3 Tech Trends to Watch in 2016
In 2016, these trends are all about taking visual BI and analytics to the next level.
- By David Stodder
- January 5, 2016
Business users are more excited than ever about modern visual analytics and business intelligence (BI) technologies. By implementing them, they hope to move beyond their years of frustration with spreadsheets and canned enterprise BI reporting, technologies that were themselves once great advances over calculators, adding machines, and pencils with good erasers.
The turn toward visual analytics and data discovery tools and applications is making it easier for nontechnical users to analyze larger volumes of data more frequently as part of their daily activities rather than in the form of occasional and special requests to IT developers and business analysts.
Yet, while adoption of visual analytics tools and applications has been having a dramatic impact, the technology industry as well as user organizations still have further to go before they can truly realize the potential of democratized visual analytics. Some of the factors most affecting the course of advancement are not about the technology itself.
First, organizations should not make the mistake of neglecting user training because these are "self-service" technologies. Users still need training, not only to learn how to get the most out of the tools and applications but also to learn how to work effectively with data and visualizations. Many users lack experience in analyzing data, evaluating the validity of data sources or analysis, or exploring for unknown trends or patterns and understanding their significance. With the number of visualization options expanding, users need guidance in choosing the best ones for their analysis and for sharing insights with others.
Second, organizations must consider what types of activities will dominate users' implementation of the tools or applications.
-- If they are using dashboards or other visualizations to simply provide a better experience with standard BI reporting, then their emphasis should be on consistent presentation and ease in identifying changes in the data, particularly over time.
-- If the context is operational monitoring and alerting, then the visual interface must make it easy for users to spot the relative importance of issues so they can analyze root causes and quickly determine the best actions. Near-real-time data updates or stream analysis may be needed.
-- If users are performing visual discovery and analysis, they need room for experimentation with a variety of data sources; they need to be able to iterate and do test-and-learn inquiries and employ visual functionality for filtering, comparing, and correlating data.
Tech Trends to Watch
As we head into 2016, BI and visual analytics technologies will continue to evolve toward meeting the needs of the democracy of primarily nontechnical users who want to integrate analytics into their daily decisions and actions. Vendors are competing to make it easier and more fulfilling to use their tools and applications. Here are three trends to watch:
Tech Trend #1: Technologies will aim for intuitive user experiences
In the words of Daniel Kahneman, Princeton University psychology professor and author of "Thinking, Fast and Slow," intuitions are "thoughts and preferences that come to mind quickly and without much reflection." Intuitive interfaces apply algorithms to learn and adjust to user's needs and patterns behind the scenes so that "speed of thought" is uninterrupted; users should not have to stop and futz with the technology before moving forward. Such interfaces could enable users to experience a kind of informed intuition. Vendors are engaging in considerable research and development in this area; it will be interesting to see what advances they deliver in the coming year.
Tech Trend #2: Interactive access to Hadoop data will mature
To support analytics processes, users, developers, and data scientists need tools and data processing platforms that enable better interactive querying of the voluminous and varied data in Hadoop files.
Previously, the options for interactive querying were limited and slow. Now, both front-end BI and analytics tools and applications and back-end data processing platforms are advancing to enable multiple styles of interaction. These include better batch processing and execution to support Hive-MapReduce jobs, SQL-on-Hadoop technologies for interacting with Hadoop data directly rather than through a middle-tier database, and the emergence of Apache Spark as an alternative, and faster platform and framework. Open source projects continue to generate new technologies, so given the level of demand, we can expect more innovation in this space in 2016.
Tech Trend #3: Embedded BI and analytics will be a major focus
TDWI Research finds that most organizations view it as an important part of their technology strategy to be able to embed dashboards, reports, visualizations, and more within other kinds of applications, portals, and business process management systems. This is particularly valuable in operational contexts where users may not have separate BI and analytics tools and in any case it is more efficient for them to interact with data without switching from one application or interface to another. Organizations should evaluate technologies for how well they achieve more seamless and integrated experiences for users, including through embedding BI and analytics.
Pushing Past Today's Boundaries
These technology developments plus attention to training issues will help organizations take their visual BI and analytics tool and application deployments to the next level. They will help users, developers, and data scientists have more productive experiences with more kinds of data. They will also make for an exciting New Year in BI and analytics.
About the Author
David Stodder is director of TDWI Research for business intelligence. He focuses on providing research-based insight and best practices for organizations implementing BI, analytics, performance management, data discovery, data visualization, and related technologies and methods. He is the author of TDWI Best Practices Reports on mobile BI and customer analytics in the age of social media, as well as TDWI Checklist Reports on data discovery and information management. He has chaired TDWI conferences on BI agility and big data analytics. Stodder has provided thought leadership on BI, information management, and IT management for over two decades. He has served as vice president and research director with Ventana Research, and he was the founding chief editor of Intelligent Enterprise, where he served as editorial director for nine years.