Data Visualization

As the name suggests, data visualization is the process by which quantitative or qualitative information is translated into visual representations (e.g. charts, graphs, maps, dashboards, etc.). These visual representations make it faster and easier for users to explore, understand, and interpret patterns, trends, relationships, anomalies, and overall performance structure. In essence, data visualization turns complex information into insightful visual stories.

Learn more about data visualization concepts here.

The most common types of data visualizations are:

• Comparison (bar chart, line chart)
• Distribution (histogram)
• Composition (pie chart, stacked bar chart)
• Relationship (scatterplot)

Each of these corresponds to an analytical question they help answer, such as “How much of the whole does this represent?” (composition).

Learn more about the various types of data visualizations here.

There are several concrete business advantages to improving your data visualization capabilities:

• Enables faster, more confident decisions via accelerated insights.
• Facilitates better alignment via shared dashboards that create a single source of truth.
• Enhances productivity via embedded analytics (like Logi Symphony) to deliver insights within apps that users already work from.
• Increases operational and financial agility via real-time discovery of patterns to act more quickly.

We recommend using the following table as a starting point for finding the right data visualization:

Goal	Visualization
Comparing values	Bar/line charts
Showing a distribution	Histograms
Showing a makeup/composition	Stacked bars, pie chart, treemaps
Showing correlation	Scatterplots

Our data analysts also suggest leaning on the side of simplicity rather than complexity to avoid overwhelming clutter. Logi Symphony and Vizlib both offer pre-built and tested chart libraries that adhere to industry best practices, so you can get started faster and more effectively.

Several characteristics define “good” data visualizations, but all work together to make it clear, accurate, and purposeful:

• Avoid distortions and misleading scales
• Prioritize context with axes, labels, and baselines
• Encourage exploration without distraction

insightsoftware data visualization tools embed these principles in our default styles and templates so you don’t have to spend as much time wrangling formatting and colors.

We recommend using color meaningfully and sparingly, such as to highlight an outlier or important data point. You should also make sure that the contrast of your chart meets accessibility standards, so users who have color blindness can still use it effectively. Lastly, sticking to distinct color palettes for categorical comparisons and sequential or diverging schemes for gradients will help visually tie elements together, and can even be combined with your brand’s colors for a more professional and seamless look.

Now that we understand data visualization and what it is, what are the tools that help modern businesses enhance their visualization practices? Data visualization tools are software solutions that facilitate the data connections, transformations, and actual rendering of visuals and dashboards. For example, our integrated stack to support data visualization includes:

• Simba drivers for enterprise-grade data connectivity
• Vizlib for advanced Qlik Sense visuals (and interactivity)
• Logi Symphony for embedded analytics across your work apps

Learn more about data visualization tools here.

A major recent trend in this space is the proliferation of white-labeled embedded analytics, using tools like Logi Symphony. This allows organizations to display charts and graphs that are branded with their own logos and colors across a variety of other systems, like their ERP or data warehouses. Full-cycle collaboration and writeback capabilities within dashboards (such as those offered by Vizlib) are also growing in popularity, as is the AI-driven automation of updates, scheduling, insights, and more.

We recommend evaluating tools based on core decision factors, such as:

• User Experience: Can non-technical users easily create dashboards using intuitive features like drag-and-drop or pre-built templates?
• Data Connectivity: Does the data visualization tool support your data sources (e.g. cloud apps, databases, files, etc.)?
• Branding/White-Label Flexibility: Can you customize the appearance of your data visualizations to match your branding?
• Performance: Does the tool slow down with larger data volumes, concurrency, and other scaling expectations?
• Collaboration: Are users able to discuss, annotate, or act within dashboards to align on insights and findings?
• Security/Governance: Does the software support security features like role-based access, SSO, audit trails, and more?

Using these core factors, it becomes easier to match your business goals to the right solution. insightsoftware platforms like Vizlib and Logi Symphony are designed to have these key components baked in from the start, instead of being treated like an afterthought or add-on.

Logi Symphony is ideal for embedded white-label data visualizations (full control over UI branding and theming) without building from scratch. Vizlib is your go-to data visualization platform to extend Qlik’s capabilities for better collaboration, writeback, planning, and more. Simba is a great choice for teams already using other data visualization tools but are looking for compatibility with MongoDB, SQL, Workday, and other data sources.

Our data visualization can work with many data sources through several approaches:

• Out-of-the-box connectors: Seamlessly integrate with all major data sources, including traditional databases, big data, flat files, and streaming web data.
• Plugin connectivity: Utilize standards-based technologies like Simba for expanded connectivity.
• Programmatic retrieval: Fetch data programmatically for custom solutions.