In this course of software engineering, you will figure out how to deploy, plan, and load information using Azure SQL Data Warehouse of Microsoft or SQL DW.
Learning Style
Provider
Difficulty
Course Duration
In this course of software engineering, you will figure out how to deploy, plan, and load information using Azure SQL Data Warehouse of Microsoft or SQL DW.
At the point when you have to scale your data warehouse processing and storage abilities in minutes, not months, you need a cloud-based enormously equal processing arrangement.
In this course of software engineering, you will figure out how to deploy, plan, and load information using Azure SQL Data Warehouse of Microsoft or SQL DW. You'll find out about compressed in-memory indexes, data distribution, elastic scale, and PolyBase for Big Data.
Note: To finish the hands-on components in this course, you will require an Azure membership. You can pursue a free Azure preliminary membership (a legitimate credit card is required for confirmation, yet you won't be charged for Azure services). Note that the free preliminary isn't accessible in all locations. It is conceivable to finish the course and gain credentials without completing the hands-on practices.
Data Analyst
Programmers
Awareness of database ideas and fundamental SQL inquiry syntax Familiarity with the analytics and reporting needs of the users a willingness to adapt effectively and continue on while troubleshooting specialized issues is basic.
| Brand | Microsoft |
|---|---|
| Subjects | Cloud Computing |
| Lab Access | No |
| Technology | Microsoft |
| Learning Style | Self-Paced Learning |
| Learning Type | Course |
| Difficulty | Intermediate |
| Course Duration | 18 Hours |
| Language | English |
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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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