Get more from Analytics 360 with BigQuery and the Google Cloud Platformjavier ramirez
If you are using Google Analytics 360, you can get much more from your data by using BigQuery to get better insights, and the rest of the cloud to get recommendations and predictions via Machine Learning. This presentation provides an introduction to Google BigQuery, Google Dataproc, Google Tensorflow/ML, and DataStudio 360 in the context of your analytics.
Google BigQuery for Everyday DeveloperMárton Kodok
IV. IT&C Innovation Conference - October 2016 - Sovata, Romania
A. Every scientist who needs big data analytics to save millions of lives should have that power
Legacy systems don’t provide the power.
B. The simple fact is that you are brilliant but your brilliant ideas require complex analytics.
Traditional solutions are not applicable.
The Plan: have oversight over developments as they happen.
Goal: Store everything accessible by SQL immediately.
What is BigQuery?
Analytics-as-a-Service - Data Warehouse in the Cloud
Fully-Managed by Google (US or EU zone)
Scales into Petabytes
Ridiculously fast
Decent pricing (queries $5/TB, storage: $20/TB) *October 2016 pricing
100.000 rows / sec Streaming API
Open Interfaces (Web UI, BQ command line tool, REST, ODBC)
Familiar DB Structure (table, views, record, nested, JSON)
Convenience of SQL + Javascript UDF (User Defined Functions)
Integrates with Google Sheets + Google Cloud Storage + Pub/Sub connectors
Client libraries available in YFL (your favorite languages)
Our benefits
no provisioning/deploy
no running out of resources
no more focus on large scale execution plan
no need to re-implement tricky concepts
(time windows / join streams)
pay only the columns we have in your queries
run raw ad-hoc queries (either by analysts/sales or Devs)
no more throwing away-, expiring-, aggregating old data.
Complex realtime event analytics using BigQuery @Crunch WarmupMárton Kodok
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.
Pub/Sub for the masses- Ein Einführungsworkshop in MQTT [GERMAN]Dominik Obermaier
Sprechen Sie MQTT? Dieser Workshop zeigt, was es mit dem schlanken und leichtgewichtigen IoT Protokoll auf sich hat und warum es sich zu einem Standardprotokoll für das Internet of Things etabliert hat. Lernen Sie, warum Pub/Sub für das Internet of Things skaliert und warum HTTP nicht der Weisheit letzter Schluss für alle IoT-Kommunikation ist. Neben einigen Live-Demos sowie einer Einführung in die Funktionsweise des schlanken Publish/Subscribe-Protokolls bekommen Sie Einblick in das junge und sehr aktive Ökosystem rund um MQTT.
Am Ende des Workshops wird ein Java basierter MQTT Todesstern Simulator inklusive Dashboard mit "MQTT over websocket" support entstehen.
An indepth look at Google BigQuery Architecture by Felipe Hoffa of GoogleData Con LA
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 Overview of Spanner: Google's Globally Distributed DatabaseBenjamin Bengfort
Spanner is a globally distributed database that provides external consistency between data centers and stores data in a schema based semi-relational data structure. Not only that, Spanner provides a versioned view of the data that allows for instantaneous snapshot isolation across any segment of the data. This versioned isolation allows Spanner to provide globally consistent reads of the database at a particular time allowing for lock-free read-only transactions (and therefore no communications overhead for consensus during these types of reads). Spanner also provides externally consistent reads and writes with a timestamp-based linear execution of transactions and two phase commits. Spanner is the first distributed database that provides global sharding and replication with strong consistency semantics.
IoT Analytics at Google Scale with James Chittenden: Using PubSub Dataflow, and BigQuery to Capture Millions of Connected Devices
There is the potential for 50 billion connected devices by 2020. Google Cloud Platform gives you the tools to scale connections, gather and make sense of data, and provide the reliable customer experiences that hardware devices require. Google’s Cloud Platform provides the infrastructure to handle streams of data fed from millions of intelligent devices.
In this meetup, we'll explore one of the world's largest appliance manufacturer's IoT architecture along with Google's partner Archipelago, and will drill into how they are leveraging Google's massive infrastructure in their solution. We'll explore what Google provides for IoT, including Pub/Sub for messaging, Dataflow for data processing, BigQuery for large scale analytics as well as best practices for real time stream processing accounting for ingest, processing, storage and analysis of hundreds of millions of events per hour.
