Digital data lies behind almost every big business decision. It drives the global economy, becoming one of the most sought-after commodities—as just one example, it pays for all those free apps and other online goodies available to us.
The amount of data being collected is currently doubling every two years, which presents new challenges of its own. If you’ve ever tried to make sense out of a spreadsheet with thousands of rows and columns, then you already know it’s practically a lost cause.
This overabundance of information is giving rise to a new era of data analytics and the need for data visualization as a way to turn information into intelligence.
What is data visualization?
Data visualization is the graphical representation of information that enables us to grasp and better understand what we’re seeing. We’re far more capable of grasping information in graphs and charts than in the form of spreadsheets and databases. Because our eyes are drawn to shapes and colors, turning plain text and numbers into visuals grabs our attention and leads us down the path of greater understanding. Detecting trends, consistent patterns and outliers becomes far easier.
Yet the process involves a lot more than simply making information aesthetically pleasing. For example, data visualization is often confused with infographics, but there are differences.
- Infographics are simply a presentation tool for showcasing static information by presenting it in a visually pleasing and easy-to-follow form. They’re best used to communicate important highlights contained within general information.
- Data visualization, by comparison, is typically dynamic and often interactive, with the charts being regularly updated, even in real time. This way, analysts can delve deeper into the data sets by creating their own filters, which allows them to make their own comparisons and draw their own conclusions.
Data visualization trends
Data visualization trends have been tracking the rapid expansion of data sets. The raw processing power required to analyze and visualize data sets running into the gigabytes or even terabytes is enormous. That’s why many modern data analytics tools are cloud-based, with the computing power coming from cutting-edge data centers rather than local machines. This boosts performance while reducing local hardware requirements and costs.
Another trend is data visualization for unstructured data. While data visualization is most often associated with structured data captured in databases and data warehouses, unstructured data contains information that has been more difficult to measure. We could view structured data as the what and unstructured data as the why.
Unstructured data can be in any number of formats—audio, images, text, video and interactive content—created by any individual, captured in any number of places and communicating more qualitative information like customer sentiment and competitor standings in the marketplace.
As data visualization tools become more sophisticated, they’re getting better at cutting out the huge amount of irrelevant data found in many sets. They’re starting to follow the less-is-more principle to make data analytics accessible to a wider audience. After all, information-driven decision-making isn’t limited to qualified data analysts. This democratization of data means anybody can take part to communicate and share all kinds of information, structured and unstructured, with any audience, knowledgeable or novice.
Data visualization tools
To help you prepare for the challenges of big data, we’ve compiled a list of data visualization tools and resources for a number of different users and needs:
Canva Graph Maker lets users create a custom chart of diagram in minutes. It features over 20 professional templates, which you can feed your data into and create graphs for adding to presentations and infographics. The tool is designed with ease of use in mind with drag-and-drop functionality and extensive customization options.
Canva’s solution is free to use, with the option to pay for extended features and styles. Most data can be pasted directly from spreadsheets, rather than entered manually.
Tableau, acquired by Salesforce in June 2019, is a sophisticated yet user-friendly visual analytics and business intelligence platform designed for use by analysts, teams and organizations. There’s a limited free public version available, while higher-end offerings range from $35 to $70 per user per month. Tableau also features an API for embedding analytics with your own products and applications.
Tableau offers a highly flexible solution with extensive customization opportunities that aren’t difficult to use. It also provides full web and mobile functionality, and its access and security controls make it a suitable choice for use in a huge variety of enterprise environments.
Google Data Studio provides an interactive web-based dashboard combined with automated reports designed to empower smarter business decision-making. It lets users import data from more than 150 other systems ranging from spreadsheets to SQL databases.
Sisense offers an agile solution with the full range of data visualization capabilities. Users can create customized dashboards and export data in a wide range of formats. It’s a cloud-native app, though it also provides support for on-premises deployments.
Zoho Analytics features KPI widgets, tabular views and pivot tables for generating reports that lead to smarter decision making. It also offers enterprise-grade data security and integration with third-party systems and applications. There’s a free trial available too.
QlikView is a data analytics platform featuring embedded analytics and an AI-powered engine for quickly discovering new opportunities and trends. An extensively customizable solution, it can be adapted for use in virtually any department on any device.
Plotly is a cloud-based data visualization solution featuring a colorful design, web-based report templates and highly customizable dashboards. With open-source code, developers can also create and modify scripts to integrate into their own projects.
Microsoft Power BI is an industry leader in data analytics and an extensive suite of analytics tools that blends seamlessly with Microsoft Dynamics CRM, Office 365 and a raft of third-party solutions.
Kibana touts its “Elastic Stack” feature, which allows users to observe data from different sources for a more comprehensive report. This makes it possible to quickly identify discrepancies and make relationships between different data sets.
Stratifyd is an AI-powered platform making inroads into visualization of unstructured data. The result of government-funded research on how artificial intelligence could be used to ingest, analyze and visualize unstructured data, the company positions itself as a tool for analyzing and visualizing customer feedback.
Drawing information from a rapidly increasing portfolio of systems and devices ranging from website analytics to automated financial reports can be both empowering and debilitating. That’s why data visualization will continue to play an important role in making sense of all that structured and unstructured data.