Big Data. Big Decisions
InformationWeek
Special Coverage Series


Google, Tableau Team On Big Data

Google BigQuery lets data analysts do fast, SQL-style querying. Tableau Software brings data visualization power to let business users in on the big data platform.

 Big Data Talent War: 7 Ways To Win
Big Data Talent War: 7 Ways To Win
(click image for larger view and for slideshow)
Google and Tableau Software announced a partnership late last week that brings together two of the hottest trends in IT: big data and data visualization.

One the big data side is Google's cloud-based BigQuery analytics platform, introduced in May and one of the biggest announcements of the year in the category. It's not just that it's from Google, an association that gave BigQuery instant credibility; it's that this big data service combines scalability and real-time querying with SQL-like query statements.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

Under the hood of BigQuery there's the Google File System and Google MapReduce, the core components of Google's big data platform that inspired Hadoop. There's also Dremel, a real-time, distributed query and analysis technology that Google has been working on for five years. Dremel lets users interactively query massive, disparate data sets on Google's platform with the kind of performance they're used to seeing from relational databases. That's also the kind of fast query capability that Cloudera is now hoping to help deliver on the Hadoop platform through its recently announced beta-stage Cloudera Impala project.

[ Want more on Google's cloud-based big data platform? Read Google Launches BigQuery Analytics Service. ]

There's a vast pool of data professionals out there that knows just what to do with the SQL-like select, aggregation, sum and string-matching options that BigQuery provides. But then there's the far larger universe of business analysts and professionals who aren't SQL savvy. That's where Tableau Software comes in.

Tableau is known for intuitive, business-user-friendly data visualization software that has helped make it one the fastest-growing vendors in business intelligence. Through a partnership the two companies have been working on together for five months, Tableau has added a connection to BigQuery in Tableau 8, a next release also announced last week and due out early next year.

"Somebody on the marketing team or the operations team of a company may not know SQL, but they sure know the business and they know the data," said Ju-kay Kwek, product manager of Google BigQuery, in an interview with InformationWeek. "With Tableau in the hands of these business users, they can now connect to an enormous data source and interact with that information in a visual and intuitive way."

Users of Tableau's desktop or server-based software won't have to know a thing about data integration or data mapping, according to Tableau, as BigQuery will show up on the data-source menu like any database, spreadsheet or flat file. With Google's servers doing all the big data heavy lifting, Tableau users will be able to fly through vast data sets with all the visualization options they're accustomed to in the software.

"We love data sources that offer fast query response times, and that's been a big challenge for people who have large amounts of data," Dan Jewett, Tableau's VP of product management, told InformationWeek. "BigQuery just makes it go fast, and you don't have to worry about things like materialized views, pre-aggregations and cubes that become lengthy and expensive IT projects."

With the BigQuery announcement, many speculated that most users of the service would be Google Analytics customers with vast stores of Web analytics data already residing in Google's cloud.

But Google also has landed BigQuery customers in the automotive, beverage, fleet rental, hospitality and pharmaceutical industries that aren't focusing on Web analytics, Kwek said. In fact, he said, they're uploading vast amounts of data from their enterprises, and they're not looking at it as temporary development sandbox for prototyping applications that are ultimately brought into production on premises. That's why end-user accessible BI tools are so important.

"We're building a complementary ecosystem of like-minded companies that are focused on enabling self-service and empowering line-of-business users to get more out of big data," Kwek said.

Thus far that ecosystem also includes BI partners Bime, Jaspersoft and QlikTech, but Tableau is the standout among these vendors where data visualization is concerned. And that's a form of self-service that lots of BI vendors are now trying to bolster in order to democratize data analysis.



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.