How to: Analyze Data from BigQuery using GoodData and CloudConnect

I really like playing around with cutting edge technologies. One of them is GoodData CloudConnect, the tool for ETL and building GoodData projects. Since we released this new feature, I have dozens of ideas how the data from various sources can be easily transformed in the cloud. Recently, for example, I found myself wondering: “How about using the Google BigQuery API as a data source? What about visualizing the data from it in GoodData?”

I know that BigQuery has a sample datasets like weather data, Github data or data from Wikipedia. How about using weather data to analyze average temperatures in San Francisco from the last 20 years?

More from source: How to: Analyze Data from BigQuery using GoodData and CloudConnect

BigQuery Best Practices and open Office Hours - Live from London

Google BigQuery - Best Practices for Loading your Data and open Office H...

Michael Manoochehri and Ryan Boyd from the DevRel team for cloud data services will be streaming to you live! They'll be discussing how to load your data into BigQuery and the various options available -- from commercial ETL tools to App Engine's Pipeline API and MapReduce frameworks, to simple UNIX command-line tools. 

They'll then open it up for a general office hours on ingestion and other topics. Please use the moderator link to ask your questions.

Google BigQuery Visualisation

Last month Google announced the public launch of Google BigQuery (http://cloud.google.com/bigquery/), which lets you gather real-time business insights from massive amounts of data without any hardware or software investments.

Today on the Google Enterprise Blog, Google shows you how two data visualization providers – Qlikview and BIME – have created visual dashboards built using Google BigQuery.

http://goo.gl/QHv0R

Google, Big Data & What it Means for SEO

In Google’s recent earnings call, the question was posed, “If you think of the future of Internet search 3 or 4 years out, how important will the social signal be and how important (will) personalization be?”

CEO Larry Page responded by explaining how he might search for one of his friends who had a common name.

“For the first time, the search box isn’t really searching a string...it’s actually searching for that person that I know,” Page said. “Having real feedback from users...is very useful for search...we have a lot of those signals already, but we can always use more...we can always use better relevance and we can always use more data to generate that.”

Page’s response reveals two insights into how Google is thinking about big data

Jump to source Google, Big Data & What it Means for SEO - Search Engine Watch (#SEW)

Using Google BigQuery to learn from GitHub data

Open-source developers all over the world contribute to millions of projects every day: writing and reviewing code, filing and discussing bug reports, updating documentation and project wikis, and so forth. The data generated from this activity can reveal interesting trends across many industries, including popularity of programming languages over time, defect rates, contribution metrics, and popularity of specific frameworks and libraries.


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Big Data Week Hackathon

Data science communities all over the world are joining in Big Data Week by hosting simultaneous hackathon meetups in their own cities. From London to San Francisco, New York to Melbourne, and the list continues to expand.  The event is happening in little over a month, but we’ve got you covered if you want to host a data hackathon hotspot.  All you need is a local data science community, a 24-hour venue, and an internet connection.  

 Information on the Data Science London, who started the event, is available at http://datasciencehackathon.com/hello-world/

For more info on Big Data Week, of which this contest is a featured event, go to www.bigdataweek.com.

BigQuery, meet Google Spreadsheets

Google announced the integration of BigQuery with Google Apps Scriptand Google Spreadsheets, a feature that was first demoed at Google IO. With this integration users now have the power to query multi-billion row tables, visualize the results and share them with others. Below you can see a simple script that queries a sample dataset and plots the results. A simple tutorial is available here with more to come soon.