Keboola and Looker will team up to deliver, this 13th of September, an event all about defining an ideal BI stack to support London’s businesses in becoming more data-driven.

During this event you will have the opportunity to learn from companies such as HomeAway and Growth Street on their strategies in crafting the best BI tech stack to support your journey into digital transformation with especial attention towards marketing automation processes to shape business success.

After a successful Data Festival event during the London Tech Week, Keboola decided to continue supporting these types of events and partnered this time with Looker. Together they will bring to London an event on topics which often present uncertainty and doubt and when it comes to data management and becoming data-driven. In an economy that requires businesses to become data-driven, it is very confusing deciding the best root to go with.

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During the night, while enjoying some drinks at one of the best Data Science hubs in London, Shack15, Guy Keren, Software Engineer at HomeAway, will be talking about the marketing automation process he and his team have put in place to drive traffic to their successful website and optimise recommendations, as a result creating a high-end service that satisfies their audience. HomeAway, acquired by Expedia Inc. in 2015, is a successful vacation rental marketplace with more than 2,000,000 vacation rentals in more than 190 countries around the world and has had proven exponential growth throughout these past years.

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During the night Dylan Baker, Business Intelligence and Analytics Lead at Growth Street, will be sharing his experience in building a BI stack that can respond to strategies in becoming data-driven. He will disclose the logic and the models used to achieve that. Growth Street offers UK businesses a faster alternative to bank overdrafts to respond to a businesses’ need to have more flexibility in managing their cash flow. Established in 2014, Growth Street experienced exponential growth thanks to the use of their data to define and predict demand.

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