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You are here: Home / Customer Data / Google Boosts Cloud Data Services
Google Boosts Cloud Services To Tackle Big Data
Google Boosts Cloud Services To Tackle Big Data
By Frederick Lane / CRM Daily Like this on Facebook Tweet this Link thison Linkedin Link this on Google Plus
At the Hadoop Summit in Brussels on Thursday, Google announced significant updates to two of its cloud services. The changes will facilitate the processing of large quantities of data and open up the company's services to European data centers.

Big data promises to give companies faster and better insight, Google Product Manager William Vambenepe said Thursday on the Google Cloud Platform Blog. "Big data the cloud way means being more productive when building applications, with faster and better insights, without having to worry about the underlying infrastructure," he said.

Google Cloud Dataflow

Since first announced at its developers conference last summer, Google's Cloud Dataflow managed processing service for live data has been in private alpha testing. With today's launch of the beta version, the resource is now available to any software developer interested in testing it. However, because Cloud Dataflow is just in beta, no service-level agreement is currently available.

In his blog post, Vambenepe offered three key benefits of the new service: noOps (no operations in-house); cost effectiveness; and safe and easy collaboration. He also noted that the Cloud Dataflow service will automatically scale to meet the needs of its customers

"Today, nothing stands between you and the satisfaction of seeing your processing logic, applied in your choice of streaming or batch mode, executed via a fully managed processing service. Just write a program, submit it, and Cloud Dataflow will do the rest," Vambenepe said.

Google BigQuery

Google's other big announcement consisted of a number of upgrades to its five-year-old BigQuery service that offers users a SQL-interface for very large unstructured data sets.

The most significant change, given the recent regulatory issues in Europe, is that users can now host their data sets on Google servers located within Europe. While not directly addressing the search preference concerns raised by regulators, the move could be seen as an attempt to minimize European complaints.

Google also took steps to make BigQuery more secure. The company introduced what are known in the SQL community as row-level permissions. This will enable designers and users of SQL tables to implement access controls with greater levels of granularity. For instance, a sales manager can be given access to certain information within a database without necessarily having access to information relevant to human resources or accounting.

Finally, Google turned up the speed of BigQuery, giving it the capability of processing 100,000 rows from a database table in just one second.

Image credit: Google.

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Ilya Geller:
Posted: 2015-04-18 @ 8:10am PT
I discovered and patented how to structure any data: Language has its own Internal parsing, indexing and statistics. For instance, there are two sentences:

a) ‘Fire!’
b) ‘Dismay and anguish were depicted on every countenance; the males turned pale, and the females fainted; Mr. Snodgrass and Mr. Winkle grasped each other by the hand, and gazed at the spot where their leader had gone down, with frenzied eagerness; while Mr. Tupman, by way of rendering the promptest assistance, and at the same time conveying to any persons who might be within hearing, the clearest possible notion of the catastrophe, ran off across the country at his utmost speed, screaming ‘Fire!’ with all his might.’

Evidently, that the phrase ‘Fire!’ has different importance into both sentences, in regard to extra information in both. This distinction is reflected as the phrase weights: the first has 1, the second – 0.02; the greater weight signifies stronger emotional ‘acuteness’.
First you need to parse obtaining phrases from clauses, for sentences and paragraphs. Next, you calculate Internal statistics, weights; where the weight refers to the frequency that a phrase occurs in relation to other phrases.
After that data is indexed by common dictionary, like Merriam, and annotated by subtexts.
This is a small sample of the structured data:
this - signify - <> : 333333
both - are - once : 333333
confusion - signify - <> : 333321
speaking - done - once : 333112
speaking - was - both : 333109
place - is - in : 250000
To see the validity of the technology - pick up any sentence and try yourself. After that try a paragraph?

In New Internet information searches for users: no spying anymore.

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