Destroy the data silos for a unified data science

One of the biggest obstacles for Machine learning (ML) is the silos. Data is stored in different systems, in different formats and different tools are used to query them. Technology silos are created by the different tools and it brings different terminology, different priorities to companies. These problems handicap our ability to deliver ML solutions. With Databricks, many of these problems can be overcome. Based on experience with our clients, we will show you in this presentation what are the features of the platform that will help you to accelerate the experiments and development of your data solutions. We will cover the different APIs in languages (Python, Scala, R, Java, SQL), features (ETL, Exploratory Data science, Data warehouse and ML) and we will cover some best practices to get you started.

Gulyás Máté
CEO, Datapao

CEO and Principal Instructor at Datapao, a Big Data and Cloud consultancy and training firm, focusing on industrial applications (aka Industry 4.0). Datapao helps companies to kick off and mature their data analytics infrastructure by giving them Apache Spark, Big Data and Data Analytics trainings and consultancy. Mate also serves as Senior Instructor and Consultant in the Professional Services Team at Databricks, the company founded by the authors of Apache Spark. Previously he was Co-Founder and CTO of enbrite.ly, an award-winning Budapest based startup.
Mate has experience spanning more than a decade with Big Data architectures, data analytics pipelines, operation of infrastructures and growing organisations by focusing on culture. Mate also teaches Big Data analytics at Budapest University of Technology and Economics. Speaker and organiser of local and international conferences and meetups.