4 Ways Data Visualization Can Help Improve Decision-Making

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Data analytics have come a long way in the last few years, allowing a wider range of users to query data and receive answers in seconds. Of course, the product of data analysis is just as important as the process. Not only has it become possible for employees outside the IT department to run ad hoc queries whenever they need, but the data visualizations they receive have become more advanced and user-friendly, too.

As Digitalist Mag writes, data visualizations today go behind static graphs. In fact, they are:


  • Interactive: Users can go beyond fixed graphs to keep exploring data insights.



  • Multidimensional: Visualization models can show relationships between variables.



  • Efficient: Graphs automatically match the data sets they’re displaying, working with data instead of against it.


Here are four ways today’s advanced data visualization can help improve decision-making.

Helps Decision Makers Grasp Insights Faster

Human beings process visual information more efficiently than any other form. Data visualization models capitalize on this, allowing users to comprehend insights at a glance.

Today’s advanced visualization tools help users grasp an immediate overview of performance and patterns within data. Rather than having to set aside chunks out of their days to pore over spreadsheets and static graphs, they can create and access interactive charts to speed up decision making without sacrificing quality.

Makes Complicated Data More Digestible

Similarly to the way interactive charts help users grasp data insights faster, they also simplify dense data sets into a more digestible format. The more straightforward and graspable the data, the less room there is for misinterpretation when it comes time to make decisions based upon it.

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Allows Users to Drill Down for Further Context

The most effective data visualizations today are interactive, “enabling users to manipulate them or drill into the data for queries and analysis.”

Static graphs offer surface-level analysis of data. But interactive charts let users keep asking questions and exploring data from different angles. This extra context tends to be helpful for decision-making because it helps users investigate data insights from every angle before drawing any conclusions.

The interactive nature of advanced data viz today allows decision-makers to keep probing data and reframing their mindsets along the way. Rather than a static chart representing both the beginning and end of a query, interactive models serve as a starting point for exploration.

In other words, good data viz can be a jumping-off point for further investigation rather than a final product. Users can carry this deeper understanding of data with them when making decisions that affect business outcomes.

Gives Everyone the Same View

A data analytics platform like ThoughtSpot powers embedded analytics, which gives users the ability to integrate data visualization into existing workflows and applications. This can mean embedding the search-driven analytics engine itself, a single chart or an entire dashboard of charts. The result? Everyone who needs access to the information at hand has the same view.

Creating this shared understanding is key for fueling decision-making when it involves more than one person — as it often does in the workplace. As one data expert writes for Forbes, establishing a shared understanding between various stakeholders can help them “achieve a consensus quickly” and “provide a starting point for discussions.” In other words, it’s an expedient way to help groups get on the same page quickly. People can simply log into the business applications and collaboration tools they already use to access interactive data visualization models — the same charts and dashboards their colleagues can access simultaneously.

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Your approach to data visualization can improve decision-making or hinder it; interactive data viz tools are a must for data-driven organizations today.


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