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DataOps, “Agile Growability,” and a Humble Dose of Humanity: 11 Things I Want to Hear at Strata + Hadoop World San Jose

See you at Strata + Hadoop World San Jose.Strata + Hadoop World San Jose is coming, and—trade show junkie that I am—I’m once again filled with anticipation. I look forward to new and exciting technologies on display, plenty of marketing hype, and of course, brightly-colored logo pens (especially the ones that double as flashlights or USB sticks). In addition to the sweet swag, here’s what I hope to see and hear in California…

Acknowledgement from data-technology vendors of the growing influence of business end users in purchase decisions. It’s no longer just about the IT leader! Selling technology for technology’s sake is not enough any more, and vendors who ignore business leadership audiences in their messaging do so at their own peril. I want to hear how cool new technologies will help not just IT leadership, but business users as well.

Context! I’m a Strata-holic. I want see all the new features of all the new functional solutions. But I want to see those solutions demo’ed in the context of broader business and DataOps workflows.

Business value! Imagine, if you will, a solution message that starts with business value and works its way backwards…like say, a technology positioned as the business case for a DataOps approach. The new data-technology sale is less about the how and more about the why: delivering tangible, measurable enterprise business value. Why aren’t we all getting that yet? (Hat-tip to the GoodData social-media folks for this much better way of putting it.)

Speaking of business value, I’m eager to hear a compelling “cloud + data = goodness” message from Microsoft. I like where Microsoft is going with its Cortana Intelligence Suite, Azure Data Factory, and Power BI. (Full disclosure: I used to work there.) But I want more. Excluding a certain online bookseller located on the opposite side of Lake Washington, Microsoft is the only major enterprise data management solution provider that owns the cloud, so to speak. In this instance, at least from Microsoft’s selling perspective, cloud is more than a commoditized, off-premise storage option—It’s a strategic advantage…I think. And I want to hear about how that’s a potential advantage for me, expressed (empathetically!) in data-analytics value terms.

And speaking of coherent cloud messages, I’m still waiting for a good solution to the data-consumption bottleneck. How can data consumers digest data (think streaming) as fast as the architecture can scale to store it? (The answer is not hiring more interns to monitor reporting dashboards.) Toph-the-marketing-boy should be able to avoid missing stuff, test new data applications easily, and work with exponentially greater datasets than he currently can. (Sisense paid darn good lip service to this challenge last fall, and I’m looking forward to an update.)

And speaking of that already-here-no-longer-looming data-consumption bottleneck as an example, I’m particularly interested in companies with data technologies that work “here” applied to what’s going on over “there.” For instance, Anodot takes its anomaly-detection technology beyond the ops world and uses it to attack the data-consumption-as-data-volume-grows-exponentially challenge. And Rocana performance-monitoring software doubles nicely as an accountability and visibility solution for senior (read: non-technical) management.

Orchestration across the silos! Point solutions are good. Functional solutions are good. But when they don’t support cross-function and cross-organizational-silo transparency, their success is limited. Platform-level data orchestration is the next big thing, and not everyone is addressing it yet. Teradata’s “Unified Data Architecture” messaging is a good start. (Teradata marketing folks, please save me a logo pen.) So is Domo’s anti-silo evangelism.

The next layer of trust in data: data solutions that are smart enough to provide on-the-fly extensibility. Call it “agile growability,” call it “smart integration,” but what it really is is a data-management model that grows dynamically as it learns from its own operation. (Continuous improvement? Oh yeah. V2.0.)  A good DataOps workflow provides the best data journey at that moment. A great DataOps workflow is smart enough to improve itself over time. A business user should be able to not just trust in the data now, but trust that the next dataset will be even better. Who’s headed this way?

Actian, I’ve had a change of heart. Please…bring back the dancers.

Democratization that’s meaningful. TIBCO, I’m looking your way—Tell me more about “self-service integration for all” (and why it’s better than the alternatives). And DataRobot—Your advanced analytics are stellar, but what’s the true business impact of my becoming a “citizen data scientist?”

Finally, a human request: Our industry has been built upon—and thrives because of—the contributions of immigrants. I speak as one (to Canada) when I ask: How can we support our tech workers impacted by possible U.S. immigration restrictions? Some initial options for Big Data companies: sign amicus briefs, petition for more H1-B visas, and hug your employees. And if it comes to it, consider opening satellite development offices in other countries. (Canadian technology firms may not wait for you.)

 

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