Which path you should follow to become certified in data – Microsoft Azure

What is Azure?

Microsoft Azure is a cloud computing service created by Microsoft to build, test, deploy, and manage applications and services using its data centers.

The Azure platform is made up of more than 200 cloud products and services designed to help you bring to life new solutions that solve today’s challenges and create tomorrow.

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How to certify in data?

Microsoft makes training paths available through certifications that range from a basic level (fundamental) to advanced (specialists).

Keep in mind that for each certification you must take an exam after paying the corresponding fee.

 

As regards Data, Azure proposes the following paths:

1. AZ-900 Microsoft Fundamentals

This certification validates basic knowledge of cloud services and how those services are provided with Azure. Candidates must demonstrate a fundamental understanding of cloud concepts, along with Azure services, workloads, security, privacy, pricing, and support.

See certification

2. Azure Data Fundamentals

Have an understanding of basic data concepts and how they are implemented using Azure data services.

See certification

 

For Data Scientists you can choose to carry out these two certifications:

3. Azure AI Fundamentals

This certification requires a basic understanding of machine learning and artificial intelligence concepts, along with related Azure services.

See certification

4. Azure Data Scientist Associate

For this certification you must have knowledge and experience in data science and in the use of Azure Machine Learning and Azure Databricks.

The candidate must run data experiments and train predictive models. Also, manage, optimize and deploy machine learning models in production.

See certification

 

For Data Engineering, two other certifications can be done:

5. Azure Data Engineer Associate

You should have a solid understanding of data processing languages, such as SQL, Python, or Scala, and should understand parallel processing and data architecture patterns.

The candidate must ensure that data pipelines and data storages are high-performing, efficient, organized, and reliable, given a specific set of business requirements and constraints. This professional can take care of unforeseen problems quickly and minimizes data loss. An Azure data engineer also designs, implements, monitors, and optimizes data platforms to meet data flow needs.

See certification

6. Customer Data Platform Specialty

For this certification, you must have first-hand experience with Dynamics 365 Customer Insights, Power Query, Microsoft Dataverse, the Common Data Model, Microsoft Power Platform, and one or more additional Dynamics 365 apps. Direct experience with practices related to privacy, compliance, consent, security, responsible AI, and data governance policy is also required.

Experience with processes related to KPIs, validation, visualization, preparation, matching, chunking, segmentation, and improvement is also needed. You should have a general understanding of Azure Machine Learning, Azure Synapse Analytics, and Azure Data Factory.

See certification

 

Broader proposals can also be followed, such as:

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