4 Minute Read

Data Visualisation Tools

Businesses and organisations typically have many streams of data. For these streams to be usable they need to be presented in a form that’s understandable by those who need it to make decisions. Data viz tools transform “raw” data into graphs, charts, tables, lists and maps. They will also allow for reports to be created which can include narrative commentary supplied by data analysts.

Data visualisation is a vital element of all data management activities. When used right, the best data visualisation software can tell the story behind your data and provide a single source of truth to your business. It can enable informed, rapid data-driven decision-making and allow businesses to become more agile, responsive to emerging trends and be more in tune with their customers.


What is a data visualisation tool?

Data visualisation tools are software tools (often with a browser interface) that can import data, merge and mix data streams, and present the required views of data at the right level of detail for the intended user.

Businesses and organisations typically have many streams of data. For these streams to be usable they need to be presented in a form that can be understood by those who need it to make decisions.

Data visualisation tools transform “raw” data into graphs, charts, tables, lists, maps and more. They also allow for reports to be created which can include narrative commentary supplied by data analysts.

Key requirements of data visualisation tools are typically:

  • Ease-of-use
  • Speed of creating new reports
  • Ability to handle big data sets easily
  • A user interface that’s attractive and intuitive

Alongside these factors, total cost of ownership is going to be a key factor in the decision to adopt a particular tool. Different licencing models are in play, including simple subscriptions, per-seat models and feature-based models.

Reports should be easy to download and print, but data visualisation tools must also take advantage of the interactivity available on the web to provide users with the ability to easily navigate the reports, drill down from top-level data into detail and get the best user experience on the widest range of desktops and even mobiles.

Data visualisation tools are in fact much more than the user interface and presentation part. They must support the data connectors necessary to connect to a wide range of data sources, and preferably allow third-party providers to develop their own data connectors, if they don’t already exist.


Who uses data visualisation tools?

There are many types of users of data visualisation tools. The most obvious is management teams who need data that’s continuously up to date, in order to make timely decisions.

There are literally hundreds of data visualisation tools on the market today and the landscape is continually changing. Let’s look at four popular tools that are dominating the marketplace: Power BI from Microsoft, Tableau, Looker and QlikSense.


Microsoft Power BI

Microsoft Power BI (Business Information) is a strong contender for best-of-breed data visualisation tool. Microsoft pitches its product as a way of consolidating multiple streams of data and moving away from “raw” data views such as Excel, SQL Server, Access, and text-based formats, such as XML, and jSON. Like most visualisation tools, Power BI can be configured to import data from unstructured sources, such as emails and PDFs, as well as tabular or relational data.

Data can be presented on desktops, on the web (secured for access only by authorised users if necessary) and on mobiles.

A key feature, which is emerging in many visualisation tools is the ability for users to enter a natural language query into a search box to ask questions in their native language to interrogate the underlying data. For example:

  • Which sales team had the highest revenue last quarter?
  • Show me the top 10 products by sales this year
  • Show me sales by category as pie chart

As you can see these types of queries will return quite different results, intelligently and in real time. This feature is called Power BI Q&A and also supports autocomplete to guess the data sets and categories you are interested in.

Power BI also supports Data Analysis Expressions (DAX). Similar in concept to Excel’s formulas, DAX allows users to query data using expressions, maths and string expressions.

Visualisation types include the full range of traditional charts, including pie charts, column charts, stacked column charts, tables, lists, area charts, scatter charts, geo maps, and line charts of all types.



Tableau is another data visualisation tool that can create beautiful dashboards and visualisations. It supports numerous data sources including both structured and unstructured data, drill-down, the capability to be programmed using popular languages such as Python and R, and has some unique features too.

Like many of the other tools, Tableau has a range of ways to connect your data including Amazon Redshift, Google Analytics, Excel, Azure databases, Databricks, MySQL and many other data sources. Databases can be cross joined so they don’t necessarily have to be merged together in a pre-visualisation operation, which can slow down the workflow.

Tableau dashboards can be viewed on mobiles and tablets, as well as desktops. It supports a very wide range of mathematical and statistical functions. And of course, it supports all the expected chart types including pie chart and bar charts, as well as histograms, Gantt charts, treemaps, geomaps and more.

“A great data visualisation tool will help management and teams understand the backstory behind their data
Ipsos Jarmany


Qlik Sense

Business Intelligence platform, Qlik Sense is another choice for understanding and visualising your data.

The Qlik angle is to close the gap between data (what you know) and action (what you should do about it) by providing ways to visualise data streams that give informative, actionable insights.

Qlik doesn’t force users to move data to the cloud, which can be difficult to do with legacy systems in play. But it also plays nicely with cloud data platforms including Amazon, Azure, Google Big Query, Snowflake, Databricks etc.

Qlik’s product suite offers more than just visualisation – it also includes data replication tools, automation, data management and more.

A unique feature of Qlik is the “associative engine”, which creates an internal catalogue of the relationships between your data points to find patterns and insights that you may not even have thought about. Using a visual interface, users (who could be non-technical) can explore data sets visually. Whereas, traditional data querying is done via query languages such as SQL (Structured Query Language) which can only filter and show the data that you specify in advance.

Qlik also has a mobile app, making it easy to use by team members who work in the field.



Looker bills itself as “Data at your moment of need” and, as you might expect from a Google product, there is a focus on speed in this visualisation tool.

Looker has no desktop app (it’s all browser-based). It allows you to create amazing visualisation of data, features strong security and sharing capabilities, allows you to schedule reports to be created and disseminated amongst team members, set up alerts when data points meet specified thresholds, and much more.

Looker might not be the right choice if your data stack is primarily Microsoft (in which case you should probably consider Power BI) but if you are more platform-agnostic Looker could be a good choice.

Like other tools, Google features powerful AI which can interpret English-language queries, avoiding the need for the data-consumers within your business to know database query languages such as SQL.

Looker has out-of-the-box integrations with many SaaS packages commonly used by businesses today, including Salesforce, Confluence, and SharePoint.


Need Data Visualisation Support?

To make sure your data is telling you the whole story about what’s going on in your organisation, look to Ipsos Jarmany.

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