Juan Manuel Perafan
Analytics Engineer - Xebia Data
Utrecht, The Netherlands
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Co-author: Fundamentals of Analytics Engineering
Juan has worked in the realm of analytics since 2017, specializing in SQL, dbt, data governance, and business intelligence (BI). He joined Xebia in 2020 as their first analytics engineer, making him an early adopter of this approach.
Besides helping his clients realize the value of their data, Juan is also very active in the data community. He has spoken at dozens of conferences and meetups around the world (including Coalesce 2023). Additionally, he is the founder of the Analytics Engineering meetup in the Netherlands as well as the Dutch dbt meetup.
Area of Expertise
The Blueprint for Data Modeling: Understanding Responsibilities and Core Tasks
When it comes to data modeling, writing SQL is just the tip of the iceberg. As an Analytics Engineer, it is your job to understand how different stakeholders fit into a wide range of tasks. From documenting data definitions, mapping key business processes, validating cardinality between entities, all the way to data quality strategies.
In this presentation, I'll introduce a structured framework detailing the meetings to arrange at different stages of the data modeling process. I'll also provide the specific questions to ask stakeholders and the expected outcomes for each step, offering a clear roadmap for effective collaboration and successful data modeling projects.
Tableau vs Power BI: The ultimate BI tool for mature data teams
In this talk, we will compare the most widely used BI tools in the market from the perspective of a mature data organization.
The focus of this talk WON’T be on flashy features nor superficial sales talk. We will compare both tools in terms of how well they fit in with DataOps best practices. How do they rank in terms of speed of delivery, governance, robustness, and analytical capabilities.
Speedrunning dbt - Productivity & time-saving tricks for dbt developers
Join me for a hands-on session where I will demostrate dbt productivity tricks, including using dbt codegen, mastering keyboard shortcuts, using state flags when you run dbt build, and leveraging slim CI for efficient testing. Learn how these simple yet powerful techniques can drastically speed up model creation and optimize your dbt workflow.
How to build a data community: The fine art of organizing Meetups
Meetups are a powerful tool for upskilling your team, fostering internal and external data communities, improving your leadership skills, and hiring new talent. In fact, the tech world is famous for its vibrant and informative meetups and conferences.
Interested in organizing a dbt meetup or a tech meetup at your organization? In this talk, you'll learn tips and tricks. From identifying and attracting world-class speakers, to handling the logistics of the event and engaging a relevant audience, you'll discover best practices for creating successful and impactful events.
In addition to practical tips and strategies for organizing meetups, you'll also learn about the many benefits of building a strong data community. By creating connections, sharing knowledge, and collaborating with other data professionals, you can gain valuable insights and advance your career in exciting new ways.
Don't miss this opportunity to learn how to build a thriving data community through organizing meetups with dbt and beyond!
dbt Metrics Strategy: Bridging KPIs and Business Objectives
The dbt metrics has made a lot of teams reflect on what is good metric and how these numbers reflect business outcomes. In this talk, I will break down the multi-disciplinary knowledge you need to improve your metrics. From business goals, KPI Trees, perverse incentives (cobra effect), actionable vs vanity metrics, to metrics definition.
This is not just a talk about dbt metrics, it is also about data strategy.
dbt Turbocharge: Boosting Performance of Your Data Models
Performance is a crucial factor in delivering timely and accurate data to organizations. However, debugging the performance of dbt models can be a challenge, as most resources available focus on legacy databases or tips for specific data engines that do not translate to modern data platforms.
In this talk, we will focus on optimizing performance for dbt users, without focusing on any specific data warehouse. We will explore the commonalities across most data warehouses and provide practical tips and strategies for improving the performance of dbt models. From query optimization to materialization strategies.
Whether you're new to dbt or a seasoned user, this talk will provide valuable insights and best practices for improving the performance of your dbt models.
Juan Manuel Perafan
Analytics Engineer - Xebia Data
Utrecht, The Netherlands
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