Latest Business Intelligence Trends (2019 BI Trends)

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How the BI is changing?

Redefined Reporting – Highly contextualized

We know that it’s not possible to everyone to explore their own data in detail every time, essentially, we see users with varying levels of skill sets. This means in 2018 and going forward, reporting will start to become redefined through providing both analysis and participants with highly contextualized information i.e. inverting analytics as we know today.
Rather than having to go to a destination to perform an analysis, it will come to users embedded right into their work space, getting the right information to the right people, at the right time, in the right place, and in the right context. And in that process, many more people will be empowered with data and analytics than ever before.


Analytics become immersive

Given that the price of virtual reality devices remains a bit too steep for mainstream adoption, we are still several years away from augmented reality. The breakthroughs likely will happen in enterprise use cases, with analytics playing a role. But immersive experiences can also take on other formats where users become engaged from a sensorial and social standpoint.
Through better user interfaces, large-scale displays in digital situation rooms, better storytelling with data, and collaborative features, more people will be drawn to using analytics.

An augmented intelligence system changes users into participants and facilitators.

Because Augmented Intelligence will be an essential component of all the trends featured, it is the 11th trend for 2018.
In its current state, the most effective use of Artificial Intelligence (AI) is applying it to a diverse but specific set of problems. But in 2018 and beyond, blending AI with technologies such as intelligent agents, bots, and automated activities, along with traditional analytical tools such as data sets, visualization, dashboards, and reports will make data more useful. That alone, however, isn’t enough. Instead, a system where machine intelligence and humans participate in a broader ecosystem, and the exchange and learnings that happen between them, is known as augmented intelligence.

Analytics become conversational

The use of analytics has traditionally been focused on drag-and-drop style dashboard list boxes and/or visualization. While there continues to be value in that, there are now more approaches available for “conversational analytics,” simplifying the analysis, findings, and storytelling so that users more easily get to that one crucial data point.
This can include natural language query, processing, and generation augmented by search and voice. This technology, helped by virtual assistants and chatbots through API integration, provide a new means of interaction.

Blockchain hype will drive experimental applications beyond cryptocurrencies.

New techniques are emerging for processing, managing, and integrating distributed data, making the location of data an increasingly smaller factor in information strategies. This means ideas can be inspired by blockchain and peer-to-peer technologies. While this is still in the beginning stages, 2018 will see innovation move beyond cryptocurrencies to experimental applications for analytics and data management.
Initially, connectivity to the blockchain ledger will have benefits. But ultimately, the value might lie in the ability to verify lineage and authenticity of data using blockchain technology.

Need for interoperability and new business models puts focus on APIs

As data, computing, and usage become more distributed, so do the technology environments of corporations. Companies are no longer looking for end-to-end solutions and single stacks as it doesn’t look like their architectures. Rather, they look for parts that can easily be stitched together, as it’s more important that different software systems talk to each other.

This means that analytics platforms in this new environment need to be open and interoperable, with extensibility, embeddability, and modern APIs. This interoperability will shift analytics from one destination to become more embedded in workflows, blurring the line between BI applications as we know them today to data-driven apps that fuel the analytics economy.

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