Keeping Up With New Analytics Trends

Analytics is a constantly changing field. The demand for business analysts that understand this changing landscape has been growing steadily over the past few years. New technologies, analytical techniques, and methods of gathering data all play a part in developing analytics trends. Staying ahead of the curve in this field is important as the ability to do the most efficient analysis and present your findings in an engaging way is an industry-wide goal. 

Understand The Limitations Of Big Data and Artificial Intelligence (A.I)

The massive data pools generated by big data and the machine learning tools developed to interpret them aren’t necessarily new ideas in the analytics world. However, due to the shifting nature of these new technologies, they still remain a stalwart talking point in industry. While big data and the AI used to process it have made analytics much easier, there are still issues that need to be addressed.

These new systems of data collection and analysis suffer from a lot of the same issues that previous systems have. They are susceptible to the Swiss cheese effect, or “cumulative act effect,” wherein small mistakes can pass through holes in an implemented system, much like the holes in Swiss cheese. While this can often happen due to failed software, bad project management, or inaccurate requirements, individuals can also make these important mistakes.

Conversely, a human touch is often required to ensure that these mistakes don’t rear their ugly heads. Despite the fantastic possibilities of using machine learning and AI to process data lakes generated by big data collection, unless reviewed and analyzed by human eyes, it can often be misleading or even useless. Though it may seem on the surface that big data and AI are the future of analytics, humanity’s ability to think laterally and create inventive ways to solve or circumvent problems can’t be discounted.

Have Your Data Tell A Story

To those outside of the actual process of analysis, analytics can be perceived as, unfortunately, quite boring. While it is an essential part of the job to be able to provide suggestions for an actionable plan based on analytics, the fact remains that by the time you get to those suggestions, you may have lost the ear of your audience. Having them understand the importance of what you’re suggesting before you make the suggestion itself can help with the impact of your statements.

While storytelling isn’t generally included as part of a business analyst’s transferable skills, it is becoming more and more important. The ability to evoke a reaction to the analysis you’re providing in the moment is invaluable to the end result you’re trying to accomplish. If people feel a connection to the data you’re analyzing and you can make it seem directly important to them outside of a strictly numbers sense, their understanding of why you’re making your suggestions increases exponentially.

This idea of having your analysis carry meaning beyond just the facts of the data is catching on in the education world as well. For the professors at Ohio University and other universities across the country, when it comes to teaching students about analytics they are embracing the idea that it isn’t the size of the data, it is about the data’s story.

Ditch the Pie Chart

While there are only so many ways to present visualized data, nothing is more tired than the humble pie chart. Its round shape is more pleasant to look at than a sheet of seemingly meaningless numbers, and has been a staple in powerpoint presentations for years. The pie chart, along with the bar chart and line graph, deserve a break. You should consider benching them in favour of more engaging visualised data going forward. 

The main reason you should put thought into your presentation of data is similar to the reason you should have your data tell a story. Heightened engagement from your audience has virtually no downside, and the impact of an invested listener is massive. Instead of displaying large blocks of text in your presentation, do more talking about the specific subject at hand, making eye contact with everyone in the room. If you do end up using bar or line graphs, use colour selectively to highlight the important data relevant to your suggestions.

By allowing the audience to further engage with you during a presentation, you also encourage a greater level of feedback from them. Not only will you have more feedback overall, but the feedback you receive will be hyper-relevant, as it comes from an audience that is actually invested in what you have to say. By making your data more interesting and engaging, you help everyone in the room reach a satisfactory and unilateral resting point.