Getting Started withData Visualizationwww.boostlabs.com / ali@boostlabs.com / 301.560.7901

Table of Contents03 //

04 //

05 //

06 //

07 //

08 //

09 //

11 //

Creating an Infographic: 8 Critical Elements of Link Worthy Visuals

New Digital Marketing Trend: Interactive Data Visualizations

Telling Stories with Data: Using Big Data Effectively

4 Great Data Visualization Tools for Data Analysis and Insights

Show Your Data Truth

The Hidden Benefit of Data Visualization: 3 Crucial Insights into Your Data

Data Visualization: A Distinct Design and Visual Communications Medium

Building the Right Team: The Role of the Information Designer in Data Visualization

3

_______________________

Creating an Infographic: 8 Critical Elements of Link Worthy VisualsThe key to a great infographic is the ability to commu-nicate a complex message simply and quickly to your target audience. Of course, creating an infographic is easier said than done. Infographics require extensive planning in order to communicate messages and information effectively and be visually engaging.

While there are some qualities that infographics share with all marketing pieces (follow your brand voice and tone, focus on clarity instead of jargon and provide value instead of just self-promotion), there are several differences too. Remember these 8 elements when creating your next infographic and your project will be much more likely to achieve success.

Element #1: Make Sure to Explain “Why” in Addi-tion to “What”

Infographics are usually loaded with data, but don’t let those numbers steal the show. Be sure to explain the relevance of the data to your reader. The most effective infographics leave the viewer not only with an understanding of the data, but with an understanding of how that data impacts their lives.

Element #2: Plan for Who and Where

After your actual data, the target audience is probably the most import consideration when planning your infographic. Considerations like expected indus-try knowledge, age and even demographic-based interests will all contribute to the appropriateness of data and design elements of your visualization. It won’t do you any good, for example, to reference Gilligan’s Island in an infographic designed for a millennial audience. While you’re thinking about your target audience, take a moment to think about your distribution platform too. If the infographic will live on

a full-sized web page, maybe it’s ok if it scrolls a few pages down. However, if your visualization will end up on a smaller page, a mobile interface or even print, you’ll want a more concise design.

Element #3: Have an Effective Headline

Just as newspaper headlines lure in readers, so too must infographic headers. Brevity helps here: maybe seven words or so. Try to put yourself in the read-er’s shoes and ask yourself: Would this intrigue me? Would I want to read this based off the headline?

Boost Insight: Don’t get too bogged down with SEO considerations in your infographic. You’ll have time to add keywords and modify titles and categorization when you distribute the infographic.

Element #4: Make the Visuals Pop

It may seem obvious, but visual content marketing depends on standing out. If people get bored, they move on. Drab colors, uniform graphics and tradi-tional data visualizations are very likely to be ignored.

Take the time to create an infographic with a polished design and striking features so that the data you have to share actually gets noticed.

The way you accomplish this will vary from brand to brand and concept to concept, but a few ideas to consider are:

n Imagery-based charts and graphs

n Striking color combinations

n Multiple font changes

Element #5: Include an “Aha” Moment

To really grab your reader’s attention, offer them a snippet of the data that they’re not expecting. You likely have a bigger story to tell, but by giving the reader a single bit of interesting data, you’ll capture their attention and raise the likelihood that they’ll read through the entire infographic.

4

Element #6: Make It More Than a List

Be careful not to fall into the “list-making trap” so common to less-effective infographics. Lists are, by nature, pretty mundane. It’s not enough to give your viewer points 1 through 10 if you want them to be engaged and interested.

Amplify the impact of your list with visuals that provide additional meaning. By involving your readers with storytelling – focusing on how this information and data is useful to them – you can create a much more effective visualization.

Element #7: Do Not Lie (Intentionally or Accidentally)

You probably don’t need to be told that lying is bad – but with infographics, it can be easy to do so accidentally. When you create your data visualization, the elements need to accurately portray the numbers they represent.

If your data doesn’t tell the story you want it to, don’t force it through your infographic – take a moment and find a new story to tell.

Element #8: Build it For Sharing

No matter how great your infographic is, if only one person sees it, it’s not very effective. Making viewers want to share your infographic is part art and part sci-ence. Start by being sure that you have an engaging story to tell. Ask yourself, why is this information im-portant? Why should my audience care? Then, make sure that your infographic tells the whole story so that new viewers won’t need background to understand what they’re seeing. Finally, be sure that you distribute it on channels that allow for easy sharing so people don’t have to work to get your visualization to their friends, family and co-workers.

