard as well as new ODBC drivers making it possible to use BigQuery with a number of tools ranging from Microsoft Excel to traditional business intelligence systems such as Microstrategy and Qlik. Agenda: • Partitioned tables • The ability to update, delete rows and columns using SQL • Integration with IAM for fine-grained security policies • Monitoring w/ StackDriver to track performance and usage • Query sharing via links, to foster knowledge within orgs • Cost optimisation strategies
Google BigQuery 101 & What’s New
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in this presentation we go through the differences and similarities between Redshift and BigQuery. It was presented during the Athens Big Data meetup May 2017.
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parse.com tutorial
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Google Developer Group (GDG) Sonargaon is a community based focused group for developers on Google and related technologies. I tried to cover a topic on Big Data & BigQuery which is the future of analytics.
Google BigQuery is the future of Analytics! (Google Developer Conference)
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Rasel Rana
Complex event analytics solutions require massive architecture, and Know-How to build a fast real-time computing system. Google BigQuery solves this problem by enabling super-fast, SQL-like queries against append-only tables, using the processing power of Google’s infrastructure.In this presentation we will see how Bigquery solves our ultimate goal: Store everything accessible by SQL immediately at petabyte-scale. We will discuss some common use cases: funnels, user retention, affiliate metrics.
Complex realtime event analytics using BigQuery @Crunch Warmup
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Márton Kodok
Abstract:- Come learn about Google BigQuery and its underlying architecture. Felipe will go over the evolution of BigQuery and explain some of the underlying principles of BigQuery and Dremel. Felipe will also go over some of the latest use cases and will demo a use case of Google BigQuery Bio:- Felipe Hoffa moved from Chile to San Francisco to join Google as a Software Engineer. Since 2013 he's been a Developer Advocate on big data - to inspire developers around the world to leverage the Google Cloud Platform tools to analyze and understand their data in ways they could never before. You can find him in several YouTube videos, blog posts, and conferences around the world. Follow Felipe at https://twitter.com/felipehoffa.
An indepth look at Google BigQuery Architecture by Felipe Hoffa of Google
An indepth look at Google BigQuery Architecture by Felipe Hoffa of Google
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Podle čeho byste měli vybírat vhodnou Big Data platfomu pro vaše potřeby?
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In this session it will presented main workflows and technologies of getting value from Big Data stored in our Enterprise using Azure. - When we have a Big Data problem - Finding the best solution for our Big Data - Working inside the Data Team - Extract the true value of our data.
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Google is expanding our storage products by introducing Google Storage for Developers. It offers a RESTful API for storing and accessing data at Google. Developers can take advantage of the performance and reliability of Google's storage infrastructure, as well as the advanced security and sharing capabilities. We will demonstrate key functionality of the product as well as customer use cases. Google relies heavily on data analysis and has developed many tools to understand large datasets. Two of these tools are now available on a limited sign-up basis to developers: (1) BigQuery: interactive analysis of very large data sets and (2) Prediction API: make informed predictions from your data. We will demonstrate their use and give instructions on how to get access.
GDD Brazil 2010 - Google Storage, Bigquery and Prediction APIs
GDD Brazil 2010 - Google Storage, Bigquery and Prediction APIs
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A Data Ecosystem to Support Machine Learning in Materials Science
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Session presented at Big Data Spain 2012 Conference 16th Nov 2012 ETSI Telecomunicacion UPM Madrid www.bigdataspain.org More info: http://www.bigdataspain.org/es-2012/conference/crunching-data-with-google-bigquery/jordan-tigani
Crunching Data with Google BigQuery. JORDAN TIGANI at Big Data Spain 2012
Crunching Data with Google BigQuery. JORDAN TIGANI at Big Data Spain 2012
Big Data Spain
Get some insight into the evolution of open source databases, broadening use cases, and choosing the right solutions for the future.
