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Vinay Paw

Data Visualisation Director

About this Author

As a Data Visualisation Director at iProspect, Vinay is responsible for ensuring clients performance data is best visualised in order to make campaign optimisations and help drive brand performance.

From Big Data to Bar Chart: How to Pick the Right Tool

There are quite a few data visualisation tools on the market. These range from basic, i.e. where you connect to a spreadsheet and quickly create some visualisations, to full enterprise solutions that offer automated dashboards. In my opinion, a marketing dashboard is crucial for any campaign as it removes the long-standing time consuming task of weekly reporting. This frees up time for channel teams to optimise their activity. On top of this, dashboards also offer more detail which can help highlight more in-depth insights on performance. In this blog post, we'll take a look at three tools (Tableau, Datorama & Data Studio) that don't require prior coding knowledge to get an automated reporting dashboard up and running. These are good examples of tools that can be used for basic or advanced projects that also don’t require you to be a data engineer. All of these tools allow you to connect to a spreadsheet and create some visualisations in less than a day. If you are looking for a free tool that provides basic functionality, the likes of Tableau Public and Data Studio are good options. However, if your campaign calls for say an automated dashboard, you'll move away from spreadsheets and now need to consider tapping into data from platforms or a database. You can broadly split data viz into its two component parts: data and visualisation. Data deals with the ETL (extract, transform, load) process. Extract data from the data sources Transform the data into a format that will allow you to query and analyse Load the data into its final target database which you can then query in your data viz tool ETL tends to take up the bulk of project time and resource. Without a clean and structured set of data to use, visualisation becomes very limited and almost pointless. It’s important to get this part of the process correct to be able to create great dashboards. Most tools will require you to already have your data in some sort of external database for it to query when a user loads the dashboard. In fact, this is how tools such as Tableau and Data Studio work. The database is where the data model is defined and the clean data is stored for the tool to query and make visualisations. However, Datorama requires you to import your data to their database and work within models they have set up. Because of this though, it means you can do all your ETL and visualisation in one tool. The ETL process is designed to be done in the database, so Tableau and Data Studio only allow you to do basic transformations once you are in the front-end of the tool such as joins and calculations. Data Studio does go half a step forward with its connections to the Google stack (Google Analytics, AdWords, DCM, etc.), so you have the ability to bypass a database if you're only looking at Google data. Visualisation is really about how you want to represent your data in a way that provides easy and insightful analysis of otherwise unreadable and overwhelming datasets. Most tools offer the same set of charts, but their ability to customise these is where the real value lies. Tableau starts by offering suggestions on what visual to use when you select a metric. It then allows you to modify until you're happy with what you've created. Datorama takes a different tact by including the option to create custom overview widgets using HTML & CSS, and more recently, compatibility to use D3 within the tool as well. Data Studio takes another view. It focuses on styling options as well as allowing you to overlay widgets on top of each other. This is a beneficial feature when creating a highly custom feel to each dashboard. Having a top-line idea of how you’ll approach these parts will generally lead you to the tool that is best suited to your use case. These are the sorts of questions you'll need to ask: Do you have a way to pull the data you want to visualise? (Extract) Is the data clean and ready to use or does it need some manipulation? (Transform) Is this data in a database you can query? (Load) Do I need a basic or highly customised dashboard? The key point to take away is that data visualisation tools will treat the ‘data’ part of the process differently. Most of the big platforms will generally get you to the same dashboard output. However, it’s vital to have a good understanding of your data infrastructure before you pick the right tool for your project or campaign. Our dedicated experts at iProspect are here to answer any questions around how data visualisations benefit your overall strategy. 0 4 min read

As a Data Visualisation Director at iProspect, Vinay is responsible for ensuring clients performance data is best visualised in order to make campaign optimisations and help drive brand performance.

Vinay Paw

About this Author

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