This training course provides you a knowledge and understanding that how to utilize MS Azure Data Factory to co-ordinate transformation and data movement through technology, for example, MS Azure Data Lake Analytics, SQL, and Hadoop. You will study methods to build pipelines that will enable you to group activities to accomplish a specific task.
Learning Style
Provider
Difficulty
Course Duration
This training course provides you a knowledge and understanding that how to utilize MS Azure Data Factory to co-ordinate transformation and data movement through technology, for example, MS Azure Data Lake Analytics, SQL, and Hadoop. You will study methods to build pipelines that will enable you to group activities to accomplish a specific task.
Want to manage and schedule big data workflows?
This training course provides you a knowledge and understanding that how to utilize MS Azure Data Factory to co-ordinate transformation and data movement through technology, for example, MS Azure Data Lake Analytics, SQL, and Hadoop. You will study methods to build pipelines that will enable you to group activities to accomplish a specific task.
Note: To accomplish this course, you will require a MS Azure subscription. You can register for a trial version at http://MS Azure.microsoft.com, or you can utilize your current subscription. The labs have been planned to limit the resource expense required to finish the practical activities.
This course is designed to provide knowledge and understanding to the candidates so they can:
There is no prerequisite for this course
| Brand | Microsoft |
|---|---|
| Subjects | Big Data |
| Lab Access | No |
| Technology | Microsoft |
| Learning Style | Self-Paced Learning |
| Learning Type | Course |
| Difficulty | Advanced |
| Course Duration | 16 Hours |
| Language | English |
Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.
Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.
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