Your data layer - Choosing the right database solutions for the future
Your data layer - Choosing the right database solutions for the future
ObjectRocket
Vadim Solovey is a CTO of DoiT International has helped to implement Google BigQuery as a cloud data warehouse for many medium and large sized data and analytics initiatives. BigQuery’s serverless architecture had redefined what it means to be fully managed for hundreds of Israeli's startups. Recently, Google announced an update to BigQuery that dramatically advances cloud data analytics for large-scale businesses such as BigQuery now support Standard SQL, implementing the SQL 2011 standard as well as new ODBC drivers making it possible to use BigQuery with a number of tools ranging from Microsoft Excel to traditional business intelligence systems such as Microstrategy and Qlik. Agenda: • Partitioned tables • The ability to update, delete rows and columns using SQL • Integration with IAM for fine-grained security policies • Monitoring w/ StackDriver to track performance and usage • Query sharing via links, to foster knowledge within orgs • Cost optimisation strategies
Google BigQuery 101 & What’s New
Google BigQuery 101 & What’s New
DoiT International
Introduction to Google BigQuery. Slides used at the first GDG Cloud meetup in Brussels, about big data on Google Cloud Platform. (http://www.meetup.com/GDG-Cloud-Belgium/events/228206131)
Google BigQuery
Google BigQuery
Matthias Feys
in this presentation we go through the differences and similarities between Redshift and BigQuery. It was presented during the Athens Big Data meetup May 2017.
Redshift VS BigQuery
Redshift VS BigQuery
Kostas Pardalis
parse.com tutorial
Parse.com
Parse.com
Hyungook Yoon
Google Developer Group (GDG) Sonargaon is a community based focused group for developers on Google and related technologies. I tried to cover a topic on Big Data & BigQuery which is the future of analytics.
Google BigQuery is the future of Analytics! (Google Developer Conference)
Google BigQuery is the future of Analytics! (Google Developer Conference)
Rasel Rana
Complex event analytics solutions require massive architecture, and Know-How to build a fast real-time computing system. Google BigQuery solves this problem by enabling super-fast, SQL-like queries against append-only tables, using the processing power of Google’s infrastructure.In this presentation we will see how Bigquery solves our ultimate goal: Store everything accessible by SQL immediately at petabyte-scale. We will discuss some common use cases: funnels, user retention, affiliate metrics.
Complex realtime event analytics using BigQuery @Crunch Warmup
Complex realtime event analytics using BigQuery @Crunch Warmup
Márton Kodok
Abstract:- Come learn about Google BigQuery and its underlying architecture. Felipe will go over the evolution of BigQuery and explain some of the underlying principles of BigQuery and Dremel. Felipe will also go over some of the latest use cases and will demo a use case of Google BigQuery Bio:- Felipe Hoffa moved from Chile to San Francisco to join Google as a Software Engineer. Since 2013 he's been a Developer Advocate on big data - to inspire developers around the world to leverage the Google Cloud Platform tools to analyze and understand their data in ways they could never before. You can find him in several YouTube videos, blog posts, and conferences around the world. Follow Felipe at https://twitter.com/felipehoffa.
An indepth look at Google BigQuery Architecture by Felipe Hoffa of Google
An indepth look at Google BigQuery Architecture by Felipe Hoffa of Google
Data Con LA
Podle čeho byste měli vybírat vhodnou Big Data platfomu pro vaše potřeby?
Výběr Big Data platformy - Jan Sovka - IBM
Výběr Big Data platformy - Jan Sovka - IBM
Profinit
In this session it will presented main workflows and technologies of getting value from Big Data stored in our Enterprise using Azure. - When we have a Big Data problem - Finding the best solution for our Big Data - Working inside the Data Team - Extract the true value of our data.
Big Data Analytics: Finding diamonds in the rough with Azure
Big Data Analytics: Finding diamonds in the rough with Azure
Christos Charmatzis
BigQuery, Google Cloud, Big Data
Big query
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Tanvi Parikh
Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...
Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...
MongoDB
CONTEXT – Write once data load - Ex. Time-series data.Which Database? SSD is Good MPP is Good Columnar is Good Logical Partition is Good Data Skew Partition is Good Search Engine Index could lead to Index Explosion Concurrent Users First, Single Query Performance Next High Throughput File level Snapshot Loading Calculate cost upfront Data Structure makes a Big Difference
Ten things to consider for interactive analytics on write once workloads
Ten things to consider for interactive analytics on write once workloads
Abinasha Karana
How to get the best of both: MongoDB is great for low latency quick access of recent data; Treasure Data is great for infinitely growing store of historical data. In the latter case, one need not worry about scaling.
Augmenting Mongo DB with treasure data
Augmenting Mongo DB with treasure data
Treasure Data, Inc.
