Building Advanced Codeless Pipelines on Cloud Data Fusion
Explore the essentials of Building Advanced Codeless Pipelines on Cloud Data Fusion ▼
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Course Feature
Cost:
Free
Provider:
Qwiklabs
Certificate:
Free Certification
Language:
English
Start Date:
On-Demand
Course Overview
❗The content presented here is sourced directly from Qwiklabs platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [May 19th, 2023]
This course, Building Advanced Codeless Pipelines on Cloud Data Fusion, provides learners with an advanced-level exploration of the features available in Cloud Data Fusion. Learners will gain hands-on practice in building more robust, reusable, and dynamic pipelines, as well as exploring the data lineage feature to gain insights into their data's history. This course is a continuation of its predecessor Quest, and is designed to help learners gain a deeper understanding of the features available in Cloud Data Fusion.
[Applications]
After completing this course, learners can apply the knowledge gained to build more advanced codeless pipelines on Cloud Data Fusion. They can use the data lineage feature to trace the history of their data and gain insights into the data's journey. Additionally, they can use the best practices shared in the course to build more robust, reusable, and dynamic pipelines.
[Career Paths]
1. Cloud Data Fusion Engineer: Cloud Data Fusion Engineers are responsible for designing, developing, and maintaining data pipelines using Cloud Data Fusion. They must be knowledgeable in data integration, data engineering, and cloud computing technologies. They must also be able to troubleshoot and optimize data pipelines for performance and scalability. As cloud computing continues to grow, the demand for Cloud Data Fusion Engineers is expected to increase.
2. Data Scientist: Data Scientists use data to develop insights and solutions to business problems. They must be knowledgeable in data analysis, machine learning, and statistics. They must also be able to interpret and communicate their findings to stakeholders. With the increasing availability of data, the demand for Data Scientists is expected to grow.
3. Data Analyst: Data Analysts are responsible for collecting, organizing, and analyzing data to identify trends and patterns. They must be knowledgeable in data analysis, data visualization, and database management. They must also be able to interpret and communicate their findings to stakeholders. As data becomes more accessible, the demand for Data Analysts is expected to increase.
4. Business Intelligence Developer: Business Intelligence Developers are responsible for designing, developing, and maintaining business intelligence solutions. They must be knowledgeable in data analysis, data visualization, and database management. They must also be able to interpret and communicate their findings to stakeholders. As businesses become more data-driven, the demand for Business Intelligence Developers is expected to grow.
[Education Paths]
1. Bachelor of Science in Computer Science: This degree path focuses on the fundamentals of computer science, such as programming, algorithms, data structures, and software engineering. It also covers topics such as artificial intelligence, machine learning, and cloud computing. With the increasing demand for cloud-based data integration solutions, this degree path is becoming increasingly popular.
2. Master of Science in Data Science: This degree path focuses on the application of data science techniques to solve real-world problems. It covers topics such as data mining, machine learning, and data visualization. With the increasing demand for data-driven solutions, this degree path is becoming increasingly popular.
3. Master of Science in Cloud Computing: This degree path focuses on the fundamentals of cloud computing, such as distributed computing, cloud architecture, and cloud security. It also covers topics such as cloud data integration, cloud storage, and cloud analytics. With the increasing demand for cloud-based solutions, this degree path is becoming increasingly popular.
4. Master of Science in Artificial Intelligence: This degree path focuses on the fundamentals of artificial intelligence, such as machine learning, natural language processing, and computer vision. It also covers topics such as robotics, autonomous systems, and deep learning. With the increasing demand for AI-driven solutions, this degree path is becoming increasingly popular.
Course Provider
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