Data visualization has become a red-hot analytics topic of late, but for Ford Research & Advanced Engineering's data science team, it's long been standard fare. That makes Mike Cavaretta, technical leader for predictive analytics there, the perfect go-to guy for advice on exploring and presenting data visually.
"Our perspective is that data visualization techniques add so much that it's really important in a data science effort to be able to use these techniques," Cavaretta told attendees of our live video chat on visual analytics yesterday.
Mike Cavaretta, Ford
At Ford Research & Advanced Engineering, data visualizations come into play when analysts are simply trying to understand the data, Cavaretta told us, as well as when they're exploring the data and looking for the unusual to pop out:
A visualization can help a lot. Just plotting things on a timeline can give you an idea of "are you hitting the peaks, are you hitting the valleys, are you hitting the trends in the data" -- how well the model is working that you just can't get from a simple statistic like an error rate or an R-squared or something like that.
Visualizations also help tell stories about the data, he added:
How do you synthesize what you have and show your conclusions in an easy-to-understand way? How do you present that to people who aren't statistically savvy, per se, but know data, understand data, and have a really good feeling for the business? That's really the key piece for us.
Below are five tips on working with data visualizations that Cavaretta shared during yesterday's video chat, which you can listen to on demand, here.
Start small: "Have some really good prototypes from really good proofs of concept," suggested Cavaretta, noting that starter data visualization software is readily available from companies like QlikView, Tableau Software, and Spotfire. Buy a single seat, do some experimentation, and show people the results and how dynamic the presentations and the data can be. Or do the same using the open-source R statistical tool. That'll take a bit more effort, though, since you'll need to do some programming, he cautioned.
Know your audience: Some people will have the time and ability to understand data visualizations and others won't. It behooves you to figure out which type of group you're presenting results to before you decide to package those visually. Ideally, the group will understand the data you have and have the time to sit through an animation of it, à la the dynamic visualizations at Gapminder, and so you can make your presentation interactive and iterative.
"That's the one that we'd rather do," Cavaretta said. "Those are the better presentations -- people are engaged, they can ask questions, and we can slice and dice on the fly." However, sometimes you'll only have 10 minutes at a board meeting to explain a complex project in a way that directors are sure to understand. Working with dynamic data visualizations might not be the best choice in such circumstances.
Don't assume a visual presentation is always best: When you're getting ready to share results, think about whether you really want to present your data visually or whether a textual narrative would be better. If you're making recommendations, stating "to meet your cost targets, you need to remove 10 cents from every part" may provide greater clarity than trying to show that through data visualization. "For the most part... you're not going to be able to be dynamic and have that narrative there. That's the piece that we've found really, really important."
Watch out for complexity: "The complexity of the visualization is sometimes very, very tempting -- being able to have something that puts everything together in one chart, one big graphic, so you're showing the distribution, you're showing the forecast, you're showing the six different variables you think are going to drive what's going to happen in the future," Cavaretta said. You and your team might understand what's going on in the visualization perfectly well, but "for somebody who hasn't lived with the data for the past two months, it can be very complex."
If you do decide to layer in lots of elements, then you'd best make a determined effort to be sure that you explain everything clearly so that everybody understands the complex visualization when you're done explaining it, he advised. The same best-practice applies to creating static infographics, he added. Maybe you don't put those four important elements into a single infographic but rather do two and two, for example.
Put another set of eyeballs on your results: Cavaretta and his team members make sure they validate results among one another -- and he recommends everybody do the same. "It's not necessarily a formal process, like a code review, but it is always something where we want to make sure we have fresh eyes on whatever we send out and how we communicate our results."
How are you using data visualizations in your company? Share your best-practices below.
I would think it'd also make sense to do a run-through of a presentation, including showing the visualizations that would be presented, prior to the business meeting. Do you think that happens often... or often enough?
@tomsg, you make a good point about wanting to know the assumptions. I don't know too much about other data visualization tools, but I do know that SAS Visual Analytics provides pop-ups that explain what the visualization means, assumptions, algorithms used, etc.
@kq4ym -- I think, too, it depends on the purpose, as Cavaretta said. If you want your audience to take away the information and really think about it later, text might be better remembered. Although he does say his team will use good infographics, too -- the type using lots of facts and text as well, a la the New York Times (though he says his team is not nearly as good as the NYT designers!). So static visualizations with text definitely have a place.
For some reason when I just see a visualization, I worry about assumptions and filters that may have helped make a point rather than just present the facts. I don't mind a visualization, but I always want the underlying data and a list of assumptions.
I would certainly agree to be aware that not all audiences want the visuals. I've seen way too many presentations that could have more easily be presented in text. After all, a visual is a summary in a lot of cases, and what is better to summarize than language.
