Knowit supports Metacore Games in the game industry

As the number of players in Merge Mansion, released in late 2020, grew, the importance of game data processing increased. The company had an old licensed data pipeline in place, but the goal was to build its own. Metacore asked AWS for help and, on a recommendation, found its way to Knowit. The partnership used AWS native tools, which facilitated integration into the customer's environment and existing tools.

As a first joint project, experts from Knowit's data unit planned how to manage the data. Metacore already had other games in the works at the time, so they needed to be ready for a much larger need and for data analysis.

Next, Knowit assembled a team to carry out the roll-out, which started in June 2021. The first version of the new data pipeline was completed in six months. In addition to AWS, the tools chosen were Snowflake, dbt, which best suited Metacore's needs, and Tableau for visual analysis of the data.

As a result of this collaboration, Metacore will be able to manage the data collected. Data collection and analysis will be scalable and ready for the growing number of users as new games are developed. The data solutions will also be continuously developed.

Understanding player behaviour is critical for a gaming company - Metacore wants to make data-driven decisions on game development. In this, data maintenance is key. If the data supply were interrupted, the game could not be further developed based on the data.

Knowit supports Metacore in data management: the actual AWS environment is managed by Metacore and Knowit provides managed services for the products it develops. This means that Knowit's role is to monitor the data pipeline around the clock, i.e. the flow of data to the right place at the right time. In addition, the quality of the data is constantly monitored through an unprecedented service of data monitoring and definition.

In addition to monitoring and testing, data modelling also plays a key role. Data modelling is done with the data build tool (dbt), which is processed from raw data in a central database in Snowflake and regularly tested for errors and anomalies using dbt. Thanks to Snowflake's scalability, response times for data freshness remain manageable, so that the data is up-to-date and ready to be used by the business intelligence tool.

Version control is also an important part of the collaboration, making it easier for more people to work with the data models. The data lineage visualisation provided by dbt also helps to visualise the extent of changes.

In mobile games, player acquisition is a key part of the business. In practice, this means advertising mainly on social media, and the scale is large. As advertising is a significant investment, Metacore wanted to streamline the management of advertising and closely monitor its performance.

Knowit was commissioned to build a web-based interface for managing, sharing and analysing advertising material. Ads can be managed and distributed to selected channels from a single location. Advertising data is made available and analysed directly in the same system that the company uses to analyse its data.

Metacore believes that, at their best, partners are an extension of your team.

"From the very beginning, we have wanted to enable the most direct collaboration possible between us and Metacore's own experts. In our joint projects, our experts and the customer's experts discuss best practices, workflow and other important issues on a daily basis. Face-to-face meetings have become an important element of close cooperation and we are actively working to enable this," says Knowit Client Executive Lasse Rantanen.

"It is important that expectations about the nature and outcome of the collaboration are clear and that both parties can positively contribute to their fulfilment. We have always had a good working relationship with Metacore and both sides can provide suggestions for improvement and change requests with a low threshold. This allows the customer to communicate the changes they wish to see and at the same time we are able to provide suggestions for improvement if we identify solutions that may work better than originally desired."

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