In today’s business landscape, leaders face an overwhelming amount of information. Without the right tools to interpret it, navigating this data can feel like walking through a maze blindfolded.
However, it doesn't have to be this way. By employing the right strategies and visualizations, businesses can turn data into a goldmine of opportunities, revealing hidden patterns and driving meaningful change.
Static spreadsheets filled with endless rows of data make it difficult to see the big picture. Data visualization transforms complex information into accessible and actionable formats like graphs, charts, maps, and dashboards. These tools highlight variability, illuminate trends, and draw attention to outliers.
Done right, data visualization:
But achieving those outcomes is easier said than done—and it’s not just about finding the right data visualization tool. Doug explains, “Buying a tool doesn’t mean you’re data-driven. What it really comes down to is data hygiene, data governance, and data strategy.”
It’s easy to get carried away with all the bells and whistles of modern data visualization tools, but the core purpose of data visualization is to drive people to action.
To start off on the right foot, write down what you want users to do when looking at your visualization before you build anything. To stay on track, keep revisiting that goal as you build.
Tailor your visualizations to your audience's needs, knowledge level, and interests. For instance, a technical team might appreciate detailed and complex visualizations, whereas a high-level executive might prefer simplified, key insights.
You should also consider the context in which someone will use your visualization. Are you creating it for a formal report? Is it supposed to be a real-time dashboard? Maybe it’s going in a public presentation. Keep user experience top of mind as you refine your visualization.
Connecting a data visualization tool to a datasource and creating fancy heat maps is easy. What’s hard is figuring out what data to feed into a visualization tool, how to ensure its accuracy over time, and how to define performance metrics in ways that make sense across the business.
That’s where a partner like Launch can help. “If you can’t trust your data, data visualizations are essentially drawings,” says Doug. “At Launch, we help our clients set a data strategy customized to their business. Over time, this builds trust and convinces leadership to make decisions based on visualizations.”
A major benefit of data visualization is the potential for greater data democratization. But not everyone needs to be—nor should be—seeing and acting on the same data. Data visualization presents compliance, privacy, and security risks that must be addressed through proper data governance.
There are clever ways to restrict permissions without hampering productivity. If six managers have different levels of authorization, for example, it doesn’t mean you need to create six different dashboards.
With thoughtful data governance, you’d have one dashboard with six different sets of permissions. That way, you’re maintaining security standards without slowing the whole system down.
At Launch, we do this internally. One dashboard represents all sectors, but each sector leader only sees what they need to see to assess their business. Executives, on the other hand, have broader access and can view overall business performance.
Try to match your visualization to the data you are presenting and your goal for end users. In general, use:
Try to eliminate unnecessary elements that do not add value to the visualization, such as excessive gridlines, additional background colors, and overly complex legends. Hone in on the most important information that you want your audience to see as soon as they see your visualization.
Creating enterprise-wide templates is a good way to simplify your designs across the board. Launch’s consulting teams spend a great deal of time standardizing color palettes, schemas, and reporting notifications for their clients because it boosts engagement.
And they also coach clients on design best practices, such as the Z Theorem—in North America, we read everything from left to right, so the most important items should be in the upper left, followed by the upper right, lower left, and then lower right. Little things like this make a big difference in usability.
While visuals should be relatively easy to digest at first glance, there are some details you need to clarify for your audience, such as:
As Doug puts it, “‘Revenue’ in one corner of the business may have a very different definition in another. Making definitions and calculations transparent makes visualizations more usable.”
For more self-serve or interactive dashboards, consider offering guidance on how to use available features effectively.
Your visualization may not be perfect the first time around, and that’s okay. Taking a build-and-iterate approach helps you gather feedback and reminds you to return to the action you’re trying to drive at every step.
At Launch, we typically do mockups first and use a small dataset. That way, we can assess what’s working and what’s not and have a good setup before moving it to a production environment with all the data flowing through it.
Before working with Launch, a large litigation consulting and support company was struggling with poor data quality, skyrocketing data architecture costs, and highly manual processes. With Launch’s help, the team designed and built a secure, optimized data pipeline that would automate analytics and dashboards that catered to both executive and tactical needs.
First, they implemented a Snowflake data architecture with robust governance best practices. They then weaved in an efficiency-optimized, self-service data model using dbt, and built a suite of actionable and intuitive Sigma Computing dashboards. By taking an iterative approach to building the pipeline and key data visuals, Launch was able to:
One of Launch’s largest software clients was having trouble deriving meaningful insights and analytics out of their substantial data. They were suffering from severe data sprawl, inconsistencies, and high storage costs.
To overcome these challenges, Launch centralized the company’s ETL process and data analysis in Microsoft Fabric and then built powerful, accurate, real-time dashboards in Power BI.
These dashboards:
Team leads used these visuals to measure their progress, predict how the market will change, drive revenue, and work more efficiently toward their future goals.
A national billion-dollar gas and electric utility company faced critical safety concerns due to falling power lines, threatening wildfires and essential services, and reached out to Launch for help. Launch saw this challenge as an excellent opportunity to centralize data management and enhance data usability via Palantir Foundry.
The team got to work integrating the client’s existing data with geospatial analytics, allowing the utility's personnel to visualize and interact with data through comprehensive maps. Data visuals enabled them to:
And, ultimately, these applications helped the company develop a plan to underground 10,000 miles of power lines by 2030 while ensuring the resilience of power supply to critical services.
Leveraging data visualization effectively can transform raw data into actionable insights, driving informed decision-making and strategic growth. But you can’t unlock these benefits without streamlined, accurate data.
