Top Two 2017 Priorities for Data Discovery and Visualization Vendors

B. Shimmin

B. Shimmin

Summary Bullets:

• The data discovery and visualization marketplace showed a tremendous amount of maturation in 2016 with vendors tackling major market opportunities surrounding the cloud, big data integration and collaboration.

• The coming year promises to build on this progress as vendor aim to make data discovery and visualization both widely accessible and fully trustworthy for everyday business users.

The data discovery and visualization marketplace during 2016 showed a tremendous amount of maturation as vendors tackled major market challenges. Vendors inured in on-premises software embraced the cloud as a strategic platform, not merely a loss leader. Solutions that historically operated at arm’s length from big data repositories opened up direct lines of communication with a wide array of data sources. And solutions that were once oriented toward insight dissemination began addressing insight discussion and collaboration, both within and beyond the confines of the boardroom. Read more of this post

Can Qlik Weather the Storm in Transitioning from Premises to Cloud?

B. Shimmin

B. Shimmin

Summary Bullets:

• As with many pure play software vendors reared on the slow but steady revenue stream of on-premises perpetual licensing, Qlik knows it must make the transition to the cloud.

• Now that the firm’s sale to Thoma Bravo is complete, Qlik is using hopeful that its newfound stature as a private company will allow the freedom necessary to endure short term disruptions in favor of long term benefits.

This week I had the pleasure of attending Qlik’s annual analyst meeting, the Qlik UnSummit, held in Miami Florida. Surprisingly, despite having endured a category four hurricane (Hurricane Matthew) just a fortnight earlier, local Miami businesses and beachgoers seemed entirely unchanged and unharmed by the storm (I know; I was there just prior to Matthew’s arrival). That’s the way forces of nature work. They are unpredictable in the extreme. You have to plan for and expect the worst all while hoping for the best, knowing that unseen and unknowable variables will ultimately decide the outcome. Read more of this post

When Building for Big Data, Remember to Think Small

Brad Shimmin

Brad Shimmin

Summary Bullets:

  • With a continued focus on top down, company-wide all-encompassing projects, big data is in danger of turning into the next service oriented architecture (SOA) – a good idea that simply cannot be realized.
  • Conversely, Microsoft’s diminutive self service business intelligence solution, Power BI for Office 365, highlights the potential in thinking small with big data.

I never win anything. For that reason I never gamble and have never, ever entered the Publishers Clearing House sweepstakes. But last week on a whim I requested a beta invitation for Microsoft’s forthcoming self service business intelligence (BI) service (Power BI for Office 365 preview). Lucky me, I won an invite and immediately began pawing through the available documentation and downloading a few samples. What did I find? Sometimes the biggest insights can be found in the smallest of packages, even the seemingly unpretentious spreadsheet itself. Read more of this post

Mobile Analytics Form a Two-Way Street Between the Past and the Future

Brad Shimmin

Brad Shimmin

Summary Bullets:

  • There are great advantages to disseminating analytics smarts to mobile users such as sales persons.
  • Real innovation, however, comes when you combine that dissemination with the collection of data points.

I spent a few hours yesterday listening to a number of SAP ISV partners including ExpertIG, Rapid Consulting and Liquid Analytics demonstrate mobile software built to support the wholesale market.  I know, that doesn’t sound incredibly exciting.  Yet, long before the expiration of my admittedly short attention span, I was struck squarely by what was for me a stunning realization.  Big data should be as much about collecting data as it is about gleaning knowledge from that data. Read more of this post

Big Data and Predictive Analytics Need More People, Not More Data

Brad Shimmin

Brad Shimmin

Summary Bullets:

  • Machine learning, data mining, and advanced analytics coupled with big data seems poised to reshape the way we make business decisions, automating them and making them more effective.
  • However, if our early work with stocks, recruitment and credit scoring are any indications, our algorithmic innovations need human oversight now more than ever.

My Google Nexus tablet knows when I should leave the house in order to keep my daily routine humming along smoothly. Using historical geolocation data, search results and email trafficit knows, for instance, where I like to dine and how long it will take me to get there at the prescribed hour on the customary day of the week. Read more of this post

The Workday Will Be Televised

B. Shimmin

B. Shimmin

Summary Bullets:

  • The fast-approaching conjunction of social analytics, the YouTube generation, and pervasive mobility will radically alter the workplace as employees begin broadcasting the telemetry of the workday.
  • Companies that head down this road must prepare now for the inevitable ethical, legal, and even technical conundrums that will follow such ubiquitous and pervasive exposure.

When I go out for a bike ride, I never go alone.  That is, anyone who has befriended me on MapMyRIDE can follow my progress in real-time, noting some very specific telemetry data generated by my iPhone and the MapMyRIDE app, including my altitude, speed, direction, and exact location.  Later, my friends and I can review a given ride, analyzing my performance (like average speed over distance) or just going along for a virtual fly-along ride.  With bespoke devices, the gobandit GPS-HD, for instance, I could take this to an entirely new level, recording and later broadcasting my daily sojourns using the same telemetry data tied to a high-definition video feed.  Soon, corporate employees will begin broadcasting their daily work routines in much the same way. Read more of this post