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Data analytics as a Management Trainee

In its raw form, data is not information but processed in the right way it can be turned into information. Amanda, Kejsi and Bjarte share their thoughts on data analytics as a business-critical tool.


Several of this year’s Management Trainees have worked on projects related to data analytics. Amanda, Kejsi, and Bjarte share their thoughts on data analytics as a business-critical tool.

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Why data analytics?


Kejsi Gjordeni created a business-critical Tableau dashboard for Visma Enterprise AB in her second Management Trainee project.

During this trainee year, several of our Management Trainees have had projects related to data analytics. So how come these kinds of projects have become popular and requested both from Management Trainees, but also from different project owners around in Visma? Amanda Lange, Kejsi Gjordeni, and Bjarte Espedokken have each had particularly data-driven projects and realised the potential the information derived from data brings for change.

Being a large enterprise, Visma has access to lots of data related to our products, services, and customers. However, despite the great accessibility most of the data is not used in an efficient way to enable and facilitate informed and smart decision making. It is often very tiresome to comprehend the information and derive any valuable insights. Therefore, data analytics has become quite a hot topic in Visma nowadays.

Undertaking a data analytics project can be relatively challenging for employees who already have their daily tasks to work with. As a Management Trainee, when you have two months to spend dedicated to a certain topic and project, it can be seen as the perfect time to learn how to use different data analytics tools and ensure a valuable delivery that gives a better understanding of the existing data.

After having to experience their fair share of data analytics projects, Amanda, Kejsi, and Bjarte all agree that it can be challenging to get to know a new Visma Business Unit, grasp the goal of the project, get access to data, prepare the data and finally visualising the data.

The key to success seems to be to spend a good time on the preliminary work, so that you have use cases, documentation, and can make informed decisions. Then the actual data analytics tools can help you build the solution very quickly. During the projects, they have utilised some great tools that have made this process easy.

Also read: The Management Trainees of 2019 are here!

How? What?


Management Trainee Amanda Lange spent a considerable amount of time working with Tableau and Alteryx in her fourth project for the CTO department.

However, in many cases, different departments have their own way of structuring data. Someone likes SQL databases, someone Google Bigquery, while others like maintaining information in a Google spreadsheet.

There might be several good reasons for using each of these different types of structuring and storing data. However, when you as a data analyst would like to analyse data across different data sources, it might require a lot of preprocessing.

By using Alteryx, we can easily format and aggregate the data from different data sources, before joining. We then end up with a new data source containing precisely the information we are interested in analysing. This enables new analyses, as we can look for correlations between data we previously have not looked at simultaneously.

Also, building a new data source based on aggregated data from the different sources improves the performance of reports. This comes from the fact that we don’t process more data than we need when we analyse the data and build reports in data visualisation tools like Tableau. 

One example of how Amanda used Alteryx was to download data from a REST API. The database was protected, so she could not access it directly, but instead through an API. Alteryx enabled her to download the data without having to write a custom script of any kind.  Alteryx’s tools did most of the work and she could later combine the downloaded data with data from Google Sheets. In addition, she was able to schedule an update every week, so that the data would always be up to date. 

While Alteryx is great for fetching, joining, and cleaning data, Tableau is a great tool for visualising it. In Tableau, you can create graphs, geographical overviews, and also allow for the end-user to customise their own view by using filters and search tools. 

Read more: One month as a Management Trainee.

Outcome, recommendations


Bjarte Espedokken mapped the Visma product portfolio as part of his third trainee project and created a dashboard that is regularly visited by employees of the entire Visma group.

The great thing about data analytics is that it yields immediate results. When a Tableau report is finished, decision-makers can utilise it to make strategic, data-driven decisions. In addition, the data sources that are created in Alteryx can be reused, so that someone else in Visma can create a new report specifically adapted to their needs. 

Once a report is available to anyone who has “contributed” with data, it also incentivises them to update the data and correct any errors, as they themselves want to be represented correctly in the report.

When there is a live connection to a data source that is automatically updated, decision-makers can also be sure that they are working with up to date data.

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