Creating an Infographic or data visualization is a big undertaking – why work hard without doing it right?

_______________________

New Digital Marketing Trend: Interactive Data Visualizations

Interactive data visualizations have the power to return trust to marketing.

It’s a sad truth, but consumers don’t trust marketing anymore. Marketers have eroded the relationship with their customers and prospects over the years almost beyond the point of rescue. It started with brands “shouting” their message on every available channel including print, television, cinema and eventually the internet. As consumers became more crafty (“Wait… there can’t be TWO best Cola drinks of all time”) mar-keting evolved.

As consumers began craving data and statistics in order to make more informed decisions, marketers started using this information in their advertising efforts. However, the overuse and manipulation of statistics caused consumers to mistrust that form of marketing (“How can 4 out of 5 Dentists prefer EVERY type of toothpaste?”).

From this past the modern consumer is born – one who wants to be able to understand the information they’re being given and where it came from. A con-sumer who wants to make their own decisions and not have the conclusions given to them.

Infographics present a unique challenge in this landscape. The very nature of a data visualization is to take complex data and boil it down to an easily consumable story that your audience can relate to. However, the amount of data you can present is limit-ed for these key reasons:

n The infographic may be exploratory or explanato-ry, but serving both purposes creates a complex and difficult-to-read (thus ineffective) visualization.

n The static visual format allows little room to pro-vide a context to the data being presented, and without context, the impact is lost.

n The static nature of an infographic means that the data can become out of date and unintentionally misleading.

These limitations and the relative ease with which data can be skewed can cause consumers to mis-trust the information presented in the infographic. Consumers may be reluctant to believe the story your infographic tells if they can’t make the same conclu-sions themselves.

An Important Note: Infographics are still very effec-tive marketing tools and a significant number of mar-keters do not use them to mislead their audience. You shouldn’t stop using them – instead you should be aware that as consumers continue to crave more and more information, infographics may have to evolve to meet the need.

5

Interactive Data Visualizations: An Evolutionary Step Forward

Well-designed interactive data visualizations have a significant advantage over their static counterparts: They can include both the conclusions and the data used to draw them.

This is done by creating interactive layers that give users the ability to dig deeper into your data story. For example:

n An interactive graph showing that a majority of the sample preferred your product can be clicked to show the exact question that was asked and explain who answered it.

n Real time business data in an analytics dash-board can show trends which can be clicked to show changes over time and the original data used to make predictions and draw conclusions.

n Recommendations can be drilled-down to show the user the actual data that was used to cre-ate them, instead of leaving them to wonder if it came solely from a desire to steer their dollars towards one product or another

n An interactive data visualization using real time web traffic data to show the most shared content on social media networks can be clicked to show the actual number of clicks and visits per post.

The advantage to this type of marketing is that you can still present an uncluttered data story. At the same time, you allow investigative consumers to see the data that you used to reach your conclusions (and then draw their own, hopefully similar, conclusions).

The Landscape Isn’t the Only Thing That’s Chang-ing: If your data story is based on information that can change frequently, creating a static infographic each time is a costly undertaking. In addition to user interactivity, interactive visualizations can dynamically re-draw themselves based on a fluid data set.

Understanding current consumer trends is critical to effective marketing. Currently, that means giving consumers the ability to inform themselves. Embrace this digital marketing trend and give them access – if you’re representing your information fairly and ethical-ly, they’ll draw the same conclusions as you and that will only serve to improve your relationship with them.

After all, isn’t that what great marketing is about?

_______________________

Telling Stories with Data: Using Big Data Effectively

Using big data effectively, at its heart, is just another form of storytelling. Like a story, big data isn’t effective unless the audience comes away from the experience changed. Of course, also like telling a story, creat-ing that sort of impact isn’t easy. We talk a lot about “telling stories with data”when creating data visualiza-tions, but what does that actually mean?

Why Call it a Data Story?

A story is a complete method of transferring informa-tion. It starts by setting the context or setting, adds layers of information and change, and finally reach-es a conclusion. This package gives the audience everything they need to understand why they are hearing the information, what that information means to them, and how they should use the information going forward.

A well-executed data visualization does the same thing. In a single package, the visualization explains the context, provides the information, and gives a conclusion. In order to make that happen, you need

to think about your data as a story.

What Exactly is a Data Story?

