Good question. What is the point? The point is to create measurable business value from enterprise data. Of course, before measurable business value comes insight. The Modern Data Architecture (MDA) recognizes that insight can lie hidden in data of all types—structured or unstructured, messy or modeled, historical or realtime.
The other day I Googled, “the problem with a modern data architecture.” Of course, at Attivio we’re big evangelists for an MDA, but it’s always interesting to see what the contrarians have to say. There were over three million returns, but none on the first two pages said a word about problems. Lots of articles about how to develop an MDA or how to optimize an MDA or why you had to have an MDA. You get the picture.
The scope and scale of today’s enterprise challenges are unprecedented in terms of their complexity. Vast volumes of information are scattered across the ecosystem and around the globe, and enterprises often are expected to dynamically retrieve precisely the right data set on a moment’s notice to win a customer’s loyalty. If not, other vendors eagerly await to win that customer’s lifetime business. Every transaction is a lifetime transaction.
If Aesop is right and we are known by the company we keep, Attivio’s success is a direct result of our associations with our top-notch channel partners. One of our longstanding resellers is Cadeon, an IT services and solutions provider based in Alberta, Canada. We recently checked in with Cadeon CEO Phil Unger about his ongoing work with Attivio.
Attivio: Tell us about your experience as an Attivio reseller.
The search market has come a long way from 2007 when Attivio was founded. We took some time to chat with Attivio co-founder and CTO Will Johnson about just how far Attivio has come and how the search market itself has evolved.
If your organization is going to win on analytics, it needs to view all of its information as a strategic enterprise asset. This includes not just the 10% you know about, but the 90% of dark data that hides in information silos. There are big challenges on the path to surfacing all of your enterprise information for business intelligence. The biggest challenge is not in storing data, or in analyzing it, but actually finding the right data. But why is it so hard? Here are the top three reasons:
It's pretty obvious to anyone who follows analytics and Big Data that an end-to-end solution for the Big Data stack will require best-of-breed technologies from multiple vendors. No single vendor can develop all the technology pieces on its own. New applications and data processing frameworks emerge and change much too quickly. As enterprises strive to create a modern and flexible hybrid data infrastructure, they look for technologies that are easy to embed and extend.