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Seo Master present to you: One of the most exciting things about the architecture of the web is how easily it supports mashups—URLs, IFRAMEs, XHR, and more make it easy to build great new services on top of building blocks from others. As more and more people use the web for non-public data, we need new techniques to secure those building blocks. That’s where OAuth comes in—an open, standard way for users to grant permission for an application to access part of their account.

Since we announced support for OAuth in 2008, we've seen tremendous usage growth in our APIs that require user authorization, like Calendar and Docs. While the spec isn't completely finalized, Google is pleased to announce our experimental support of an easier way for developers to obtain user authorization for our APIs: OAuth 2.0 with bearer tokens. Whether you use our updated client libraries or just write to the protocol, you should be able to do more with less code.

In addition to supporting a simplified protocol, we're also introducing a simpler, cleaner consent page for OAuth 2.0:


Google believes in open systems that give users value, transparency and control. We hope the OAuth 2.0 protocol helps developers deliver just that: powerful applications that make use of user data without compromising on safety or security. Check out our documentation to get started with OAuth 2.0.

By Andrew Wansley, Google Developer Team2013, By: Seo Master

seo Making auth easier: OAuth 2.0 for Google APIs 2013

Seo Master present to you: Author Photo
By Michael Manoochehri, Developer Programs Engineer, Cloud Platform

Google BigQuery is designed to make it easy to analyze large amounts of data quickly. Overwhelmingly, developers have asked us for features to help simplify their work even further. Today we are launching a collection of updates that gives BigQuery a greater range of query and data types, more flexibility with table structure, and better tools for collaborative analysis.

Big JOIN and Big Group Aggregations

Extracting insights from multiple datasets can be challenging and time-consuming. This is especially true when datasets become too large to query with a traditional database system. With traditional databases, SQL functions like joining and grouping are typically used to bring together data for analysis. What happens when your data is too large to fit into a conventional database? Working with multi-terabyte datasets often requires developing complicated MapReduce workflows, investing in expensive infrastructure, and great deal of time. Very often, it's a combination of all three.

In response to developer feedback, we're launching new features that enable analysts and developers to run fast SQL-like join and aggregate queries on datasets without the need for batch-based processing. Our new Big JOIN feature gives users the ability to produce a result set by merging data from two large tables by a common key. Big JOIN simplifies data analysis that would otherwise require a data transformation step, by allowing users to specify JOIN operations using SQL.

Popular web applications produce user activity logs that can grow by billions of rows each week. Dividing users into smaller groups is a key step for analysis. However, each group of users can number in the millions. To handle this for such large volumes, we've enabled Big Group Aggregations, which significantly increases the number of distinct values that can be grouped in a result set.

To use these new features, simply add the EACH modifier to JOIN or GROUP BY clauses.


/* JOIN EACH example
* Selects the top 10 most edited Wikipedia pages
* of words that appear in works of Shakespeare.
*/

SELECT
 TOP(wiki.title, 10), COUNT(*)
FROM
 [publicdata:samples.wikipedia] AS wiki
JOIN EACH
 [publicdata:samples.shakespeare] AS shakespeare
ON
 shakespeare.word = wiki.title;


For more information, including best practices, when using JOIN EACH and GROUP EACH BY, visit the BigQuery query reference.

Native support for TIMESTAMP data type

We are also adding a new TIMESTAMP data type, in response to one of our most frequent requests from developers. This new data type lets you import date and time values in formats familiar to users of databases such as MySQL, while preserving timezone offset information.

Along with the new data type come new functions for converting TIMESTAMP fields into other formats, calculating intervals, and extracting components such as the hour, day of week, and quarter.


/* TIMESTAMP example
* Which hours in the day are the most popular for GitHub actions?
* This query converts github_timeline "created_at" date time   
* strings to BigQuery TIMESTAMP, and extracts the hour from each.
*/

SELECT
 HOUR(TIMESTAMP(created_at)) AS event_create_hour,
 COUNT(*) AS event_count
FROM
 [publicdata:samples.github_timeline]
GROUP BY
 event_create_hour
ORDER BY
 event_count DESC;


Read more about the available TIMESTAMP functions in our query reference guide.