A data story isn’t much different from any other story – there’s a point you want to make and you need to lead your audience on a path from ignorance to awareness. The biggest difference with a data story, however, is that they’re usually inspired in one of two ways:

You have a collection of data you’d like to put to use – the ending isn’t well-defined, but you have all the elements necessary to get there.

You know the point you’d like to make and want to use data to back

it up – you know the ending you’d like, but may be unsure of how to use your data to get there. You know what you’d like to show, but have to interpret existing data to see if it works, or compile new data to make your point.

Whether you’re starting at the end and working back-wards, or starting at the beginning and discovering where your data leads, you motivation is to inform, educate and maybe even entertain to your audience.

6

How do you Tell a Data Story?

Like any good presentation, telling your data sto-ry starts by knowing your audience. Unlike a more traditional story, however, your data story requires a more in-depth understanding of your audience to be truly effective. Ideally, you can define your audience by answering these questions:

n Who is your target reader/viewer? (What role do they play, title do they have, etc…)

n What do they want to know? (What information is important to them.)

n How do they like to see data presented? (Are they likely to prefer an in-depth data table, or will charts and graphs be sufficient? )

n Where will they find your data story? (How it’s best distributed will help you understand the medium you can work with)

The format you choose for your data story will rely heavily on your target audience, but there are several options to choose from:

n Text

n Infographic

n Interactive Data Visualization

n Motion Graphic

n Video

n Interpretive Baboon Symphony

There’s still plenty of work to do from this point. un-derstanding what kind of story you want to tell, who you want to tell it to and how you’ll be telling it are the most critical decisions for creating an effective data story. Big data is, as its name suggests, imposing – but the most important element is the story it tells. Finding those stories and telling them is how you can make big data work for your marketing goals.

_______________________

4 Great Data Visualization Tools for Data Analysis and Insights

When creating data visualizations, there are two primary options: hiring a data visualization specialist/agency or using data visualization software. Each method is appropriate for different types of visual-ization projects. If you have a project that is best served by data visualization software, then you’ll need to choose the best data visualization tools for your project.

We’ve compiled a list of the tools we know and like – the one that’s right for you will vary based on your specific project needs, but these will give you a start:

MicroStrategy Analytics Desktop

MicroStrategy Analytics Desktop is a fast and us-er-friendly software for visual data analytics. Quick to download and install, this visualization software allows you to get to work quickly. Included sample data and pre-built interactive dashboards further serve to lower the learning curve.

MicroStrategy allows you to connect any database you like, import Excel spreadsheets/CSV files and even import data from an online source. What’s more,

you can blend multiple data sources and types to gain the exact insights you need.

The basic version is free and allows for simplistic, but insightful, visualizations to be created. If your project requires more advanced features, like Salesforce Re-porting, Enterprise Information Integration or Mobile access, upgrading to “Analytics Enterprise” allows you to access to these features.

Domo

Domo offers an online business intelligence tool that has a sleek UI and is specifically designed to allow users to build sophisticated dashboards with no IT in-volvement. Because the software is accessible online, Domo and the dashboards it creates, are available to your entire organization.

Their Domo platform is particularly well-suited for users looking to visualize data in existing cloud-based apps like Salesforce.com. In addition to cloud-based apps, Domo can take input from databases, spread-sheets and even social media platforms. The output is just as versatile – Domo created dashboards are de-signed to be viewable on tablets and mobile devices in addition to a traditional PC interface

Tableau

Tableau offers a suite of tools that include an online, desktop and server version. All of these versions pro-vide a easy-to-use drag and drop interface that can help you quickly turn your data into business insights. The online and server versions allow your entire team to build and work with the visualization tool.

Like many other data analytics and visualization tools, Tableau can connect to local or remote data of many different formats. Additionally, the Tableau engine can connect to live data for up-to-date visualizations (at the sacrifice of some speed) or warehoused data for much smoother-moving visualizations.

7

QlikView

The QlikView business discovery platform is one of a few visual analytics tools offered by Qlik. QlikView can’t create the same elegant visualizations that the other tools offer, but the software’s dynamic model means that you can quickly analyze your data in mul-tiple dimensions. In addition, QlikView is able to work off of data in memory instead of off your disk, allowing for real-time operational BI environments (like monitor-ing financial transactions).

QlikView is able to work with a wide variety of data sources, including SAP, Oracle, Salesforce.com and other legacy data files like Excel spreadsheets. What’s more, QlikView can combine these disparate data sources into a single visualization or dashboard.