Data Science and Big Data Corporate Training
Hudson Data Corp Training
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Menish Gupta
Google is expanding our storage products by introducing Google Storage for Developers. It offers a RESTful API for storing and accessing data at Google. Developers can take advantage of the performance and reliability of Google's storage infrastructure, as well as the advanced security and sharing capabilities. We will demonstrate key functionality of the product as well as customer use cases. Google relies heavily on data analysis and has developed many tools to understand large datasets. Two of these tools are now available on a limited sign-up basis to developers: (1) BigQuery: interactive analysis of very large data sets and (2) Prediction API: make informed predictions from your data. We will demonstrate their use and give instructions on how to get access.
GDD Brazil 2010 - Google Storage, Bigquery and Prediction APIs
GDD Brazil 2010 - Google Storage, Bigquery and Prediction APIs
Patrick Chanezon
BitBootCamp Evening Classes
BitBootCamp Evening Classes
BitBootCamp Evening Classes
Menish Gupta
This presentation was given at the 2019 GlobusWorld Conference in Chicago, IL by Ben Blaiszik from University of Chicago and Argonne National Laboratory Data Science and Learning Division.
A Data Ecosystem to Support Machine Learning in Materials Science
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Crunching Data with Google BigQuery. JORDAN TIGANI at Big Data Spain 2012
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Your data layer - Choosing the right database solutions for the future
Google BigQuery 101 & What’s New
Google BigQuery 101 & What’s New
Google BigQuery
Google BigQuery
Redshift VS BigQuery
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Parse.com
Parse.com
Google BigQuery is the future of Analytics! (Google Developer Conference)
Google BigQuery is the future of Analytics! (Google Developer Conference)
Complex realtime event analytics using BigQuery @Crunch Warmup
Complex realtime event analytics using BigQuery @Crunch Warmup
An indepth look at Google BigQuery Architecture by Felipe Hoffa of Google
An indepth look at Google BigQuery Architecture by Felipe Hoffa of Google
Výběr Big Data platformy - Jan Sovka - IBM
Výběr Big Data platformy - Jan Sovka - IBM
Big Data Analytics: Finding diamonds in the rough with Azure
Big Data Analytics: Finding diamonds in the rough with Azure
Big query
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Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...
Big Data Analytics 3: Machine Learning to Engage the Customer, with Apache Sp...
Ten things to consider for interactive analytics on write once workloads
Ten things to consider for interactive analytics on write once workloads
Augmenting Mongo DB with treasure data
Augmenting Mongo DB with treasure data
Hudson Data Corp Training
Hudson Data Corp Training
GDD Brazil 2010 - Google Storage, Bigquery and Prediction APIs
GDD Brazil 2010 - Google Storage, Bigquery and Prediction APIs
BitBootCamp Evening Classes
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A Data Ecosystem to Support Machine Learning in Materials Science
A Data Ecosystem to Support Machine Learning in Materials Science
Google Cloud Platform at Vente-Exclusive.com
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How is AI changing journalism? (v. April 2024)
How is AI changing journalism? (v. April 2024)
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Slides from a workshop exploring "Moving Beyond Twitter/X and Facebook - Social Media for local news providers" This presentation outlines social media habits in the US (and globally) and offers suggestions for how local newsrooms can tap into them. The presentation features key data, user case studies and recommendations for new things to try out. The presentation was part of the New York Press Association's 2024 spring conference. https://nynewspapers.com/2024-nypa-spring-conference/
Moving Beyond Twitter/X and Facebook - Social Media for local news providers
Moving Beyond Twitter/X and Facebook - Social Media for local news providers
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Geoff Huston, Chief Scientist at APNIC deliver keynote presentation on the 'Future Evolution of the Internet' at the Everything Open 2024 conference in Gladstone, Australia from 16 to 18 April 2024.
'Future Evolution of the Internet' delivered by Geoff Huston at Everything Op...
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APNIC
Geoff Huston, Chief Scientist at APNIC, presents 'Networking in the Penumbra' at NZNOG 2024 in Nelson New Zealand from 8 to 12 April 2024.
Networking in the Penumbra presented by Geoff Huston at NZNOG
Networking in the Penumbra presented by Geoff Huston at NZNOG
APNIC
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