It’s the week that Google holds its NEXT conference. NEXT is the chance for Google to show off its Cloud Platform and, with it, further their ambitions to more evenly compete with the two public cloud vendors of scale, Amazon Web Services, and Microsoft Azure. NEXT marks an interesting development and perhaps the ultimate fulfillment of the promise that Diane Greene, co-founder of VMware and now head of all things cloud at Google brings to the organization. To understand that statement you need to comprehend that Google has historically been known as a very inward-looking organization, wholly secure in its own direction and story and unwilling to engage with pretty much anyone.

The fact that Google is holding a Cloud Platform-specific event and the fact that they’re going against their usual modus operandi and engaging with the media and analyst community to do so is an indication of a real opening up and desire to play by the traditional rules of IT vendors.

Anyway, the analysis of Google’s moves aside, this week will see a huge number of companies announcing Google-related products and services. A case in point comes from Looker who is rolling out an integration with Google’s Cloud BigQuery Machine Learning offering.

For those that haven’t come across it, Looker is an analysis and visualization company that aims to help its customers derive insight from their data. Looker integrated into a host of different products to drive data-driven decision making to its customers. Part of Looker’s value proposition is to tie into various data infrastructure offerings and drive the analysis goodness on top of that infrastructure.

The two sides of the analysis coin

There are two aspects to deriving insights from data – the first is developing the machine-learning algorithms, and tuning them for particular data types, the second part is to then run those algorithms on the data sets to develop the pretty pictures and dashboards that deliver those insights. In the traditional world, these were two distinct processes and the idea of integrations such as this one are to move those two operations close together – in doing so, the aim is to speed up the processes around data science.

With this integration, data teams can save time and eliminate process steps by creating machine learning (ML) models directly in Google BigQuery via Looker – without the need to transfer data into additional ML tools. According to the company, BQML predictive functionality will also be integrated into new or existing Looker Blocks allowing users to surface predictive measures in dashboards and applications.

Lloyd Tabb, Looker’s co-founder explains the value here:

Much of the work in machine learning centers around data preparation and ML model evaluation and tuning. Looker and BQML are great together in that Looker handles the data preparation and BQML does the learning. Looker can also help you evaluate and tune ML models to integrate predictions into dashboards and data workflows.

For their part, Google, via Sudhir Hasbe, Director of Product Management for Google Cloud had this to say:

BigQuery ML brings machine learning closer to where customers are storing large datasets, so they can quickly create and deploy models, at scale. Looker’s integration with BigQuery ML adds powerful capabilities for our joint customers who can now use Looker to run ML models directly in BigQuery and surface the predictive insights across their organizations.”

MyPOV

Google realizes that it cannot be all things to all people and it has to embrace a broader ecosystem to add value (and, ultimately, drive adoption) for its Cloud Platform. Integrations such as this one help it with that ambition. As for Looker, this partnership is a case of it covering the bases of potential customer demand. While in third place, Google Cloud Platform is still an important public cloud player and for Looker to achieve its ambitions it needs to cover all the potential platforms that its prospective customers use. How much this partnership really moves the needle for either party is something that we will only be able to assess in the fullness of time.

Ben Kepes

Ben Kepes is a technology evangelist, an investor, a commentator and a business adviser. Ben covers the convergence of technology, mobile, ubiquity and agility, all enabled by the Cloud. His areas of interest extend to enterprise software, software integration, financial/accounting software, platforms and infrastructure as well as articulating technology simply for everyday users.

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