Top five business analytics intelligence trends for 2019

From explainable AI to natural language humanising data analytics, James Eiloart from Tableau gives his take on the top trends in business analytics intelligence as we head into 2019.

Business analytics trends

Business analytics trends- Business analytics intelligence prediction number one: After the hype, the rise of explainable AI

AI promises to enhance human understanding by automating decision-making. But, as organisations rely on AI and machine learning for data-driven decision-making, we’re seeing a rise in human hesitation about the trustworthiness of model-driven recommendations. Many machine learning applications don’t offer a transparent way to see the algorithms or logic behind decisions and recommendations. This need for transparency will drive growth of explainable AI in 2019. If you can question humans, why not have the same option with machine learning when making decisions?

Business leaders will put greater pressure on data science teams to use models that are more explainable and reveal how models are constructed. AI has to be trusted to make the strongest impact, and the generated conclusions must be intelligible, simple and dynamically answer questions to help humans understand their data.

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Business analytics intelligence prediction number two: Natural language humanises data analytics

Natural language processing (NLP) helps computers understand the meaning of human language. BI vendors will incorporate natural language into their platforms, offering a natural language interface to visualisations. At the same time, natural language is evolving to support analytical conversation—defined as a human having a conversation with the system about their data. The system leverages context within the conversation to understand the user’s intent behind a query and further the dialogue, creating a more natural, conversational experience. That means when a person has a follow-up question of their data, they don’t have to rephrase the question to dig deeper or clarify an ambiguity. Natural language will be a paradigm shift in how people ask questions of their data. When people can interact with a visualisation as they would a person, it allows more people of all skill sets to ask deeper questions of their data. As natural language evolves within the BI industry, it will break down barriers to analytics adoption and help transform workplaces into data-driven, self-service operations.

Business analytics intelligence prediction number three: Actionable analytics put data into context

Data workers need to access their data and take action—all in the same workflow. In 2019, expect more organisations to use data analytics exactly where it’s needed and not in isolation. Organisations will truly reap the benefits of how BI platform vendors are offering capabilities like mobile analytics, embedded analytics, dashboard extensions, and APIs. Embedded analytics puts data and insights where people are already working so they don’t have to navigate to another application or shared server, while dashboard extensions bring access to other systems right into the dashboard. And mobile analytics put data directly into the hands of people in the field. These advancements are equally powerful as they meet the needs of different business teams and verticals by empowering new audiences with on-demand data in context.

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Harvard Business Review Analytic Services report reveals that only five per cent believe that their organisations are very effective at implementing modern data sharing, while 67% want to move towards that approach, showing that data sharing is very much on the agenda of organisations in the year ahead

Business analytics intelligence prediction number four: Enterprises get smarter about analytics

Business intelligence initiatives often have a well-defined start and end date and it’s not uncommon for them to be considered “complete” after they are rolled out to users. But merely providing access to business intelligence solutions isn’t the same as adoption. Chief data officers, primarily, are re-evaluating how BI adoption plays a part in a strategic shift towards modernisation, because true value isn’t measured by the solution you deploy, but how your workforce uses the solution to impact the business.  The assumption that everyone is getting value out of a BI platform just because they have access to it can actually be an inhibitor to real progress with analytics.

As these internal communities on-board workers onto a BI platform, organisations can start to delegate analytical responsibilities and create new user champions. This will ultimately reduce the heavy lifting for maintenance and reporting, traditionally reserved for IT.  More internal champions will start to emerge, acting as subject matter experts who socialise best practices and align people on data definitions. Inevitably, all of these movements will lead to more people using and getting value out of BI software. And most importantly, your workforce will become more efficient and your organisation more competitive.

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Article Credit: IA

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