Every so often I get an email from an analytics vendor letting me know that they've added new functionality to the platform. We've got great new features – would love to show them to you!. Inevitably, the fantastic new functionality turns out to be something like the ability to change dashboard themes or an additional database connector. These are great things, but fall a little short of groundbreaking.
It would be fair to say that over time, I’ve become a little jaded to these types of vendor announcements.
So, when I received a product announcement email from Periscope Data a few weeks ago, I was prepared to be unimpressed. I assumed that they had added new theming options, could now connect to some obscure database, or had received some fresh new certification.
Boy, was I wrong.
You might recall from my recent “Vendors You Should Know” profile of Periscope Data that they are the “Swiss Army Knife” of analytic platforms. Most analytic systems are designed for one of two audiences: data scientists or general users. The data scientist platforms allow the user to perform complex, highly targeted analyses but often at the expense of usability. These platforms are too complicated for the average user. The analytic applications designed for general users are far more comfortable to use and allow non-data scientists to perform pre-defined analyses and some ad hoc exploration but aren’t well suited to the types of complicated, one-off investigations performed by data professionals. Periscope bridges the divide between these seemingly separate worlds and allows a company to implement a single platform that serves the needs of both data scientists and general users or, in my area of interest, product teams building customer-facing analytics. There’s an obvious cost-saving benefit to having a single platform for all analytics, but there is another less apparent advantage. Using a common platform — such as Periscope Data — for internal analysis and data products reduces the risk of a mismatch. When using multiple platforms, there’s a possibility that the numbers from one system aren’t the same as those from another. Time is wasted trying to run the cause of the discrepancy to ground, and when the issue surfaces in a data product, credibility is lost.
Even still, I wasn’t expecting all that much when the Periscope team highlighted two key new features they’ve recently rolled out: R and Python integration (launched in February) and “visual data discovery” (launching today).
This was an error on my part. Although the new Periscope release contains several exciting and useful new features, these two are true game changers.
Let me explain.
Read the rest of this post on the NextWaveBI blog.