TDWI Takeaways and Emerging Trends
In February, I attended TDWI in Las Vegas to speak at its Leadership Summit. The summit combined technical and business-oriented sessions that highlighted trends in data and analytics and the way in which technology supports broader business value. The attendees were a mix of technology and business decision-makers and practitioners. The event allowed decision-makers to gain insights into technology adoption without focusing on only technical tracks.
My talk discussed actionable intelligence and the ability to tie business intelligence (BI) to action and discernable business value. To gain value from data, simply monitoring performance or creating dashboards does not cut it. Organizations need to understand what they want to achieve and what data insight means in order to gain quantifiable value.
In addition to my session, I listened to a panel highlighting industry trends and spoke to several analysts and consultants to get a broader view of the emerging trends in the market. Although IoT, Blockchain, and easier access to data were popular topics, the concepts surrounding self-service access and AI really resonated with me based on what I have been seeing in the industry.
The Future of Self-Service
The way self-service has existed until now is dead. There has always been a goal of providing people with dashboards and interactive reporting tools that they can leverage irrespective of comfort with technology. The reality is that self-service still requires technical preparation, developed algorithms that can be applied in business scenarios, and ensured data integrity of some level. Even if data is delivered in a specific way, the ability to slice and dice data also means that information can be construed in a way that serves specific needs and may not always be accurate. This is because information can be interpreted in different ways by different groups of people. Without collaboration across the organization, and an understanding of what data assets mean, it becomes difficult to deploy self-service access and expect all types of employees to have the same skill set or level of understanding. Consequently, although self-service access is important, today’s self-service does not provide the intuitive understanding or interactivity that we are used to in our private lives through the apps we use on a regular basis.
AI and Predictive Analytics
The use of BI and analytics has matured enough in many organizations to the point that companies are looking for answers regarding what will happen next and how to gain insight previously unavailable. For the past few years, big data architectures and data lakes have been the rage as organizations feel that they need to tackle their big data challenges. At the same time, accessing that data and gaining quantifiable value from the information stored remained allusive to many. With predictive analytics and machine learning becoming more widespread, businesses can take advantage of all of the data they stored and that has been analyzed in a historical way for several years. Now companies can begin to develop scenario-based predictive models and leverage machine learning to gain insight that will drive business further.
Overall Industry Insight
Today, there is a convergence of business information and data access that has never been seen. The desire for real-time access to information is becoming a reality that supports quantifiable benefits of leveraging business intelligence and analytics. At the same time, organizations demand easily consumable dashboards, reports, and applications. Doing so with consistent data quality and integrity remains a challenge for many. However, based on the increasing importance data plays within organizations, creating intuitive and accurate information access is becoming more of a reality.
As businesses take advantage of what the market has to offer, the concept of self-service will no longer apply. Eventually applications will be intuitive without being a market trend, in the same way that BI will be consumed more holistically by leveraging technologies to address business challenges and opportunities instead of market hype.