The Big Data Iceberg
If there’s one area of analytics that people get really passionate about, it’s visualization.
If there’s one area of analytics that people get really passionate about, it’s visualization.
In the past few years especially, we’ve had “discussions” on the differences between data science (DS) and statistics/machine learning as disciplines.
Does turning data into beautiful, elegant graphics actually result in a better-informed audience? Is it the most efficient, effective way to get your point across?
So much of life is random, and not just baseball. Or at least complicated beyond human comprehension, which is pretty much the same thing as random. And yet, we humans believe there must be a reason for what has happened,
In mobile business intelligence (BI) design, two elements are always in play. I refer to them as “utility” (not to be confused with utility in economics) and “impact.” At the micro level, they influence directly how we develop our mobile assets (reports, dashboards) in order to effectively deliver actionable insight through the mobile user interface and experience. At the macro level, they influence how we designand execute our mobile BI strategy.
Think about one of your favorite apps for personal or business use (excluding games). What part or functionality leaves a lasting impression with you and/or makes you want to come back and use it again and again? What are some of the techniques that the designers of that mobile app used to draw you in? Was it simplicity, performance, the smart use of graphics, or maybe something else that you haven’t seen before?
In the last installment of this series, I described the three key steps that everyday business intelligence (BI) users typically go through when they consume data: Observation, Perspective, and Insight. These steps often take place in an ad-hoc manner without the same degree of precision and requirements that one expects in corporate BI environments. Nevertheless, everyday BI users follow a similar process to achieve the same end goal—insight through data for better-informeddecisions.
Everyday BI users rely on technology solutions that can deliver insight-driven and action-ready information. This is important for businesses because better-informed consumers tend to make better-informed decisions. And they tend to be more loyal because they recognize the improvements that these solutions can make in their daily lives.
How have you seen these three steps to insight unfold in your everyday BI experiences?
In mobile business intelligence (BI) design, performance is one of the most critical elements of the mobile BI success formula. High quality content, reliable data, andmobile purpose are a must. However, none of that matters if the performance is poor—mobile users tend to be less patient about performance. Think about it for a moment. Unlike a PC users who may be chained to a desk, mobile BI users typically access mobile BI assets on the go and with less time to spare.
Sports and entertainment organizations collect tremendous amounts of data on the fan experience, such as attendance, ticketing, merchandise, etc. These data troves can provide invaluable opportunities for growth and profitability. That is why I called sports and analytics a “perfect couple” in my Sports & Analytics series.
However, having all the data doesn’t do much good if we are not asking the right business questions — or don’t have the right analytics platforms to answer them.