In today’s business landscape, leaders face an overwhelming amount of information. Without the right tools to interpret it, navigating this data can feel like walking through a maze blindfolded.
However, it doesn't have to be this way. By employing the right strategies and visualizations, businesses can turn data into a goldmine of opportunities, revealing hidden patterns and driving meaningful change.
Static spreadsheets filled with endless rows of data make it difficult to see the big picture. Data visualization transforms complex information into accessible and actionable formats like graphs, charts, maps, and dashboards. These tools highlight variability, illuminate trends, and draw attention to outliers.
Done right, data visualization:
But achieving those outcomes is easier said than done—and it’s not just about finding the right data visualization tool. Doug explains, “Buying a tool doesn’t mean you’re data-driven. What it really comes down to is data hygiene, data governance, and data strategy.”
It’s easy to get carried away with all the bells and whistles of modern data visualization tools, but the core purpose of data visualization is to drive people to action.
To start off on the right foot, write down what you want users to do when looking at your visualization before you build anything. To stay on track, keep revisiting that goal as you build.
Tailor your visualizations to your audience's needs, knowledge level, and interests. For instance, a technical team might appreciate detailed and complex visualizations, whereas a high-level executive might prefer simplified, key insights.
You should also consider the context in which someone will use your visualization. Are you creating it for a formal report? Is it supposed to be a real-time dashboard? Maybe it’s going in a public presentation. Keep user experience top of mind as you refine your visualization.
Connecting a data visualization tool to a datasource and creating fancy heat maps is easy. What’s hard is figuring out what data to feed into a visualization tool, how to ensure its accuracy over time, and how to define performance metrics in ways that make sense across the business.
That’s where a partner like Launch can help. “If you can’t trust your data, data visualizations are essentially drawings,” says Doug. “At Launch, we help our clients set a data strategy customized to their business. Over time, this builds trust and convinces leadership to make decisions based on visualizations.”
A major benefit of data visualization is the potential for greater data democratization. But not everyone needs to be—nor should be—seeing and acting on the same data. Data visualization presents compliance, privacy, and security risks that must be addressed through proper data governance.
There are clever ways to restrict permissions without hampering productivity. If six managers have different levels of authorization, for example, it doesn’t mean you need to create six different dashboards.
With thoughtful data governance, you’d have one dashboard with six different sets of permissions. That way, you’re maintaining security standards without slowing the whole system down.
At Launch, we do this internally. One dashboard represents all sectors, but each sector leader only sees what they need to see to assess their business. Executives, on the other hand, have broader access and can view overall business performance.
Try to match your visualization to the data you are presenting and your goal for end users. In general, use:
Try to eliminate unnecessary elements that do not add value to the visualization, such as excessive gridlines, additional background colors, and overly complex legends. Hone in on the most important information that you want your audience to see as soon as they see your visualization.
Creating enterprise-wide templates is a good way to simplify your designs across the board. Launch’s consulting teams spend a great deal of time standardizing color palettes, schemas, and reporting notifications for their clients because it boosts engagement.
And they also coach clients on design best practices, such as the Z Theorem—in North America, we read everything from left to right, so the most important items should be in the upper left, followed by the upper right, lower left, and then lower right. Little things like this make a big difference in usability.
While visuals should be relatively easy to digest at first glance, there are some details you need to clarify for your audience, such as:
As Doug puts it, “‘Revenue’ in one corner of the business may have a very different definition in another. Making definitions and calculations transparent makes visualizations more usable.”
For more self-serve or interactive dashboards, consider offering guidance on how to use available features effectively.
Your visualization may not be perfect the first time around, and that’s okay. Taking a build-and-iterate approach helps you gather feedback and reminds you to return to the action you’re trying to drive at every step.
At Launch, we typically do mockups first and use a small dataset. That way, we can assess what’s working and what’s not and have a good setup before moving it to a production environment with all the data flowing through it.
Before working with Launch, a large litigation consulting and support company was struggling with poor data quality, skyrocketing data architecture costs, and highly manual processes. With Launch’s help, the team designed and built a secure, optimized data pipeline that would automate analytics and dashboards that catered to both executive and tactical needs.
First, they implemented a Snowflake data architecture with robust governance best practices. They then weaved in an efficiency-optimized, self-service data model using dbt, and built a suite of actionable and intuitive Sigma Computing dashboards. By taking an iterative approach to building the pipeline and key data visuals, Launch was able to:
One of Launch’s largest software clients was having trouble deriving meaningful insights and analytics out of their substantial data. They were suffering from severe data sprawl, inconsistencies, and high storage costs.
To overcome these challenges, Launch centralized the company’s ETL process and data analysis in Microsoft Fabric and then built powerful, accurate, real-time dashboards in Power BI.
These dashboards:
Team leads used these visuals to measure their progress, predict how the market will change, drive revenue, and work more efficiently toward their future goals.
A national billion-dollar gas and electric utility company faced critical safety concerns due to falling power lines, threatening wildfires and essential services, and reached out to Launch for help. Launch saw this challenge as an excellent opportunity to centralize data management and enhance data usability via Palantir Foundry.
The team got to work integrating the client’s existing data with geospatial analytics, allowing the utility's personnel to visualize and interact with data through comprehensive maps. Data visuals enabled them to:
And, ultimately, these applications helped the company develop a plan to underground 10,000 miles of power lines by 2030 while ensuring the resilience of power supply to critical services.
Leveraging data visualization effectively can transform raw data into actionable insights, driving informed decision-making and strategic growth. But you can’t unlock these benefits without streamlined, accurate data.