vikas kumar
Jest członkiem od 2022
Liga srebrna
3600 pkt.
Jest członkiem od 2022
This course is part 1 of a 3-course series on Serverless Data Processing with Dataflow. In this first course, we start with a refresher of what Apache Beam is and its relationship with Dataflow. Next, we talk about the Apache Beam vision and the benefits of the Beam Portability framework. The Beam Portability framework achieves the vision that a developer can use their favorite programming language with their preferred execution backend. We then show you how Dataflow allows you to separate compute and storage while saving money, and how identity, access, and management tools interact with your Dataflow pipelines. Lastly, we look at how to implement the right security model for your use case on Dataflow.
This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.
While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting. Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.
This course explores the implementation of data load and transformation pipelines for a BigQuery Data Warehouse using Dataproc.
Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Ukończ szkolenie wprowadzające Wdrażanie równoważenia obciążenia w Compute Engine, aby zdobyć odznakę potwierdzającą zdobycie następujących umiejętności: pisanie poleceń gcloud przy użyciu Cloud Shell, tworzenie i wdrażanie maszyn wirtualnych w Compute Engine oraz konfigurowanie systemów równoważenia obciążenia sieci i HTTP. Odznaka umiejętności to wyjątkowa cyfrowa odznaka wydawana przez Google Cloud, która potwierdza Twoją wiedzę o produktach i usługach Google Cloud. Aby ją zdobyć, musisz pokazać, że potrafisz zastosować zdobytą wiedzę, w praktycznym, interaktywnym środowisku. Ukończ to szkolenie oraz moduł Challenge Lab, aby zdobyć odznakę umiejętności, którą możesz udostępnić w swojej sieci kontaktów.