Answer Tough Big Data and Big Analytics Questions with Google BigQuery

Introducing Google BigQuery

With Google BigQuery publicly available, all businesses can combine large data sets with amazing speed and do analytics in the cloud.

What Kinds of Questions Can You Answer With Google BigQuery?

Let’s say you are the marketing manager of a large B2C business that is driving traffic to your site through many channels including paid search, affiliates, email, and some offline campaigns as well. You really want to tie the campaign cost data all the way to your qualified leads, opportunities, and sales data, which typically resides in a CRM system, such as SalesForce, SugarCRM, or the like.

But why stop there? You also want to throw in your web analytics data and get engagement metrics in the mix. Last but not least, you’ve done your homework and implemented an integration strategy to tie all this data together (e.g. using a primary key).

You want to produce a very actionable report that shows:

Campaign cost data
Web analytics data
CRM data
A super actionable metric cost per qualified lead, broken down by campaign!

Report Analysis

In the above report, the cost per qualified lead for the Software Demo campaign in Google Adwords was just a little bit over $30, and you can start trending and optimizing accordingly. Run experiments and gather user feedback to bring that cost down!

Other Useful Features

Metrics like cost per qualified lead can be recalculated with amazing speed as often as the data is refreshed.
Results like this can be saved as a table, allowing you to build up layers of useful reports and then combine them to build even more useful reports.
Reports can be downloaded in CSV format for integration with Excel, PowerPoint, or whatever presentation and integration tools your business might use.
Unsampled reports from large data sets in Google Analytics Premium are the perfect kind of data set to upload to Google BigQuery.

Technical Details about Google BigQuery

Google BigQuery is a tool which allows businesses to gain insights from large data sets without any initial hardware purchases or software investments.
The BigQuery service is an online analytical processing (OLAP) system designed for terabyte-scale datasets.
The service supports SQL-like queries against those massive datasets.
BigQuery is surprisingly developer friendly, as it supports the straight forward REST (REpresentational State Transfer) Web service for pushing data to Google’s cloud and then querying it.
Google BigQuery can be accessed through a web tool or programmatically through the REST interface.
The web tool might be useful in visually identifying relationship and building queries, while the REST interface lets your developers get at the data in the most efficient way.