Although there are some noteworthy challenges when it comes to creating scripting and troubleshooting data challenges, the QlikView tool is generally quite user friendly and offers robust filtering options.

When you need the ability to quickly visualize your data or use a dashboard to watch for known, expect-ed and unexpected circumstances, visual analytics software may be right for you. Choosing the best data visualization tools for your organizations needs is a process of trial and discovery. These four options are a great place to start.

When you’re looking for a data visualization that will have a high return-on-investment, a custom dash-board may be right for you.. A custom data visual-ization dashboard allows your organization access to data in real time, allowing you to quickly understand key business metrics and make decisions based on that information. Custom visual dashboards save time, improve decision making, and help save or bring in new revenue. Experienced data visualization firms like Boost Labs can build a great custom dashboard that is tailored to your company’s needs.

_______________________

Show Your Data Truth

Most of our clients never seem to have an issue when it comes to data collection. After all, data is everywhere in a business and it’s profoundly silly how quickly and easily it piles up. It can be difficult to de-termine the right time to pull insights, tell that incredi-ble data story, or just do something, anything, with it.

Why is it a challenge? Here are some common rea-sons:

n Data is available, but it’s not easily accessible (unstructured or various locations)

n The Data available can’t support the intended story

n The Data doesn’t tell a clear story

Given these complications, how do you get your data out there?

1. Tell an “Internal Data Story,” not meant for the wider world

A story that can be told internally is the best way to vet your idea. Things like sales pipeline info, customer satisfaction ratings, etcetera can all be great baseline metrics for an overall story. On occasion, this can lead to providing a level of transparency to the entire company and help them unite around a common goal. The end product can also provide an idea for possible external ap-proaches.

Example: One of our clients decided to build an executive dashboard that showcased the company’s revenue performance via key metrics. We developed unique charting types within a specific layout driven by data

relationships, the combination resulted in an illumi-nating experience, used throughout the company to help inspire greater performance. This dashboard has also led to the motivation of publicly bound products that showcased valuable insights to its customers.

8

2. Perform Data Discovery

Everyone overestimates how difficult it is to visualize your data, but with data manipulation products like Tableau, Domo, Pentaho, IBM’s Many Eyes, D3, and R, among others, it’s that much easier to gain under-standing of data using a visual medium.

The key is to start with a simple portion of your data and to start pulling basic insights to visualize and correlate with each other. This process leads to a compound series of questions that can help provide an overall vision to the end product goal. We see the effect during our discovery process, which usually leads to unforeseen avenues for data intelligence.

Example: A client of ours had a challenge with their existing customers. Their clients were in a process rut when it came to gaining intelligence via our client’s data set. This meant that our client’s customers were quickly hitting a perceived value ceiling when it came to extracting the most insights out of the data set. The simple solution came down to how the data was visualized and internally struc-tured.

Through our innovation process we created a “Rainbow Matrix Sphere Grid” design to help solve our client’s challenge. Users can select multiple items for a campaign, visualize relationships be-tween all items, see the population that the cam-paign can target, and create interlinking boolean rules. This ultimately helped our client’s customers lead to a better process of exploring out of the box insights, thus gaining more value out of the same data set.

_______________________

The Hidden Benefit of Data Visualization: 3 Crucial Insights into Your Data

A slick chart, an interactive data-exploration inter-face or a KPI-based dashboard; all of these are data visualization products. They garner a lot of attention because they are a finished product, and look nice as well. However, for many companies engaged in data visualization, those final deliverables aren’t the most important benefit of data visualization. Instead, it’s the insights into the quality of their collected data that truly leads to success.

Data visualization provides 3 key insights into data:

n Is the data complete?

n Is the data valid?

n Is the data well-organized?

Without knowing those 3 elements, data collection and business intelligence processes become much more expensive, labor intensive, and may end up abandoned when the data doesn’t demonstrate what is intended. Using the insights from data visualization,

these projects can have a much higher likelihood of completion and success.

Insight into Data #1: Is the data complete?

The most straightforward insight that visualization can give you about your data is its completeness. With a few quick charts, areas where data is missing show up as gaps or blanks on the report (called the “Swiss Cheese” effect).

In addition to learning which specific data elements are missing, visualizations can show trends of missing data. Those trends can tell a story about the data collection process and provide insight into changes necessary in the way data is gathered.

