In 1951, astronomer Gerard Kuiper predicted there was a giant cloud of ice particles and comets beyond the planet Neptune. The sun’s mass would occasionally drag some of these objects into an orbit, resulting in short-term comets that would melt as they got close to the sun. Kuiper’s theory was not proven until 1992, when a belt of icy objects (now named for him) was discovered between Neptune and Pluto.
The beginning of the new year is a great time for resolutions and predictions. The LRS Analytics and Big Data Team has bold predictions for 2018, and based on the rate of change we see in analytics, it won’t take 40 years to prove them like those of Kuiper.
So, without further ado … our predictions:
1. Data Governance, Security, and Quality Make A Comeback
The lines between traditional silos of data will blur as analytics changes the cost and scale of our economy. Companies will focus less on ownership of data, and more on usefulness and trust of data. Governance of data will move closer to sources as usage and quality measures are automated and taken in real-time. This, in turn, will force enterprises to re-evaluate the way they provide quality data to workers.
2. Analytics Moves Beyond Visualizations And Becomes Conversational
It will no longer be enough to provide easy-to-understand visualizations in analytics. The next wave of workers grew up with the iPhone and apps they can talk to. As analytics permeates all applications and processes, those users will expect the same when it comes to gaining insight from data. Analytics vendors are now including the capability to either type or say a question, and have written summaries of the information presented back to the user. This also speaks to the rapid improvements in platform integration, search, and API integration occurring in technology today.
Figure 1. Example of conversational analytics with self-generated descriptions of content
3. Data Catalogs Will Be The Rage
Ancient Egypt invested heavily in educating scribes who archived their language, which is why we can retrieve and understand it today. Does anyone know anything about the Mesmes language? No, and that’s because there are no more speakers and it was not documented. The victors in the next round of business are not those who can collect the most data, but those who catalog their data so everyone can understand it and make the best decisions with it. Because machine learning, IoT, and predictive applications require trusted information, data literacy for everyone will drive a need to understand all data, in all formats, wherever it exists. Catalogs that provide extended element information and lineage will be as important as the data itself.
4. AI Will Force HR Departments To Think About Managing Machines And People Together
In Deloitte’s 2017 Global Human Capital Report, 41% of respondents said they either fully implemented or made significant progress in adopting cognitive or AI technologies. But only 17% of those companies said they were ready to manage a workforce where people, bots, and AI work side-by-side. This will force a shift in pre-requisite skills needed for most jobs, and a shift in how the performance of augmented workers (people and machines working as a team) is evaluated. These are still challenges analytics can help any organization with.
5. Context Will Be King
All reporting will be redefined to be more contextualized. Analytics vendors will deliver information that is role-based, location-aware, event-driven, and has a temporal sense. This further hones the ability personalize information for the right person at the right time in the right place. Providing this additional context also means that more people can be enabled in analytics than ever before.
The LRS Big Data and Analytics team has over 20 years of experience in analytics, information management, and data warehousing. If you are interested in discussing current trends in analytics and understanding how we can help you find value in your data, please fill out the form below to request a meeting.
About the author
Steve Cavolick is a Senior Solution Architect with LRS IT Solutions. With over 20 years of experience in enterprise business analytics and information management, Steve is 100% focused on helping customers find value in their data to drive better business outcomes. Using technologies from best-of-breed vendors, he has created solutions for the retail, telco, manufacturing, distribution, financial services, gaming, and insurance industries.