Talent creates data gravity. The ability to innovate depends on talented people accessing and collaborating on the same data. Analysts talk about data analytics as if its the coming of the new industrial revolution.
The highest kudos in my career? I once had a CEO of a publicly-traded company thank me for bringing the organization out of the stone ages. What exactly did I do to receive such high praise? The company was a collection of engineering subsidiaries. On paper, the products complimented each other. However, the business units couldn’t leverage the synergies because of the engineering design in silos.
One engineering group worked out of St. Louis and the other out of Chicago. I implemented an MPLS network enabling distributed collaboration on engineering drawings. The project led to the capability of new product creation.
This experience was early in my IT architecture career. It was the first experience where I learned IT could truly power the business. The base capability of enabling collaboration over distance is one of the fundamental drivers for providing value. Talent is the one thing heavier than data. Consolidating the engineering staff to a single location wasn’t a possibility. Moving the data was a lighter shift.
At Cloud Field Day 6, I heard from a company focused on reducing the mass of talent – Hammerspace.
Importance of Meta Data
The Holy Grail of data collaboration is the ability to provide data instantly to anyone needing that data. You can’t beat the speed of light. But a critical challenge in collaboration around information is understanding what data you have and where that data exists. We’ve written extensively about the topic when discussing data protection and data management companies. We did a recent video with Commvault talking about some of the use cases and the capabilities of their Activate product in regards to metadata.
Over the years, I’ve had a bias toward solutions that virtualized data. Many of the business challenges I’ve faced deals with the inability to share data across a vast geographic region efficiently. The example above is a case in point. The solution was relatively simple. I installed what at the time was high-bandwidth WAN technology and enabled SMB sharing over that connection. However, the pace of data growth over the period has accelerated.
Fast forward to my last big data challenge a few years ago. I worked for a global pharmaceutical with research facilities spread across the world and partnerships with industry-leading public research institutions. It’s not difficult to imagine the amount of data that needed to be shared across the organization, let alone considering the challenges with collaborating with outside researchers. Research by MIT Sloan shows that digitally mature organizations are more likely to have partnerships with external partners.
A potential solution to the problem of sharing data across broad geographic regions is data virtualization via a global namespace. One of the central challenges I’ve encountered in solving the problem of collaboration is identifying the location of data needed to be accessed. How does a data scientist identify a data set closest to their compute? Add to that the desire to collaborate with an external partner.
This elemental challenge is where solutions such as Hammerspace come into play. Hammerspace ingests all of your unstructured data. You can organize it in a single namespace and then present it via standard protocols such as SMB and NFS.
A scientist working against DNA scans in Oregon is working on the same set of data that a clinical researcher is using in Chicago. Hammerspace doesn’t magically reduce the access time to that data. That trick is left to a product from Lucidlink, another Cloud Field Day 6 presenter.
Solutions such as Hammerspace highlight the importance of closing the gap of geographically dispersed talents. There are other non-technology challenges, such as cultural and data sovereignty. Data insights are a great value add to your existing capability. Don’t forget the ability for talented people to identify and access data that exists in your organization.