A Data Completeness Example: After creating a visu-alization on a collection of survey data regarding mov-ie-going habits, it’s clear than there are a significant number of blanks after question 14 on the survey. The visualization helps the survey company recognize that those specific records need to be abandoned, but also that the survey should be shortened to accom-modate for “respondent fatigue”, the likely cause of the incompletions.

Insight into Data #2: Is the data valid?

The importance of visualization among data vali-dation techniques has been discussed before. It’s clear, then, that visualization can play a pivotal role in understanding data’s validity. By executing a quick, preliminary visualization on collected data, trends that indicate problems in the complete data can be found.

A Data Validation Example: A collected dataset is designed to demonstrate the difference in male population statistics between Alaska and Florida. Examination of individual records and outliers show that the data is valid – there are a significantly higher percentage of males in Alaska than in Florida, this is expected. However, a visualization of the entire data-set shows that there are more males in Alaska than Florida. This is a red flag because, even with the gen-

9

der ratio differences, Florida’s larger population means that it should have a higher total number of males.

A well-designed, preliminary visualization can give in-sight into the validity of collected data that is difficult, or even impossible, to gain with traditional methods.

Insight into Data #3: Is the data well-organized?

Poorly organized data can be the bane of the final step of a data collection or business intelligence pro-cess. Using data organization tools from the start can help streamline later steps of the process.

During collection, the data is often organized in a way that optimizes the gathering process. However, that same organizational scheme can be a problem when the time comes to act. The data visualization process serves to highlight the organizational challenges of your data and provides insights into how it might be done better.

A Data Organization Example: A client wishes to use their collected customer data to develop a cus-tomer profile that defines demographic breakouts of snack-food purchases indexed by time of day. Their data visualization partner asks them where that data is stored and it is discovered that the transactional data is stored separately from the customer profile information, and that data can only be intersected through yet another correlational dataset. While all the data is technically available, the data needs to be reorganized to be functional in decision making.

Data visualization isn’t just data organization and analysis tool; it can play a crucial role in the entire data gathering and management process. With a well-executed visualization, taking time to understand what is to be learned from the data and how the in-formation will be gathered, companies are able to cut costs and eliminate the waste that comes from having to re-gather or re-organize their data.

_______________________

Data Visualization: A Distinct Design and Visual Communications MediumLet’s start with a conversation about basketball before we dive into data visualization. In 1993, at age 30 and after leading the Chicago Bulls to three consec-utive NBA championships, Michael Jordan (typically referred to as the best player of all time) announced his retirement from basketball to pursue a career in professional baseball. That second career lasted less than two full seasons in the minor leagues, where one of the greatest athletes of all time struggled to even be called “average.” He eventually returned to basket-ball and led the Bulls to three more championships.

As amazing as he was, Jordan couldn’t transfer his ability into another “medium.” His years of honing his skills as a basketball player didn’t translate to base-ball. His expertise in one sport did not automatically qualify him for success in another.

This same principle holds true for data visualization. Too often, marketers, CEOs, data analysts and more assume that a data visualization is just a graphic with some charts on it and treat the design process as the same. This leads to poorly created visualizations, lengthy revision cycles and generally a dissatisfaction with the final product.

10

Visual Communication through Data Visualization & Infographics Stand Apart from Graphic Design

A painting, a piece of prose, a dance, a powerful con-certo, or a line of poetry: Each of these is a separate and distinct medium of expression. Each invokes dif-ferent reactions and emotions. Each works differently, and demands its own degree of expertise.

It’s why Michael Jordan couldn’t hit a curve ball.

Data visualization isn’t just an extension of graphic arts. It’s a medium that demands specific expertise. You may have that person in-house, in the form of an information designer, but many companies need to look externally for this resource. But, even with the right designer, your job is only just beginning.

Good Visual Communication Design and Data Viz Start with Knowing Your Data Story

Data visualizations are a unique communication medium in that they tell a complex data story visual-ly. It’s crucial, then, that your visual communication projects start with a story. You have some information you want to share with your audience and you want it to inspire some action from them. Knowing the final objective of the visualization is so important that an experienced information designer or visualization agency won’t even begin designing until this step is accomplished.

