Enterprise Data and Analytics Market Outlook for 2016

B. Shimmin
B. Shimmin

Summary Bullets:

• The enterprise data and analytics marketplace has been struggling to hold onto traditional philosophies of control, governance, and discipline, while simultaneously looking way ahead to a future that’s free from such constraints.

• How will that play out over the coming year? We think IoT will emerge as a service, data preparation will permeate data discovery tools, and data itself will form a new marketplace.

The end of each year always seems to race toward us, the closer we get the faster it approaches. Within the U.S. perhaps that’s because we always have a stack of our major holidays in the last month and a half of the year. Perhaps it’s just that the new year, like any good waypoint on a journey, forces us to take stock of where we’ve been and contemplate what lies beyond that arbitrary horizon. And suddenly we’re living two lives at once, which can feel pretty crowded and frenetic.

In a similar manner the enterprise data and analytics marketplace has been living two lives. It has been struggling to hold onto traditional philosophies of control, governance, and discipline, while simultaneously looking way ahead to a future that’s free from such constraints where more data from more sources flows with more rapidity to more people in more meaningful ways. That has created some considerable momentum (and associated chaos) within the market. Here are five such high level transformations we’re looking forward to in the coming year:

  1. IoT Becomes IoTaaS. While IoT will still struggle at the outer, hardware-centric edge with incompatibility and performance/security concerns, enterprise buyers will see some relief and opportunity as technology providers such as Google, SAP, Microsoft, Oracle, IBM, and Cisco begin hosting IoT platform services. Platforms such as Microsoft’s Azure IoT Suite will evolve to help solve some of the serious issues surrounding data capture and integration, bubbling up into the resulting soup into existing analytics software.
  2. Data Democratization Collides with Data Preparation. Lightweight discovery and visualization vendors like Tableau, Qlik, Birst, and Zendesk (BIME), will gain a competitive advantage through the adoption of data preparation capabilities that promise to return some controls to IT and provide business users with some confidence in the data selected.
  3. Business Intelligence 2.0. This Time It’s Personal. Now that the major BI vendors have “mostly” moved their software to the cloud, enterprise buyers can look forward to both improved licensing flexibility (between premises and cloud) and widening options in terms of choosing where data lives and how users access that data. More importantly, cloud-borne BI solutions, will more readily integrate with their data discovery and visualization counterparts, as with IBM Cognos Analytics and Watson Analytics.
  4. Data Subscriptions Drive New Ecosystems. Traditional technology providers with a strong ecosystem and cloud platform will begin delivering data itself as a service, beginning with carefully curated data sets and expanding to include data published (and sold) by third parties. Already we’re seeing the beginnings of this with IBM’s acquisition of The Weather Company’s content and Qlik’s acquisition of DataMarket. More will follow.
  5. Everyone Gets Predictive. Advanced analytics functionality such as data mining, forecasting, statistical analysis, simulation, etc. are at last leaving the ivory tower. Though not fully self-service as yet, many solutions, like Expert Storybooks feature within IBM’s Watson Analytics and Microsoft’s Cortana Analytics can literally walk business users through the task of identifying patterns and predicting business or operational outcomes.

What do you think?

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