Scout24's Journey to Self-Service BI with AWS Cloud and MicroStrategy

Scout24’s journey towards federated, autonomous, and scalable data architecture started in 2013. Hadoop was introduced to manage the organization’s expanding data repository, and data engineers and administrators realized that analytics couldn’t be driven centrally. This is how self-service reporting became actively promoted and supported within the organization. Krystyna Kurinna, Data Access and Services Team Lead at Scout24, describes the organization’s commitment towards accommodating self-service BI as the coalescing of three components: state-of-the-art technology, proper organizational structures, and culture. Their ultimate goal was to build a landscape of data producers and consumers with just enough organizational and cultural rules to ensure seamless cooperation without impeding autonomy. The data team needed to provide a solid data platform and clear guidelines and training on how to participate in the landscape. By making the data lake easier to interface with, they made it simpler to access and publish data. With their defined set of organizational and cultural parameters established, Scout24 carefully chose the technology for a massive shift towards full organizational enablement to foster growth at scale. MicroStrategy was chosen for its semantic metadata layer, ability to centralize and monitor company-wide KPIs, scalable architecture, and easy-to-use self-service capabilities. Within Scout24’s data landscape, MicroStrategy connects to the Amazon S3 data lake through the Presto query engine. Amazon S3 was chosen for its powerfully performant, secure, and expansive features. Alation was chosen for its seamless integration with MicroStrategy and its adaptable interface. As a data catalog and organizer, it forces collaboration and knowledge exchange, provides easy searches for data and defined tags, and provides curation for data quality maintenance.