Finding that story can be difficult, especially when the impact of a data set isn’t clear. That’s where you can leverage additional resources to understand what your information actually means to people. Try these resources to help you interpret the story your data tells its target audience.

n Another Department in Your Company – other departments will bring their own perspective to the data and show you how it impacts the people they work with most often (prospects, existing clients, past clients, vendors, etc…)

n A Long-Standing Client – letting your trusted and long-standing clients look at your data and help you interpret what impact it has on them is a great way to get the general client perspective.

n An Experienced Data Visualization Agency – Data visualization agencies look at data every day and help companies tell the stories behind it. Use one as a resource to understand what your data can say.

After you’ve decided on the story you want to tell, take a moment to be sure that your data actually backs it up. If your data doesn’t correlate, you can either find a different story or collect other data. Either solution, in the long run, is better than trying to force a visualization to represent the data in a way it doesn’t fit.

Define the Audience for Your Visual Content

Storytelling 101 (and thus, Marketing 101) is “know your audience.” Because data visualizations tend to tell a complex story, the more you know about the target audience, the more powerful the data visualiza-tion will be.

By knowing your audience, you know how:

n Data should be gathered – Collecting the data that matters to the final audience the first time around saves time and money by avoiding costly re-gathering.

n Data should be set up for presentation – Knowing the expertise and experience of your audience allows you to know how complex the presentation can be (and how much background needs to be explained).

n The data visualization should be distributed – Getting your visualization in front of the right people means putting it where they’re already hanging out. Knowing your audience means that you know how to reach them.

A final piece of visual content like a data visualization or infographic is often a static image – and that has led people to believe it’s just another “graphic design project”.

Remember that visualization is its own communica-tion medium, requiring a different level of expertise and different work before any lines are drawn. Get started right, and have the right members on your team, and you won’t be driving the lane when you should be swinging for the fences.

11

_______________________

Building the Right Team: The Role of the Information Designer in Data VisualizationThe total volume of information in the world is growing exponentially (actually, it’s doubling each year). On top of that, information is more important to marketing and business intelligence than it’s ever been. Because displaying that information in an easy-to-digest data visualization or infographic is so important, it’s crucial to have the right skillset on your visualization team.

All designers handle the challenge of presenting information. Their objective is always to engage and enlighten, and often to persuade. However, not all designers are capable of presenting complicated data stories and insights in a way that is:

n Engaging

n Explanatory

n Easily absorbed

n Accurately portrayed

Enter the information designer.

How is an information designer different from a graphic designer?

Let’s start with an analogy: Baseball pitchers and information designers have a lot in common. There are 9 men on the field for a professional baseball team at any given time, and they all have at least one thing in common: They can throw a ball fast and accurately. However, that doesn’t mean they can all pitch. There’s more to pitching than just throwing the ball hard and straight – it’s a specific talent and skillset that must be found and cultivated. The same is true of information designers.

Most professional designers are skilled at using lay-out, color and other graphical elements to make the presentation of information attractive and readable. But, typical graphic designers tend to be concerned with generating an emotional response only in the viewer.

The information designer, on the other hand, tackles different communications challenges. While an infor-mation designer’s final product must be attractive and eye-catching, their true job is to connect intellectually with emotion. That means that an information design-er will place a higher priority on accuracy and ease of data consumption within an aesthetically pleasing visual context.

However, engaging graphics are still a key part of their responsibility. Information designers don’t abandon the idea of having a visually compelling end-product – they simply make sure that their presentation deci-sions reinforce the data instead of obscuring it.

What makes an information designer special?

First and foremost, a good information designer needs to be a good graphic designer. The skillset required to create great data visualizations and info-graphics includes the same graphic design under-standing and training of a traditional designer. As a general rule, an information designer is fully capable of handling the role of a traditional graphic designer. The opposite, however, cannot be said.

12

A good information designer has additional skills that lend themselves toward understanding and present-ing data. For some, these come from a background in mathematics, statistics, or research. For others, it may be business school or management training. Whatever the reason, data speaks to these people and they are able to coherently “speak data” to oth-ers.

Put plainly, an information designer will be better equipped to understand the story within your data and then tell it with a data visualization. That means they can:

n Create the project more efficiently

n Notice discrepancies or other issues with the data set

n Offer insight into better ways to reach your objec-tives

n Work directly with analysts to find additional data points

Sharing the tremendous amount of data you have is a challenge. Build your data visualization team with an information designer at its core, and you have an advantage that leads directly to an amazing final product.

No matter what stage you are in, there is a solution to help get you to the overall goal of showing your data truth.

If none of the ideas have helped, please call or email us to see if we can help give you your first step.

www.boostlabs.com / ali@boostlabs.com / 301.560.7901