Setting up your data architecture can be tricky and confusing without knowing what the future holds for your company’s growth. Some might have attempted to sell you out of the shelf solutions or you could have been overwhelmed by hearing about unlimited different technologies, concepts, big data engines that are scalable without a limit... Right? Or just go with Google Analytics since your marketing team is already keen on that? Do you have a hunch of what you should use?
I have worked and built multiple data architectures for companies with different sizes from only few thousands to billions of active users; and used all modern technologies such as Azure SQL Data Warehouse, Redshift, Presto, Hive, Spark, Airflow, Kinesis Data Firehose. From my experiences at Facebook and Microsoft, I know how these tools can be used efficiently and what are the best practices of the industry.
In this talk I will guide you what solutions are available for all company sizes, when is the right time to add or replace architecture elements for better scaling and/or better engineering. What are the caveats and deep technical tricks to get the most out of these tools. Moreover, I will answer how to avoid building or setting up overcomplicated systems, and when should you hire data scientists or data engineers.
Bence Faludi is passionate about building data architectures and making reusable datasets that can help businesses to grow and understand their audiences. He likes simplicity, and elegant but flexible solutions for all problems.
He works as an independent consultant for various clients simultaneously to set up their Big Data platform. Nowadays, he is helping Wowcher to optimize their data processing.
Bence has worked at Facebook, Microsoft, Wunderlist as a Data Engineer; published a few open source libraries such as mETL, night-shift; and worked for a few months as a consultant for eyeo - the company behind Adblock Plus.
Data Council, PO Box 2087, Wilson, WY 83014, USA - Phone: +1 (415) 800-4938 - Email: community (at) datacouncil.ai