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Valentina Perezalonso
Valentina Perezalonso
Content Marketing Manager
14 Oct, 2021 · 4 min read

Sharpist: From data-keen to data-driven

How Y42 helped Sharpist reduce engineering time and optimize their data analytics process across the company.


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Berlin, Germany

  • Y42 allowed Sharpist to save on at least 1 additional data engineer.

  • Y42 saved Sharpist half of the working time when it comes to the engineering, modeling, and visualization process.

  • Y42 has brought Sharpist closer to a data-driven culture: Now the entire company works with dashboards and data insights. 

  • Sharpist offers workshops for all their employees so that everyone can get familiar with Y42 and learn how to work with data independently.

The company

Sharpist offers personalized learning for every employee worldwide through 1:1 digital coaching and continuous micro tasks. From a longer-term perspective, Sharpist is building a central interface to an employee’s development, which allows for tracking development data and creates, in turn, measurable business impact for organizations. The result is a data play rolled-out via product, processes, and people.

A company like Sharpist accumulates a lot of data, both product and business-related, which calls for a data team to generate insights from it. Nathalie Gocht is the Data Scientist and with her team, she is in charge of understanding how the product is positioned in the market, which new features to develop and how the business is doing overall.

Business challenge

Nathalie believes that understanding how your business is positioned in the market is crucial for startups to make sensible business decisions and thereby offer the best product possible to its customers. But to get there, you have to work with data, and that is something that Sharpist recognized, and started to build the necessary infrastructure for, early on.

Data analytics was Sharpist’s priority from the get-go, especially because anything else in the data science space — for instance, putting together a database, a warehouse, an ETL tool, a visualizations tool, an analytics tool and an AI/ML tool — needs a lot of money and engineering time to set up. Despite not having an analytics tool from the start, Sharpist worked with Google BigQuery and enabled the necessary analyses through SQL queries.

However, this process turned out to be quite long and they could only achieve a tiny fraction of what they intended to. At that point, it was clear to Sharpist that they would either need to hire many more people for the data team, which would be very costly, or buy a tool. That’s where Y42 came in.

Why they chose Y42

What drew Sharpist in were the integrations: Y42 offers 100+ integrations to choose from — no programming required from the user. Considering that, up until then, Sharpist had been doing all the engineering behind integrations themselves, having them already available freed up time for them to focus on other things, like modeling or analyzing data.

Moreover, the ability to request APIs and get different teams on board to work with the tool and collaborate was a big plus when choosing Y42. The fact that Y42 sits on top of Sharpist’s BigQuery warehouse, giving them full ownership of all their data (since all the modeled data is placed back into the warehouse) was the determining factor for them to choose this tool. The various data export options and the automation layer were the cherries on top of the cake.

“The complete offer of integration, automation, and then of course the functionalities of visualization and modeling were crucial for us to choose Y42. The tool was very easy to test and when using the modeling layer, you could immediately see what it was doing with your data. No need to try any SQL queries or engineering to get results,” explains Nathalie.


Once Sharpist got started with Y42, their first project was simple: replicate every single query they had in BigQuery, see if the data was processed correctly, get a general overview of how the software works, and of course, test how much faster it really is to work with Y42.

The first use case was meant to duplicate the data they already had on how their service is being used — namely, how many coaching sessions are taking place, how many learners are active, how microtasks are performing, etc.

To Nathalie’s surprise, from engineering and modeling all the way to visualization, working with Y42 completely optimized the process and took them half the time it used to take without the tool. Nor did quality assurance take any time with Y42, as they only had to click on “export” and check if the results matched with the visualizations.

"It is extremely easy and time-saving to work with the drag and drop interface and the configurations Y42 offers."

Nathalie Gocht
Nathalie Gocht
Data Scientist at Sharpist


Nathalie explains that all in all, Y42 has had a massive impact on day-to-day work — not only for the data team, but for Sharpist as a whole. Now the entire company checks the dashboards — a data-driven culture has been instilled.

Sharpist and Y42 are an ideal match, as being data-driven is ingrained in both of their DNAs. Y42 just managed to enable Sharpist in order to fulfill their potential. At Sharpist, employees now have the right data at their fingertips to investigate business hypotheses. The dashboards are also regularly checked to understand how the business performs and how the product features are doing. Y42 has allowed Sharpist to move from a solely qualitative analysis approach (through customer interviews) to a quantitative approach with factual numbers and insights.

The impact of Y42 on Sharpist is such that the data team even offers Y42 workshops, enabling every employee to learn how to use the tool and dispel the fear of working with data. Their goal is to have trained everyone in the company by the end of the year. This would give some time back to the data team and allow them to focus on data engineering and data science.

Empowering teams to perform their own analyses is key to Sharpist’s mission — and Y42 is there to help them along the way.

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