Over the last decade, we’ve seen an explosion of SaaS applications. Salesforce, HubSpot, MailChimp, Box, NetSuite, Zendesk, AdWords, New Relic, Dropbox, Facebook Ads and so many more. (Those were literally just the first 10 that came to mind.)
And all of those apps produce data. Data that’s critical to running your business.
While many of those apps include some basic reporting, you need to combine data from all your apps in one place to derive real business value from it. That’s the only way to get a global view of what’s happening and why it happened.
Naturally, lots of customers come looking for an analytics tool that can plug into all their SaaS apps, suck the data out, centralize it, magically make sense of it, and let them find insights.
I’m going to be straight with you: Looker is not that tool.
Other tools won’t say that. They’ll say, “Yes! That’s us!”
I know, because that tool doesn’t exist. And I’d strongly advise caution before buying what they’re selling.
The first reason you should be wary of anyone promising that magical solution is that keeping up to date with dozens of other vendors’ API specs and customers’ unique needs is hard.
When you buy connectors that are bundled with an analytics tool, you can bet that vendor is spending thousands of engineer-hours building and maintaining their connectors. And those are hours they’re not spending making their core analytics product better.
Buying connectors from your analytics vendor is kind of like buying a TV/DVD combo. You get a mediocre TV and a mediocre DVD player. But the real issue arises when you’re ready to upgrade to a better TV or to replace your DVD player with Blu-Ray. The purchase that started as a time and money saver is now far more complicated and expensive.
The second reason to be cautious is that built-in connectors work one of two ways: either they give you a black box or they give you a data dump.
Black boxes are initially appealing, because they look simple from the outside. But that’s only because they’ve hidden the gnarly stuff inside, where you can’t see or understand it. Analytics you don’t understand are analytics that can lead to mistaken decisions.
You don’t know what’s happening in those black boxes, so it’s hard (or impossible) to understand which definition of retention rate or open rate or any of the hundreds of other business-critical definitions are being used.
Because you can’t see inside the black box, you also can’t customize it to your business’s particular needs. So costs skyrocket as you’re forced to pay extra for every bit of customization.
The other path tools take is to offer a data dump instead of a black box. However, without guidance as to what the data actually means, a data dump doesn’t provide much value either. Without a model for what the data means, you have to have create that logic from your own knowledge. And while that might seem reasonable, wait until you see what these data dumps look like.
For example, here’s a “basic” entity-relationship diagram for Salesforce’s data tables (and this is just the sales objects):
It’s not simple. It’s not easy to understand. And building out those relationships in your analytic tool is difficult, time-consuming, and error-prone.
At Looker, we chose to focus on building a phenomenal data exploration platform. And spending time on connectors would impede our progress toward that goal. But that doesn’t mean we leave you to fend for yourself when it comes to centralizing your data.
Instead of building connectors ourselves, we’ve cultivated an extraordinary group of partners whose sole focus is moving data seamlessly out of your SaaS apps into whichever data warehouse you choose. Partners like Fivetran, Stitch, and Segment do an amazing job centralizing your raw data from apps like Salesforce, Zendesk, and dozens more. Additionally, by getting your data out of these SaaS apps and into a centralized environment, you have created a store of all the data that drives your business that you truly own.
And then Looker takes over with our Looker Blocks, plug-and-play code modules that make sense of the data for you, so you can start exploring it immediately. Looker Blocks are just LookML (Looker’s flexible SQL modeling language), so you can see exactly how the data is structured and customize it however you need.
It’s not a black box and it’s not a data dump. It’s convenient and transparent, and it’s all done without distracting Looker’s engineers from building amazing features for our customers.
What’s more, this is the only approach that is future-proof. We’re already seeing the ecosystem evolve with tools like Google’s new BigQuery Data Transfer Service, where Google pushes YouTube, DoubleClick, AdWord, and Google Analytics data directly into your BigQuery instance. As the cost of keeping up with an ever-growing set of APIs grows, we expect more SaaS vendors will offer the option to have your data delivered to wherever you need it.
Moving data yourself is expensive and slow. Subscribing to a data stream or having the vendor deliver it to cloud storage is getting easier everyday. As more vendors move to this new model, do you really want to be stuck with an analytic tool that you chose for an obsolete feature? Or do you want something that will work with whatever your future stack looks like?
Choose the pipeline that makes sense for you now (we’re happy to help you choose); pipe the data into the database that fits your current needs (we’re happy to help there, too); and put the best data exploration platform on top (happy to help you choose, but I think you know what the answer is going to be 😀)