Get more from Analytics 360 with BigQuery and the Google Cloud Platformjavier ramirez
If you are using Google Analytics 360, you can get much more from your data by using BigQuery to get better insights, and the rest of the cloud to get recommendations and predictions via Machine Learning. This presentation provides an introduction to Google BigQuery, Google Dataproc, Google Tensorflow/ML, and DataStudio 360 in the context of your analytics.
Google BigQuery for Everyday DeveloperMárton Kodok
IV. IT&C Innovation Conference - October 2016 - Sovata, Romania
A. Every scientist who needs big data analytics to save millions of lives should have that power
Legacy systems don’t provide the power.
B. The simple fact is that you are brilliant but your brilliant ideas require complex analytics.
Traditional solutions are not applicable.
The Plan: have oversight over developments as they happen.
Goal: Store everything accessible by SQL immediately.
What is BigQuery?
Analytics-as-a-Service - Data Warehouse in the Cloud
Fully-Managed by Google (US or EU zone)
Scales into Petabytes
Ridiculously fast
Decent pricing (queries $5/TB, storage: $20/TB) *October 2016 pricing
100.000 rows / sec Streaming API
Open Interfaces (Web UI, BQ command line tool, REST, ODBC)
Familiar DB Structure (table, views, record, nested, JSON)
Convenience of SQL + Javascript UDF (User Defined Functions)
Integrates with Google Sheets + Google Cloud Storage + Pub/Sub connectors
Client libraries available in YFL (your favorite languages)
Our benefits
no provisioning/deploy
no running out of resources
no more focus on large scale execution plan
no need to re-implement tricky concepts
(time windows / join streams)
pay only the columns we have in your queries
run raw ad-hoc queries (either by analysts/sales or Devs)
no more throwing away-, expiring-, aggregating old data.
Complex realtime event analytics using BigQuery @Crunch WarmupMárton Kodok
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.
Pub/Sub for the masses- Ein Einführungsworkshop in MQTT [GERMAN]Dominik Obermaier
Sprechen Sie MQTT? Dieser Workshop zeigt, was es mit dem schlanken und leichtgewichtigen IoT Protokoll auf sich hat und warum es sich zu einem Standardprotokoll für das Internet of Things etabliert hat. Lernen Sie, warum Pub/Sub für das Internet of Things skaliert und warum HTTP nicht der Weisheit letzter Schluss für alle IoT-Kommunikation ist. Neben einigen Live-Demos sowie einer Einführung in die Funktionsweise des schlanken Publish/Subscribe-Protokolls bekommen Sie Einblick in das junge und sehr aktive Ökosystem rund um MQTT.
Am Ende des Workshops wird ein Java basierter MQTT Todesstern Simulator inklusive Dashboard mit "MQTT over websocket" support entstehen.
An indepth look at Google BigQuery Architecture by Felipe Hoffa of GoogleData Con LA
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 Overview of Spanner: Google's Globally Distributed DatabaseBenjamin Bengfort
Spanner is a globally distributed database that provides external consistency between data centers and stores data in a schema based semi-relational data structure. Not only that, Spanner provides a versioned view of the data that allows for instantaneous snapshot isolation across any segment of the data. This versioned isolation allows Spanner to provide globally consistent reads of the database at a particular time allowing for lock-free read-only transactions (and therefore no communications overhead for consensus during these types of reads). Spanner also provides externally consistent reads and writes with a timestamp-based linear execution of transactions and two phase commits. Spanner is the first distributed database that provides global sharding and replication with strong consistency semantics.
IoT Analytics at Google Scale with James Chittenden: Using PubSub Dataflow, and BigQuery to Capture Millions of Connected Devices
There is the potential for 50 billion connected devices by 2020. Google Cloud Platform gives you the tools to scale connections, gather and make sense of data, and provide the reliable customer experiences that hardware devices require. Google’s Cloud Platform provides the infrastructure to handle streams of data fed from millions of intelligent devices.
In this meetup, we'll explore one of the world's largest appliance manufacturer's IoT architecture along with Google's partner Archipelago, and will drill into how they are leveraging Google's massive infrastructure in their solution. We'll explore what Google provides for IoT, including Pub/Sub for messaging, Dataflow for data processing, BigQuery for large scale analytics as well as best practices for real time stream processing accounting for ingest, processing, storage and analysis of hundreds of millions of events per hour.
使用 Raspberry pi + fluentd + gcp cloud logging, big query 做iot 資料搜集與分析Simon Su
This is a short training for introduce Pi to use fluentd to collect data and use Google Cloud Logging and BigQuery as backend and then use Apps Script and Google Sheet as presentation layer.