Getting value out of data faster at Google


If I were to put this in a nutshell, the right tool sets from Tableau and Google Cloud Platform helped our customers prospect realize value faster out of big data—and actually realize the value.

Tableau: Why do businesses seek out Google BigQuery?
Brad Kilshaw, Cloud Platform Partner Manager, Google: So as we all know, there's a tectonic shift to the cloud. Many businesses are trying to move away from complex, on-premise, data warehouse solutions that are difficult to manage.

We're seeing more and more enterprise customers embracing Google BigQuery. We see Tableau being one of the partners that will allow us to go and engage inside of enterprises. It will allow us to visualize data alongside BigQuery, and move into a business sometimes as a tactical way, initially, to move in, and then we can expand our footprint.

Tableau: How does Tableau help you help your clients?
Vish Agashe, Global Product Lead for Big Data Technologies, Google: I can quantify the impact in terms of people putting more data into Google Cloud Platform, BigQuery. The reason they put more data is because they're able to get value out of that data using tools from Tableau. I see that more and more install base in terms of more data scientists, more analysts, kind of querying data out of Google Cloud Platform using Tableau.

So if I were to put this in a nutshell, the right tool sets from Tableau, Google Cloud Platform helped our customer prospects realize value faster out of big data and actually realize the value.

Tableau: What do clients get out of this partnership?
Brad: I'd say the value for customers is really around reducing costs with joint solutions. And we believe that with Tableau and BigQuery, we can reduce costs for customers, we can increase their pace of analyzing data, and we can allow their business to scale quickly and easily. We can only do that with partners that add value to us. I see that as one key area.

Vish: Customers are really happy because they can get up and running really fast with this integration. Given what Tableau 8.2 has done in terms of integration with BigQuery. It's pretty seamless. Single point and click, and they can start analyzing massive data sets.

Tableau: So the partnership works well?
Brad: We're looking for innovative, agile partners with solutions that are easy to use that integrate with Google. And, absolutely, we see that partnership with Tableau delivering on all of those fronts. It's a perfect complement, it's a perfect partnership for Tableau to visualize this phenomenal infrastructure that Google sits on with BigQuery. A perfect partnership that we work in synergy.

Tableau: What kind of customer feedback do you get?
Vish: I have personally spent a lot of time in the BI industry and Tableau is doing some unique things. We hear constantly from customers that they're able to get up and running with Tableau and BigQuery within a matter of hours, and that's a big testimony to what Tableau does well.

It is about using data to generate insights. Using data to drive your decision making rather than the other way around.

Tableau: What’s collaboration been like with Tableau?
Vish: The experience with Tableau has been fantastic. Every time we come to event, we are treated as a family. Experience with how fast some of the feature requests are -- some of the kind of fixing of the bugs has been amazing. How fast we have been able to get interactions with senior folks in product management and development to issues we report has been amazing.

Brad: So for us to go into new business and engage with prospects, they're our number-one visualization partner. And also they allow us to engage with other technology partners as well such as DataSift, where we can take social feeds, ingest it into BigQuery, and allow people to go visualize social aspects about their marketplace and themselves.

Tableau: Has Tableau been up the technology challenges?
Vish: Yes. If you consider BigQuery supports SQL interface RESTful APIs. And Tableau engineering team took advantage of that and integrated using our native APIs in 8.2

You know, it was relatively straightforward. Both engineering teams worked together. We already had the APIs out there. So it was relatively easy from the perspective of bringing those architectures together and integrating.