June 29, 2017 - Dale Kim | Big Data Ecosystem

The Urgence for Convergence

In case you missed the recent Convergence conference in Cincinnati in which Arcadia Data was a sponsor and presenter, I want to give a quick recap of the key topics that were covered. As you’d expect from the name of the event, convergence was a key theme. How does that theme relate to data-driven initiatives and digital transformation? Ultimately, it’s about being able to do more by simplifying the hard parts. Data architectures today are getting extremely complex, and big data challenges are only made harder when you try applying your traditional best practices. For example, standing up new applications as separate silos is becoming impractical on big data. Silo sprawl in traditional environments was a big enough problem, but organizations could get value despite the complexity. With big data, the problem becomes exponentially worse because of the much larger volumes of data you need to track. The overhead of managing separate silos tends to outweigh the benefits of these practices. You end up dealing with much more duplicated data that forces redundant security models, ongoing data movement, and significant data quality/consistency problems.

The day was kicked off with a presentation by Andy Goade, who leads the Midwest solutions engineering team at MapR. In his talk, he specifically called out “data convergence” as one of the keys to digital transformation. He explained that you shouldn’t have to create separate clusters for historical data and immediate data, especially in the context of analytical versus operational data. By having all your data in the same location, you get real-time access to data with no unnecessary copying and movement, leading to simpler data governance and lower total cost of ownership. Along the way, Andy provided customer examples that demonstrate data convergence in action. He also talked about the types of agility that drive digital transformation: data agility, application agility, and infrastructure agility. Agility leads to advantages such as self-service data exploration, real-time data access, and global reach across the cloud.

Many of the topics covered in Andy’s talk are exactly why we’re excited about our partnership with MapR Technologies. The benefits of our product, Arcadia Enterprise, are nicely aligned with the technology advantages of the MapR Converged Data Platform. Arcadia Enterprise is also designed to avoid data silos, as it supports an in-cluster analytics architecture that obviates the need to create summarized extracts and data marts that is common in a traditional BI environment. This architectural simplicity leads to real-time access to data, and lets you drill down to granular details without specialized applications and without IT intervention.

The next talk was by Kevin Whitfield of Management Science Associates (MSA). Kevin detailed their technology solution that solves business challenges around providing customers with all the market intelligence they need to make better product sales and marketing decisions. Not surprisingly, a lot of popular themes were important goals in their solution design, including fast access to granular details, scalability, flexibility, and cost-effectiveness. While MSA is not currently an Arcadia Data customer, it was great validation to hear their main objectives were consistent with our technology objectives. I was particularly happy that in his talk, Kevin reinforced the fact that security is not something you tack on later; that it’s something you consider as part of the architectural design, a recommendation (and maybe even an insistence) I’ve often discussed.

Batting third was our own Robb Horton, our local solutions architect. Robb talked a little about the rise of the “citizen data scientists,” an emerging term that describes power users who typically dig into data more than business analysts, but don’t necessarily develop machine learning models like data scientists. Although Arcadia Enterprise is valuable for all types of analytics users, we see the citizen data scientists as a key audience for us because they have been mostly underserved in the past. Robb also talked about the trend around operationalizing analytical dashboards into applications that can be used for daily business activities. Robb then went into an interesting discussion on how you can segregate four main approaches to BI based on two dimensions: scalability and agility. Arcadia Enterprise was architected with both dimensions in mind, which one can say is equivalent to architecting a system for big data. Since MapR was also architected for big data, Arcadia Data and MapR are a great product combination for today’s data-driven initiatives.

The rest of the conference had interesting talks from MapR customer Kabbage, Microsoft, and a couple of subject matter experts from MapR. Cloud and streaming were leading topics among those talks, which are certainly important to Arcadia Data as well. You can expect to hear more from us on that in the future.

We look forward to more joint activities with MapR Technologies, particularly when it comes to enabling business success for joint customers. With our alignment around data architecture simplicity, reduced/eliminated data movement, scalability, real-time data access, etc., we believe we have a great story for any data-driven company’s needs around data management and analytics. Check out our video of Arcadia Enterprise on MapR and be sure to tell all your friends about it!


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