Posts in Google Cloud Platform
Supermetrics, Google BigQuery and Data Pipelines for Digital Marketers

Chances are that around the corner from the analytics project you’re working on that’s using SaaS data piped-into your data warehouse using a service from Stitch or FIvetran, there’s a marketing analyst using Google Sheets and an add-in from Supermetrics to analyze their channel advertising spend.

Supermetrics are the biggest analytics tool vendor company you’ve never heard, and that’s because their products are aimed squarely at marketers, not data engineers or data analysts, and within that particular market they’re massive; what they sell is easy-to-setup connectivity to all the major advertising and social networks directly from within Google Sheets in the form of the Supermetrics Google Sheets Add-In, a product we’ve used in the past when looking to to understand how well we place in Google search results for keywords relevant to our business.

googlesheets.png

Supermetrics do two things well; they provide connectivity to all the major ad networks that marketers’ use (and there’s lots of them beyond the basic Adwords, Facebook Ads and Snapchat Ads that we’re most familiar with), and they focus exclusively on the non-technical, marketing user rather than data engineers and data analysts, providing in-addition to their Google Sheets add-in a connector for Google Data Studio, for example.

But although you can use Google Sheets as federated sources for Google BigQuery tables and theoretically you could then use the scheduled data refresh feature in Supermetrics’ add-in to regularly download new data and thereby create a sort-of data pipeline into your warehouse, in-practice this probably requires a bit more knowledge of how BigQuery works than the average marketer is likely to have.

So I was particularly interested to see that one of the new BigQuery features announced at Google Cloud Next’19 last week was a number of Supermetrics-provided data connectors for BigQuery in the Google Cloud Marketplace, providing data pipeline-as-a-service connectivity from ad network sources such as Bing Ads, LinkedIn ads, AdRoll and others and with data being fed directly into Google BigQuery using their Data Transfer service.

supermetricspage.png

Some of these sources are also covered by new connectors from Fivetran also in this same Google Cloud Marketplace, so what’s the difference between a data pipeline provided by Supermetrics compared to one from Fivetran or Stitch? Setting up a Supermetrics data pipeline using Google BigQuery’s data transfer service is pretty straightforward and not that different from setting up a data pipeline using Fivetran or Google’s own underlying data transfer technology, as shown in the screenshots below:

steps.png

Its when you look at how Supermetrics land data into BigQuery though that you see their difference in approach; instead of presenting you with several tables of data mapped to the structure of the API calls for each service, the Supermetrics BigQuery tables are typically denormalized (flattened into one big table of data) and come with extensive and verbose column descriptions and metadata, making it much easier for marketers to know what each column is used for and the precise definition of all the metrics and dimension attributes.

metadata.png

Pricing is per data source with a 14-day free trial at the start, to me it looks like Supermetrics are looking to position their pipeline-as-a-service in-between Stitch and Fivetran’s in-terms of pricing but with the service aimed at marketers, not data engineers. Details of pricing and pricing metrics are on the Supermetrics support page and full details of the service are on the Supermetrics for BigQuery product homepage.

Five Thoughts About Thomas Kurian’s Move to become CEO of Google Cloud Platform

The news broke late on Friday that Thomas Kurian is joining Google to become their new CEO for Google Cloud Platform. Five thoughts on Kurian’s move:

  1. It’s a smart move made by an exceptionally smart guy. Brave, as well, given the recent history between Oracle and Google but also not surprising given his drive and presumably point to prove. I met him a few times as part of Oracle’s ACE Director program and he’s the only software exec I know who can talk long-term strategy and vision one minute and then explain to you in-detail how it all works, and doing it all with great humility and courtesy.

  2. The fact that GCP is spoken-of as an also-ran at 10% market share whilst Oracle Cloud gets bundled in with “Next 10” shows what a mountain Oracle have to climb to even become a contender to compete with Microsoft and Amazon in the cloud business - and their insistence on only allowing their SaaS and PaaS apps to run in Oracle Cloud is a worrying parallel with the “Windows Tax” that Microsoft’s Office and Server products teams had to pay back in the Steve Ballmer Era, but with Oracle’s equivalent to Satya Nadella having lost the argument and jumped-ship

  3. But Oracle will survive and this has happened many times before - Ray Lane, Charles Philips, Tom Seibel, Mark Benioff all left and in many cases founded massively successful and competitive businesses, client-server went to internet architecture and then internet went to cloud, it’s all part of how businesses renew and people move on and up, and there’s plenty more smart (and most likely, smarter) people left in Oracle and Larry Ellison is still just as driven, competitive and on-top of his game.

  4. Look out for a very interesting (as in Brexit, interesting to watch but not to be part of) culture clash at GCP, with TK about the most top-down leader of a product development team I’ve ever seen and Google, famously, engineering-focused beanbag-friendly and bottom-up. Add to that the feelings most Googler’s have towards Oracle and TK will have his work cut-out early on to win the various teams over - my guess is that his work-ethic, technical chops and sheer ability will do just that and if this role is a success, Sergey and Larry may well have found their new Eric Schmidt but this time with technical skills to match theirs - but there’s always the chance that culture will prevail and he’ll be the next Marissa Meyer instead. No pressure there then..

  5. Expect to see GCP moving increasingly into SaaS B2B areas such as ERP, CRM, Financials and industry-vertical applications to complement their commoditised IaaS and PaaS cloud business and leveraging their massive GSuite and increasingly ChromeOS install base. Just think what they could do if they had access to all the world’s structured business transactional data as well as the unstructured search, email and spreadsheet data they have now - even more comprehensive and market-leading search, the world’s biggest and most valuable ML training set, and a business model that could provide these applications for free in exchange for exclusive access to that data and Google being your default search engine. That’s the real existential threat to Oracle; spending all their time trying to win an un-winnable cloud infrastructure war and then GCP coming along and making ERP, CRM and business applications essentially free.