Hello Dev Community!
On the 16th of April, we are organizing the Data Love conference – a grandiose online event dedicated to every fan of Data Engineering and Data Science (from beginners to expert level).
Data Love covers the best global practices for using Big Data, Machine Learning, Spark, cloud, Kubernetes, and data architecture.
FREE of charge participation with new video service to chat with speakers after talks SpatialChat.
With this event, we hope to build more personal connections between the audience and our lovely speakers. For that, we asked our speakers to share their ideas.
Let’s jump on a wonderful ride of the Data Love world and explore what our speakers have to say.
Our next fantastic speaker is Jules Damji, Developer Advocate at Databricks.
Jules S. Damji is a Senior Developer Advocate at Databricks, an MLflow contributor, and O’Reilly co-author of Learning Spark 2nd. He is a hands-on developer with over 20 years of experience and has worked at leading companies, such as Sun Microsystems, Netscape, @Home, Opsware/Loudcloud, VeriSign, ProQuest, and Hortonworks, building large-scale distributed systems. He holds a B.Sc and M.Sc in Computer Science (from Oregon State University and Cal State, Chico respectively), and an MA in Political Advocacy and Communication (from Johns Hopkins University).
What is your favorite project or a project that you’re particularly proud of?
There is more than one. I would say Apache Spark™, Delta Lake, and MLflow. Each serves a purpose, has a vibrant community of contributors, and has seen wide adoption, where both the original creators and community contributors are innovating in their advancement.
Big data. Cloud data. ML, AI training data, and personally-identifying data. Data is all around us. The world is data-centric. What are some of the industries your clients come from?
Data is pervasive, and as a result, all industries—health & life sciences, manufacturing, retail & e-commerce, media & entertainment, energy & utilities, fintech, etc—have embraced the idea of data-driven decisions, with data as its locus.
How did Covid-19 change data science/engineering in 2020?
The year 2020 was the year of distress; the year 2021 was the year of hope. Data-driven decisions and policies dictated how we controlled, curbed and mitigated the pandemic. WHO, CDC, JHU, and other institutions garnered data, analyzed, built predictive models: this was a huge data project, which validates data-driven policies. At the heart of this global data gathering and cleaning, effort was data engineers and data scientists.
Do you have any final thoughts you’d like to share?
We are amidst a data zeitgeist. Data is not the new oil, data is the new center of gravity: it pulls and gels together data teams to solve tough data problems.
We thank Jules for the thoughtful answers!
At the conference, he is going to speak on the topic: The Future of Data Science/ML at Scale: A Look at MLflow, Delta Lake + Lakehouse.
If you want to attend Jules’s talk and to discuss some questions “in person” you can join us on the 16th of April!
The lineup of speakers is incredible. Topics are diverse. Suitable for any level. Interesting Q&A sessions in Spatial Chat. New career opportunities.
Data is all around you.
Data Love@_datalove
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