Data is everywhere (and it always has been). Buying habits have always existed, as have demographics and weather patterns. Though they’ve been measured and tracked effectively for the last 50 years or so, for much of that time, only very large corporations or entities could afford it. In the last few years, however, the age of data democratization has arrived and that once limited data is suddenly available to companies of all sizes. The democratization of data has leveled the playing field. With vast amounts of information readily available at the push of a button, this movement has ushered in a new kind of business. The Impact of Big Data Democratization The Internet has provided an enormous “data warehouse” that reaches across all sectors: from healthcare to education, from government to technology and from business to recreation — absolutely every facet of life has been impacted by the widespread availability of data. Healthcare – Data democratization will continue to facilitate greater sharing and collaboration between researchers, scientists and medical professionals. The sharing of discoveries can lead other teams to build on those successes and work toward the next major breakthrough. No longer confined to the walls of their lab — or the pages of a paper medical journal that might or might not be read — the new interconnectivity in medicine, science and healthcare is a perfect example of the democratization of information. Education – Data democratization can give more people access to high-quality and affordable education. Government – By focusing on data availability as opposed to websites, data democratization can lead to a more transparent government. Personal Use – The storage of vital personal information also benefits from a cloud-based approach (the heart of data democratization). For example, In the event of a fire, natural disaster, sudden death of a spouse or other tragedy, people are able to locate important documents much more quickly, making it much easier to work with insurance companies. Those are just a few examples – ultimately businesses and individuals can use the increased availability of data to make better-informed decisions and understand the world around them. Putting Data Democracy to Work A company looking to take advantage of the benefits that come from data democratization needs to start with preparation. This preparation takes the form of both technical changes and perspective changes – getting your personnel on-board with a new way of sharing and accessing data is key to making democratized data a company-wide tool. Connect Your Public and Private Data – Analysts cannot effectively create plans and designs without the full spectrum of information. By ensuring that they have access to both public and private information (and understand how they’re connected), you ensure that they can draw the right conclusions from the data you’ve collected. Use Information Designers and Visualizations – The wealth of data that will become available means that it will also be difficult to sort through. Data visualizations (created by information designers) will make that information easier to inspect and draw conclusions from. Prioritize The Impact of Your Data – Your data visualizations are likely to show a large number of relationships and dependencies between your customers and company activities. Understanding and teaching your team about which of those are actually meaningful and important is key to avoiding “Analysis Paralysis.” Knowledge is power. We have entered into an era where more knowledge is available to companies and individuals than ever before. Putting that data to good use takes some practice and preparation (and a few good tools), but everyone now has the power to use information that used to belong to a very few – and that’s why it’s called Democracy. If you’re ready to capitalize on data democratization but are unsure on where to get started, contact us to learn how we can help you put your data to work.
A slick chart, an interactive data-exploration interface 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: Is the data complete? Is the data valid? 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 visualization on a collection of survey data regarding movie-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 accommodate for “respondent fatigue”, the likely cause of the incompletions. Insight into Data #2: Is the data valid? The importance of visualization among data validation 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 dataset shows that there are more males in Alaska than Florida. This is a red flag because, even with the gender ratio differences, Florida’s larger population means that it should have a higher total number of males. A well-designed, preliminary visualization can give insight 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 process. 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 customer 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 information 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. To find out what your data has to say to you, contact Boost Labs to learn about creating a visualization to give you the insights your project needs to succeed.
Data visualizations (like charts, graphs, infographics, and more) give businesses a valuable way to communicate important information at a glance, but what if your raw data is text-based? If you want a stunning visualization format to highlight important textual data points, using a word cloud can make dull data sizzle and immediately convey crucial information. What are Word Clouds? Word clouds (also known as text clouds or tag clouds) work in a simple way: the more a specific word appears in a source of textual data (such as a speech, blog post, or database), the bigger and bolder it appears in the word cloud. Here’s an example from USA Today using U.S. President Barack Obama’s State of the Union Speech 2012: As you can see, words like “American,” “jobs,” “energy” and “every” stand out since they were used more frequently in the original text. Now, compare that to the 2014 State of the Union address: You can easily see the similarities and differences between the two speeches at a glance. “America” and “Americans” are still major words, but “help,” “work,” and “new” are more prominent than in 2012. Using word clouds isn’t exclusively for creating presidential eye candy. Keep reading to discover how word clouds can benefit your business. Where Word Clouds Excel for Businesses In the right setting, word cloud visualizations are a powerful tool. Here are a few instances when word clouds excel: Finding customer pain points — and opportunities to connect. Do you collect feedback from your customers? (You should!) Analyzing your customer feedback can allow you to see what your customers like most about your business and what they like least. Pain points (such as “wait time,” “price,” or “convenience”) are very easy to identify with text clouds. Understanding how your employees feel about your company. Text cloud visualization can turn employee feedback from a pile of information you’ll read through later to an immediately valuable company feedback that positively drives company culture. Identifying new SEO terms to target. In addition to normal keyword research techniques, using a word cloud may make you aware of potential keywords to target that your site content already uses. When Word Clouds Don’t Work As mentioned, word clouds aren’t perfect for every situation. You wouldn’t use a pie chart to show company revenue growth over time, and you shouldn’t use word clouds for every application, either. Here’s when you want to avoid using a word cloud. When your data isn’t optimized for context. Simply dumping text into a word cloud generator isn’t going to give you the deep insights you want. Instead, an optimized data set (one handled by an experienced data analysis team) will give you accurate insights. When another visualization method would work better. It’s easy to think “Word Clouds are neat!” and overuse them — even when a different visualization should be used instead. You need to make sure you understand the right use case for a word cloud visualization. There are many other instances when a different visualization should be used over word clouds. (Feel free to contact one of our data analysts to learn more.) How to Make a Word Cloud As shown by their increasing popularity, making a word cloud for your website or business isn’t difficult, but there are some important considerations that need to be made so your visualization is more than just eye candy. First, you’ll want to get a valuable, text-based data set. Having an experienced analyst compile this helps to ensure your source data is actually usable. The next step is to run your data through a word cloud tool. Many businesses like and use Wordle, but there are many others you can try, too (such as Tagxedo and WordItOut). The downside to these free tools is many sites, including Wordle, automatically add all text clouds to their portfolio. This means any site visitor can see it, potentially undermining your marketing efforts. (Check your individual tool’s policies to see if your word cloud will be used in this way.) Exporting your word cloud from a free tool might take some work. Sometimes, if download as an image or PDF isn’t available, you’ll be forced to take a screenshot – a less-than-elegant solution. Here’s what to do if you really want your word cloud to be noticed: consider designing your word cloud from scratch! Does this sound like a lot for you to handle in-house? Not all companies have (or need) an in-house data analyst. Our experienced team at Boost Labs has experience working with enterprise clients such as the U.S. Census Bureau, small businesses like individual websites, and everything in-between. Contact us today for a personalized consultation.