3 Signs That BI Will Never Be The Same Again
Gartner officially deemed 2016 the year of Modern BI and with this new era of BI changes are inevitable. Understand how the traditional BI is reshaping in this data century with Scrollytelling, citizen data scientist and new BI approaches.
By Pia Opulencia, Director of Platform at Narrative Science.
The communication process between analysts and business users has been long discussed even before “data science” became a hot new job title. An article by analytics industry leader, Tom Davenport, praised the concept of “light quants” and “analytical translators” within the workplace as an assistive force in helping organizations extract actionable insights from their data. “It would of course be great to have someone with heavy quant skills who is also a fantastic teller of analytical stories, but we are talking about a very small intersection of skills here. In fact, even if you once had strong communication skills, most graduate programs in quantitative fields will tend to drum those skills out.”
In fact, some argue that all technical skills aside, domain expertise is still the number one needed trait to be able to extract relevant findings from analytics. The heavy lifting to perform data analytics, understand the business problem and domain, and finally communicate it in a relevant, consumable manner narrows the available workforce with these specific combination of skills greatly. Organizations’ ongoing struggle to solve their “data problems” has forced the market to evolve, a few major trends taking place include:
Scrollytelling or Dynamic Storytelling
A recent trend called scrollytelling has surfaced. Readers can view associated media, like videos and photos, interact with charts and be immersed in a dynamic experience while scrolling through on a webpage. It makes for a beautifully designed and immersive experience, but it isn’t quite suitable for a business environment where decision makers need a concise recommendation presented up front.
Gartner officially deemed 2016 the year of Modern BI. BI tools historically have been geared towards data savvy folks within the IT organization and have developed capabilities surrounding their particular skill sets. The shift towards self-service BI and visualization as a means for communication to the true end report consumers, business users, has raised the bar in terms of ease of use, but also caused some concern over misinterpretation without an “analytical translator” by your side.
With Modern BI, platforms offer complimentary analysis tools like natural language generation integrated into the platform. When NLG is paired with data visualization, easy-to-understand narratives serve to automatically communicate insights from data, reducing overall time to insight, and scaling analytic practices enterprise wide.
An example of data visualization with NLG integrated.
Citizen Data Scientists
Citizen data scientists are folks that are data savvy, though their main roles reside outside of the IT and Data Science teams. Gartner describes these people as “power users” who understand data, technology, and come in the form of Business Analysts and other similar titles. The advent of Modern BI has provided them with intuitive, easy-to-use tools. I predict that citizen data scientists will enable the scalability of analytics across an organization and truly maximize the value of data. Some folks are skeptical of the new role, but nonetheless, the role highlights the need and importance of arming business users with the ability to accurately interpret data and effectively communicate insights in order to maximize the value of BI.
As Tom Davenport so aptly states, “stories have always been effective tools to transmit human experience; those that involve data and analysis are just relatively recent versions of them. Narrative is the way we simplify and make sense of a complex world. It supplies context, insight, interpretation—all the things that make data meaningful and analytics more relevant and interesting.”
Bio: Pia Opulencia is the Director of Platform at Narrative Science. She leads the development team building the next generation of Quill, an Advanced NLG platform that generates data-driven narratives at scale.
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