Top 5 Takeaways from Google Cloud’s Data Engineer Spotlight

In the past decade, we have experienced an unprecedented growth in the volume of data that can be captured, recorded and stored.  In addition, the data comes in all shapes and forms, speeds and sources. This makes data accessibility, data accuracy, data compatibility, and data quality more complex than ever more. Which is why this year at our Data Engineer Spotlight, we wanted to bring together the Data Engineer Community to share important learning sessions and the newest innovations in Google Cloud. Did you miss out on the live sessions? Not to worry – all the content is available on demand. Interested in running a proof of concept using your own data? Sign up here forhands-on workshop opportunities.Here are the five biggest areas to catch up on from Data Engineer Spotlight, with the first four takeaways written by a loyal member of our data community: Francisco Garcia, Founder of Direcly, a Google Cloud Partner. #1: The next generation of Dataflow was announced, including Dataflow Go (allowing engineers to write core Beam pipelines in Go, data scientists to contribute with Python transforms, and data engineers to import standard Java I/O connectors). The best part, it all works together in a single pipeline. Dataflow ML (deploy easy ML models with PyTorch, TensorFlow, or stickit-learn to an application in real time), and Dataflow Prime (removes the complexities of sizing and tuning so you don’t have to worry about machine types, enabling developers to be more productive). Read on the Google Cloud Blog: The next generation of Dataflow: Dataflow Prime, Dataflow Go, and Dataflow MLWatch on Google Cloud YouTube: Build unified batch and streaming pipelines on popular ML frameworks #2: Dataform Preview was announced (Q3 2022), which helps build and operationalize scalable SQL pipelines in BigQuery. My personal favorite part is that it follows software engineering best practices (version control, testing, and documentation) when managing SQL. Also, no other skills beyond SQL are required. Dataform is now in private preview. Join the waitlist Watch on Google Cloud YouTube: Manage complex SQL workflows in BigQuery using Dataform CLI #3: Data Catalog is now part of Dataplex, centralizing security and unifying data governance across distributed data for intelligent data management, which can help governance at scale. Another great feature is that it has built-in AI-driven intelligence with data classification, quality, lineage, and lifecycle management.  Read on the Google Cloud Blog: Streamline data management and governance with the unification of Data Catalog and Dataplex Watch on Google Cloud YouTube: Manage and govern distributed data with Dataplex#4: A how-to on BigQuery Migration Services was covered, which offers end-to-end migrations to BigQuery, simplifying the process of moving data into the cloud and providing tools to help with key decisions. Organizations are now able to break down their data silos. One great feature is the ability to accelerate migrations with intelligent automated SQL translations.  Read More on the Google Cloud Blog: How to migrate an on-premises data warehouse to BigQuery on Google Cloud Watch on Google Cloud YouTube: Data Warehouse migrations to BigQuery made easy with BigQuery Migration Service #5: The Google Cloud Hero Game was a gamified three hour Google Cloud training experience using hands-on labs to gain skills through interactive learning in a fun and educational environment. During the Data Engineer Spotlight, 50+ participants joined a live Google Meet call to play the Cloud Hero BigQuery Skills game, with the top 10 winners earning a copy of Visualizing Google Cloud by Priyanka Vergadia. If you missed the Cloud Hero game but still want to accelerate your Data Engineer career, get started toward becoming a Google Cloud certified Data Engineer with 30-days of free learning on Google Cloud Skills Boost. What was your biggest learning/takeaway from playing this Cloud Hero game?It was brilliantly organized by the Cloud Analytics team at Google. The game day started off with the introduction and then from there we were introduced to the skills game. It takes a lot more than hands on to understand the concepts of BigQuery/SQL engine and I understood a lot more by doing labs multiple times. Top 10 winners receiving the Visualizing Google Cloud book was a bonus. – Shirish KamathCopy and pasting snippets of codes wins you competition. Just kidding. My biggest takeaway is that I get to explore capabilities of BigQuery that I may have not thought about before. – Ivan YudhiWould you recommend this game to your friends? If so, who would you recommend it to and why would you recommend it? Definitely, there is so much need for learning and awareness of such events and games around the world, as the need for Data Analysis through the cloud is increasing. A lot of my friends want to upskill themselves and these kinds of games can bring a lot of new opportunities for them. – Karan KukrejaWhat was your favorite part about the Cloud Hero BigQuery Skills game? How did winning the Cloud Hero BigQuery Skills game make you feel?The favorite part was working on BigQuery Labs enthusiastically to reach the expected results and meet the goals. Each lab of the game has different tasks and learning, so each next lab was giving me confidence for the next challenge. To finish at the top of the leaderboard in this game makes me feel very fortunate. It was like one of the biggest milestones I have achieved in 2022. – Sneha Kukreja
Quelle: Google Cloud Platform