Dataflow

Dataflow is a programming model used for processing large volumes of data. Coursera's Dataflow skill catalogue teaches you about the design and implementation of data pipelines that enable efficient, reliable, distributed data processing. You'll learn about the concepts of parallel processing, windowing, and watermarks in data streaming. You'll also gain insights on how to effectively manage and transform immutable collections of data, understand event time and processing time, and design scalable real-time data processing architectures. This knowledge is beneficial to data engineers, data scientists, and anyone looking to enhance their skills in handling vast quantities of data in real-time scenarios.
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Results for "dataflow"

  • Skills you'll gain: Dataflow, Data Pipelines, Data Processing, Debugging, Performance Tuning, Serverless Computing, CI/CD, Unit Testing, Google Cloud Platform, Disaster Recovery, Integration Testing

  • Status: Preview

    Skills you'll gain: Dataflow, Serverless Computing, Identity and Access Management, Data Pipelines, Data Processing, Data Security, Cloud Storage, Google Cloud Platform, Containerization, Scalability

  • Status: Free Trial

    Skills you'll gain: Dataflow, Data Pipelines, Google Cloud Platform, Data Integrity, Performance Tuning, CI/CD, Data Processing, Debugging, System Monitoring, Issue Tracking, Unit Testing, Disaster Recovery

  • Status: Free Trial

    Skills you'll gain: Dataflow, Data Pipelines, Serverless Computing, Identity and Access Management, AI Personalization, Google Cloud Platform, Data Integration, Cloud Security, Data Integrity, Performance Tuning, Data Security, MLOps (Machine Learning Operations), CI/CD, Data Processing, Debugging, Real Time Data, System Monitoring, Cloud Storage, Issue Tracking, Data Storage Technologies

  • Status: Free Trial

    Skills you'll gain: Dataflow, Google Cloud Platform, Data Pipelines, Real Time Data, Cloud Engineering, Data Lakes, Data Infrastructure, Big Data, Data Warehousing, Extract, Transform, Load, MLOps (Machine Learning Operations), Data Processing, Cloud Storage, Applied Machine Learning, Data Storage, Looker (Software), Apache Hive, Data Integration, Data Storage Technologies, Machine Learning

  • Status: Free Trial

    Skills you'll gain: Dataflow, Data Pipelines, Debugging, Data Integrity, Performance Tuning, System Monitoring, CI/CD, Unit Testing, Data Processing, Google Cloud Platform, Disaster Recovery, Integration Testing

  • Status: Free Trial

    Skills you'll gain: Dataflow, Data Pipelines, Apache Kafka, Real Time Data, Data Processing, Extract, Transform, Load, Pandas (Python Package), Data Transformation, SQL, Jupyter, Google Cloud Platform, Development Environment, Analytics, Cloud Storage

  • Status: Free Trial

    Skills you'll gain: Dataflow, Data Pipelines, Real Time Data, Data Processing, Jupyter, Google Cloud Platform, JSON, Application Programming Interface (API), SQL, Analytics

  • Status: Free Trial

    Skills you'll gain: Dataflow, Serverless Computing, Data Pipelines, Identity and Access Management, Cloud Security, Data Security, Google Cloud Platform, Data Processing, Containerization, Scalability

  • Status: Free Trial

    Skills you'll gain: Dataflow, Google Cloud Platform, Data Pipelines, Data Warehousing, Cloud Engineering, Unstructured Data, Real Time Data, Data Lakes, Big Data, Cloud Infrastructure, Data Infrastructure, MLOps (Machine Learning Operations), Extract, Transform, Load, Tensorflow, Data Visualization, Applied Machine Learning, Cloud Storage, Dashboard, Data Presentation, Data Architecture

  • Status: Free Trial

    Skills you'll gain: Dataflow, Data Pipelines, Debugging, Operational Databases, Google Cloud Platform, System Monitoring, Data Integrity, CI/CD, Maintainability, Data Processing, Unit Testing, Performance Tuning, Disaster Recovery

  • Status: Free Trial

    Skills you'll gain: Feature Engineering, Tensorflow, Google Cloud Platform, Data Quality, Data Cleansing, Keras (Neural Network Library), Scikit Learn (Machine Learning Library), Machine Learning, Exploratory Data Analysis, Supervised Learning, Data Processing, Dataflow, Data Pipelines, MLOps (Machine Learning Operations), Big Data, Data Transformation, Artificial Neural Networks, Deep Learning, Applied Machine Learning, Performance Tuning

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