How To Pick The Right Data Visualization Tool

Cache Merrill -

So many data visualization tools are available these days, and this number will only increase. Picking the right one from all these various options is not a simple thing, and it can be overwhelming. You need to find the best tool for presenting your business, and there is no tool that will fall under the category “one size fits all.”

Though the task might seem tedious, you can make it easier by identifying the right data visualization tool by analyzing and answering the following questions.

Question No 1: What Kind of Questions Do Your Business Users Ask?

Do you have any operational reporting requirements? Are you seeking to find trends? Do you know how much data you are dealing with? Is it going to be terabytes of data that is transactional or gigabytes of data that is aggregate? Do your business users have more questions than those that are listed?

Question 2: What is the Skillset of Your Business Users?

Are the business users proficient in using Excel? Do they have the ability to construct their SQL statements? Can the business users create their reports when they are using another reporting tool?

Question 3: What Are Some of the Technical Resources They Have Access to?

Are you maintaining a business analyst team separately? How big is your user base? Do you use any legacy applications and do you want to integrate them into the new solution? What flavor of database do you own (Relational database or Big Data)?

Question 4: How Much Data Do You Have in Your Possession and What Is its Condition?

Are you planning to report on terabytes of transactional data or are you planning to aggregate the data into a reporting layer? Do you want your data to pass through a transformational layer right before it reaches the reporting users? How many types of data sources do you have (i.e., flat files, web services, and databases)?

The answers that you find for these questions can guide you to a single tool. In some cases, these answers will help you to narrow down the options. Some of the common scenarios that come from these initial answers are as follows.

Common Scenarios

Financial Data Wranglers: These are for businesses with users who are required to distribute financial statements. They also need to find out the anomalies that are affecting the profit margins.

Possible Solution: Using the PowerBI, they can integrate their current reports generation in Excel or SSRS. When they make this their underlying source, they can power up the analysis. This action will also make the users happy mainly because they can transfer their knowledge with ease to the new tool. Their report consumers will be glad as well because they can quickly slice and dice the pre-calculated KPIs.

Variety of Users: Some users require visual KPIs every day in the morning. But, we also have a significant user base who are willing to put in the effort to create their reports.

Possible Solution: Tableau is one tool that has a tremendous and beautiful looking visual set that they can use to create quick KPIs. And the best part is that they can do this with low technical overhead using its extract function. Teams can quickly learn how to use this tool and build up their analysis.

Deep Divers: These are the companies where the primary business users also act as business analysts. The data that they want to analyze is of significant size (multiple terabytes) which also includes various source types. These users also have the task of answering numerous questions using extensive analysis in order to create real-time reports.

Possible Solution: When they have such a comprehensive approach to data, they might require a tool that is exceedingly flexible. Looker is one great tool that is the perfect solution. It has a design that can help them in handling a substantial amount of the data. The best part is that it also comprises a robust modeling tool which can assist in quickly incorporating new data sources when they are available.

Other Factors You Should Consider

There are several other factors that you may need to consider when picking a data visualization tool. They are as follows:

  1. Do you want the tool to be installed on a local server or do you plan to use a cloud-based solution? For example AWS or Azure?
  2. Are you planning to integrate legacy solutions that might require custom code bridges? Do you think it makes sense to use Amazon Lambda or Azure functions which might act as “serverless” bridge?
  3. Will your customers access the information or data remotely? Are you planning to use a real cloud infrastructure such as Tableau Online?
  4. What type of skill set does your team have? Are you employing full-time JavaScript developers in your group? If you wish to have a customizable experience, D3 will be of interest to you.

Picking the right data visualization tool requires you to balance both the analytical and technical needs. You should determine not only the training schedules but also consider adding new components to the current technical architecture if required. There might be times when it feels like your needs are competing with each other, but with careful consideration, you can pick the right tool.