BI Technology

5 BI and Analytics Predictions for 2019

The analytics and business intelligence market is set to undergo unprecedented change in 2019. Driven by new technologies like AI and machine learning, along with advances across the cloud ecosystem, data leaders face tremendous transformation - and opportunity.

Here are five predictions for what the analytics ecosystem holds for 2019.

1. Self-service BI for the masses becomes a reality

Self-service BI has been a mirage for decades. The so-called “modern BI” tools claimed to be self-service, but self-service for who? Not the vast majority of business users. True self-service for all business people, technical and non-technical, will finally be possible through the emergence of a new category of search-driven BI tools. These tools use search, which everyone knows from their personal lives, as the primary interface for users to get insights of their data. Just as Google changed the internet with search, as more users get exposed to this new paradigm, there is no going back. Search-driven BI is here to stay. In 2019, the mirage of self-service BI for everyone finally becomes an oasis of insights.



2. Data conversations and stories become popular ways of consuming analytic insights

Search allows for interactive analytics at the speed of thought. Instead of static insights, users can ask questions of their data and instantly get answers. This answer sparks off another question, whose answer incites yet another question. Often times the questions build on each other - a follow up question inherits the context of the previous questions. This is typical of how the human mind processes information. The user is engaging in a conversation thread with her data. In 2019, this will become the norm for analytics, where systems maintain and utilize context throughout the conversation. This type of conversational search, especially when coupled with a voice interface, promises an easy and natural way for any user to gain data insights.

While gaining insights is critical, presenting those insights to others is equally important in organizations. Just as the human brain learns through conversations, it also learns through a story. In 2019, the most powerful analytics will move beyond a simple chart or table. Instead, a collection of insights are woven together into a story. Storytelling is a powerful means of communicating insights. Stories bring to life data in visualizations through textual commentary, images, annotations of data points, event marker overlays on charts, natural language explanations of data, animation and slides.

3. Emerging Mobile BI solutions boost adoption

If adoption of BI in enterprises is low today, the adoption of mobile BI is abysmally low. Mobile BI adoption has failed primarily because vendors have attempted to stuff their desktop versions into a mobile offering. This is not what users really want. The sweet spot emerging for mobile is voice-driven, natural language search-based interfaces that empowers users to get insights when and where they need them. They are not looking to browse catalogs, author content, or perform complex interactions, all of which are cumbersome. Voice capabilities lend themselves very well to serving the needs of mobile users, and will drive significant adoption of mobile BI for the first time in the history of the field.

4. AI in BI goes mainstream

AI is making a mark in enterprise software. In BI and analytics, AI has ushered in the era of augmented analytics - augmenting the insights users generate manually - with system-generated insights. The system-generated insights are valuable for two reasons - not only does this make it possible for users to automatically run through thousands of questions they’d never be able to manually execute, it also helps users who may not know what questions to ask of their data avoid missing key insights.

Such systems require two elements for being effective:

  1. Large amounts of training data used in finding relevant, personalized insights, including input such as the searches users conduct and the feedback they provide to the answers generated.
  2. A very powerful data and compute engine that can automatically maintain snapshots of data and can process thousands of queries extremely fast.

We envision the emergence of self-driving analytics - the combination of system-generated insights on questions users may have never thought of, and automated, personalized insights pushed to users through email and mobile.



5. Hybrid-cloud and multi-cloud deployments become the norm

Enterprise data infrastructures are at an inflection point with major shifts toward the Cloud. The traditional concerns about sensitive, high-value data warehouse data moving to the Cloud has changed, as enterprises become increasingly comfortable with security of cloud platforms. Once security concerns are addressed, cost becomes the next most important factor. Cloud data platforms are providing significant overall reduction in total cost of ownership (TCO). Transactional systems, which are a major source of data for data warehouses and data lakes, have already been moving to the Cloud at a much faster pace, reducing the issue of moving large data volumes from on-premise to the Cloud.

For large enterprises, the movement to the Cloud will be gradual, spanning many years. Many enterprises will operate in a hybrid mode, spreading their data assets between on-premise and the Cloud. In addition, more enterprises will adopt two-vendor cloud strategies for risk reduction and price negotiation leverage. As a result, we will likely also see data assets of enterprises spread between different cloud platforms.



In 2019, we will see BI and analytic systems that can operate seamlessly in these multi-cloud environments. These systems will offer multi-cloud analytics, a single pane of glass view into all the data assets of the enterprise. To the end user, the system will seem like one single system. The usage of the system by end users will be totally unaffected by any changes to the underlying on-premise and/or cloud platforms or data movement across them.

There’s lots more coming for the analytics market in 2019. Check out part two of our predictions for 5 more things you can’t afford to miss in the coming year!