By Clarity Insights,
Clarity Insights is a strategic partner to the nation's leading data-driven brands.


At Clarity Insights, our clients often ask us what the best data visualization tools are. It’s probably a question you’ve asked at one point or another, and it’s a good one. There are so many data visualization options available--and the number is growing all the time--that it can be overwhelming to sort through them.


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As with any tool selection in your data architecture, there isn’t a “one size fits all” option, but you can figure out how to choose the right data visualization tools by answering a few questions. Take a minute to answer the following questions:

1. What type of questions are your business users asking?

Do you have operational reporting needs?  Are you trying to find trends?  Do you even know what the questions are?  How much data are you dealing with (terabytes of transactional data or gigabytes of aggregate data)?

2. What is the skill level of your business users?

Are your users proficient in Excel?  Can they construct their own SQL statements?  Do they create their own reports in another reporting tool?  

3. What technical resources do you have ready access to?

Do you have a separate business analyst team?  How big is your user base?  What flavor of database do you have (Relational databases or Big Data)?  Do you have legacy applications that you need to integrate into your new solution?

4. How much data do you have and in what condition is it?

Are you going to be reporting on terabytes of transactional data, or do you have data aggregated to a reporting layer?  Does your data need to go through a transformational layer before getting to the reporting users?  Do you have many different data source types (i.e. flat files, databases, web services)?

The answers to these questions should drive you toward a single tool, or at least help you narrow the field. Common scenarios we see coming out of these initial answers include:

Financial Data Wranglers Our business users need to distribute financial statements, but they also need to discover what anomalies are causing profit margins to change.  

    • Possible solution: With PowerBI you can incorporate your current report generation in SSRS or Excel as an underlying source to power your analysis.  Your users will be happy because their knowledge transfers easily over to the new tool and your report consumers will be happy as they will quickly be able to slice and dice pre-calculated KPIs.

Variety of Users We will have some users that need visual KPIs each morning, but we also have a significant user base that will want to create their own reports.

    • Possible solution: Tableau has a great looking visual set that can produce quick KPIs with low technical overhead through their extract function.  With a gentle learning curve and a large user base, you can quickly get your team up to speed in building their own analysis.

Deep Divers Our primary business users will also act as our business analysts.  However, the data that is being analyzed is of a significant size (multiple terabytes) and contains multiple source types.  These users are tasked with answering questions that require extensive analysis to create real-time reports.

    • Possible solution: Such a wide approach to data analysis needs a gentle learning curve that is also extremely flexible; Looker is a great example of this solution as it is designed to handle large amounts of data and includes a robust data modeling tool that can quickly incorporate new data sources as they become available.

It’s important to consider other factors as you choose the right data visualization tool, like:

  1. Is the tool going to be installed on a local server or are you going to use a cloud solution? For example, AWS or Azure?
  2. Are you going to be incorporating legacy solutions that will need custom code bridges? Does it make sense to use Amazon Lambda or Azure Functions to serve as that “serverless” bridge?
  3. Will your customers be accessing the data remotely?  Can you use a true cloud infrastructure like Tableau Online?
  4. What kind of skills does your team have?  Do you have full time JavaScript developers? If you do and desire a fully customizable experience, D3 might be of interest.

Choosing the right data visualization tool means balancing analyst needs and technical requirements, determining training schedules and determining whether you need to add components to your current technical architecture to accommodate all your business needs. Sometimes you may even find that your needs compete with each other or seem to indicate opposing tools are tied for first. Turn to Clarity’s expert data visualization consultants to prioritize strengths and make the right decision for your business. Visit our Data Visualization page for more information on how Clarity is the right fit for you.

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