As said in the blog, it is important to understand that whether the audience is that which needs to understand the nitty gritties of the topic concerned or needs final numbers and facts so that they are able to take a decision. If the audience is the former type, then analytics in the form of visuals can help else a text-based summary might suffice. In a board of directors meeting for e.g. you dont want to hear from a director "we are not interested in the details, all we need to know is that the project is to feasible or not so just give us a brief idea" hence making analytics in the form visuals completely unnecessary.
NRF Retail's Big Show 2015The flagship industry event of the National Retail Federation, Retail's Big Show is an annual event held over four days in New York City. As the world's leading retail event, the Big Show brings together 30,000 retail professionals and vendors from more than 86 countries, and features more than 100 education sessions, 270 speakers and 550 exhibitors. The conference connects retail solution providers with retail executives searching for the most effective solutions, tools and technologies.
LEADERS FROM THE BUSINESS AND IT COMMUNITIES DUEL OVER CRITICAL TECHNOLOGY ISSUES
The Current Discussion
Visual Analytics: Who Carries the Onus? The Issue: Data visualization is an up-and-coming technology for businesses that want to deliver analytical results in a visual way, enabling analysts the ability to spot patterns more easily and business users to absorb the insight at a glance and better understand what questions to ask of the data. But does it make more sense to train everybody to handle the visualization mandate or bring on visualization expertise? Our experts are divided on the question. The Speakers: Hyoun Park, Principal Analyst, Nucleus Research; Jonathan Schwabish, US Economist & Data Visualizer
The hospitality industry gathers massive amounts of customer data, and mining that data effectively can yield tremendous results in terms of improved CRM, better-targeted marketing spend, and more efficient back-end processes. Roger Ares, vice president of analytics at Hyatt Corp., discusses the ways he and his staff use big data.
Charged with keeping track of travel assets, including employees, iJET International relies on data management best-practices and advanced analytics to keep its clients in the know on current and potential world events affecting travel, Rich Murnane, Director of Enterprise Data Operations & Data Architect, told All Analytics in an interview from the 2014 SAS Global Forum Executive Conference.
Jason Dorsey, chief strategy officer for the Center for Generational Kinetics and keynote speaker at last month's SAS Global Forum 2014, describes how Gen Y professionals are enhancing the makeup of multigenerational analytics organizations.
From analytics talent development to the power of visual analytics, All Analytics found a variety of common themes circulating throughout the exhibition floor and session discussions at the 2014 SAS Global Forum and SAS Global Forum Executive Conference events held last month in Washington, DC.
Talking with All Analytics live from the 2014 SAS Global Forum Executive Conference, Eric Helmer, senior manager of campaign design and execution for T-Mobile, discussed the importance of customer data -- starting internally -- in devising the mobile operator's marketing plans.
The big-data analytics market can be a confusing place. Among the vendors vying for your dollars are traditional database management providers, Hadoop startup services, and IT giants. In this video, All Analytics editors Beth Schultz and Michael Steinhart sit down in a Google+ Hangout on Air with Doug Henschen, executive editor of InformationWeek. Henschen discusses use cases for big-data analytics, purchase considerations, and his recent roundup of the top 16 big-data analytics platforms.
At the National Retail Federation BIG Show last month, All Analytics executive editor Michael Steinhart noted a host of solutions for tracking and analyzing customer activity in retail stores. From Bluetooth beacons to RFID tags to NFC connections to video analytics, retailers must find the right combination of tools to help optimize the shopper experience, streamline operations, and boost revenues.
The days when historical shipment trends and gut feelings were enough to forecast retail demand accurately are long over. SAS chief industry consultant Charles Chase outlines the benefits of pulling real-time sales information from point-of-sale and product scanner systems, then flowing that data into dynamic forecasting tools from SAS.
With today's advanced visual analytics tools, you can stream data into memory for real-time processing, provide users the ability to explore and manipulate the data, and bring your data to life for the business.
Dynamic data visualizations let analysts and business users interact with the data, changing variables or drilling down into data points, and see results in a flash. Advance your use of data visualization with tools that support features like auto-charting, explanatory pop-ups, and mobile sharing.
No doubt your enterprise is amassing loads of data for fact-based decision-making. Hand in hand with all that data comes big computational requirements. Can traditional IT infrastructure handle the increasing number and complexity of your analytical work? Probably not, which is why you need a backend rethink. Big data calls for a high-performance analytics infrastructure, as Fern Halper, a partner at the IT consulting and research firm, Hurwitz & Associates, discusses here.
Redbox's bright-red DVD kiosks are all but ubiquitous these days, located in more than 28,000 spots across the country. Jayson Tipp, Redbox VP of Analytics and CRM, provides an insider's look at how the company has accomplished its phenomenal nine-year growth.
InterContinental Hotels Group (IHG), a seven-brand global hotelier, has woven analytics into the fabric of its operations. David Schmitt, director of performance strategy and planning, shares IHG's analytics story and his lessons learned.