Add columns to existing BigQuery tables

When working with large amounts of fast moving data, it's not uncommon to find out that you need to add additional fields to your tables. In response to developer feedback, we have added the ability to add new columns to existing BigQuery tables.

To take advantage of this feature, simply provide a new schema with additional columns using either the "Tables: update" or "Tables: patch" BigQuery API methods.

For more information on this feature, visit the BigQuery API reference.

BigQuery Web UI: Dataset links and dataset sharing notifications

BigQuery has always provided project owners with very fine-grained control of how their datasets are shared. To make it easier for teams to work on collaborative data analysis, we've added direct links to individual datasets in the BigQuery Web UI. This provides a convenient way for authorized users to quickly access a dataset, and allows for bookmarking and sharing.

In addition, we've also added email notifications to inform users when they've been given dataset access privileges. When a dataset has been shared with another user via the sharing control panel, BigQuery sends a notification email containing a direct link to the dataset.


The BigQuery UI features a collection of public datasets for you to use when trying out these new features. To get started, visit our sign up page and Quick Start guide. You should take a look at our API docs, and ask questions about BigQuery development on Stack Overflow. Finally, don't forget to give us feedback and join the discussion on our Cloud Platform Developers Google+ page.


Michael Manoochehri is a Developer Programs Engineer supporting the Google Cloud Platform. His goal is to help make cloud computing and data analysis universally accessible and useful.

Posted by Scott Knaster, Editor
2013, By: Seo Master

seo BigQuery gets big new features to make data analysis even easier 2013

Seo Master present to you:
Theft of personal data is a rising phenomenon and seems to be growing as technology further progresses. What’s more, businesses and organizations are equally affected by this menace. Despite having in place data security measures, individuals and organizations can still fall victim to data thieves. So why is your data so important to these e-criminals? The answer is simple; your data can be used clear-out your bank account, or worse, steal your identity to commit fraud and other criminal activities.

There are many mistakes organizations and individuals can make which can lead to theft of their data. Taking simple measures can certainly safeguard your data from potential theft. The following is a list of things you need to be aware of in-order to protect yourself.

Shred your paper work:

            If you decide to discard any documents, such as credit statements, bank statements, utility bills and other related information, then you need to make it a habit to shred such documents every time you decide to throw them out.  More than often, Dumpster-divers will often go through your pile of garbage seeking out un-shredded statements containing bits of your personal information. Once these so called “Dumpster-divers” get a hold of your information, it’s only a matter of time before they use your information to max out your credit card, or perhaps transfer your life savings from your savings account, to an offshore account.

To effectively shred such documents, make sure you make use a cross-shredder instead of a traditional shredder. Cross-shredders can shred such documents much more effectively than traditional shredders.

Smash your old hard-drive into pieces:

           This step may seem a bit on the extreme side, but that’s what you have to do in order to keep your personal data safe. Even if you had previously stored personal data on your hard-drive and then happened to delete that data -- thinking it was permanently wiped-out of your hard-drive; chances are your deleted data could still be retrieved. Data recovery software can easily recover most permanently deleted data.

           When you empty your recycle bin, it may appear that the data stored in your recycle bin is gone forever. However, bits of data are always present on your hard-drive, and basic data recovery software can easily retrieve such deleted data. Thus, when you send in your old desktop or laptop for recycling, chances are that someone may try to retrieve your personal data on your laptop or desktop.  Therefore, this is the reason why you need to smash your hard-drive, before you recycle your machine.

Use anti-data theft software and antivirus software:

           If you, for some reason, need to store confidential data on your personal computer, you can do so securely with the help software that can lock folders. Moreover, investing in good anti-virus software will help you keep your identity safe on the internet.

Stay away from Phishing email:

           Phishing is the practice of recording your personal user-names and passwords so that some kind of fraud can be conducted using your log-in credentials. The scam works something like this: you receive an email from Facebook, or perhaps your bank, prompting you to log-in, so that your identity can be confirmed. Most people don’t think twice about such emails, and will log-in to confirm their accounts and to prove their identities. Little do you know, in the background, your credentials are being recorded by key-logging software!

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2013, By: Seo Master

seo Keeping Personal Data Safe: Mistakes You Should Avoid 2013

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