Microsoft Azure Data Analyst

Overview

On this Microsoft Azure Data Analyst Skills Bootcamp, your Apprentice will certified in boosting the value of your business’ data assets by using Microsoft Power BI, through learning to design and build scalable data models, cleaning and transforming data, enabling advanced analytic capabilities, and deploying and maintaining deliverables.

In just 12 weeks, a certified Microsoft Azure Data Analyst on your team will be responsible for a multitude of tasks, including:

  • Collaborating with key stakeholders to deliver relevant insights
  • Resolving inconsistencies, unexpected or null values, and data quality issues
  • Using DAX to build complex measures and implement Time Intelligence

As a Microsoft Gold Partner for Learning, Apprentices will get access to Microsoft Official Curriculms (MOCs), learn from Microsoft Certified Trainers (MCTs) as well as Data Subject Matter Experts (SMEs).

Firebrand deliver the programme through Online Instructor-Led learning, based on our Lecture, Lab and Review methodology. Apprentices will be supplemented with support from our Data SMEs, and get full access to an e-learning platform.

Firebrand take sole delivery of the Microsoft Azure Data Analyst Bootcamp provision and will provide the operational infrastructure to recruit learners, deliver training, provide additional support to learners and to access a guaranteed interview with Employers who are regularly hiring people with these skills.

Skills Bootcamp Delivery

The table below details the end-to-end process of the Bootcamp and breakdown of the guided learning hours attached to each certified qualification.    

Week

10 

11 

12 

Total  

Microsoft Azure Fundamentals 

e-Learning

 

 

  

  

  

  

  

  

  

  

  

Online Instructor - Led Training (OIL)

10 

 

 

 

 

 

 

 

 

 

 

 

10 

Microsoft Azure Data Analyst Fundamentals 

e-Learning

 

 

 

 

 

 

 

 

 

 

 

Online Instructor - Led Training (OIL)

 

 

 

10 

 

 

 

 

 

 

 

 

10 

Data Analyst Associate 

e-Learning

 

 

 

 

 

 

 

 

 

21 

Online Instructor - Led Training (OIL)

 

 

 

 

 

10 

 

10 

 

10 

 

 

30 

GMFJ Profile Development 

 

 

 

 

 

Success Coach Support 

1.5 

1.5 

1.5 

1.5 

1.5 

1.5 

1.5 

1.5 

1.5 

1.5 

1.5 

1.5 

18 

Soft Skills/Employability 

 

 

 

 

 

 

 

15 

 

Number of GLH 125

Curriculum

Microsoft Azure Fundamentals 

  • Module 1: Describe cloud concepts, Azure services. 
  • Module 2: Describe core solutions/management tools on Azure
  • Module 3: Describe general security/network security features
  • Module 4: Describe identity, governance/privacy/compliance features
  • Module 5: Describe Azure cost management and SLA’s

Microsoft Azure Data Analyst Fundamentals 

  • Module 1: Describe cloud concepts. 
  • Module 2: Describe core Azure service
  • Module 3: Describe core solutions and management tools on Azure
  • Module 4: Describe general security and network security features
  • Module 5: Describe identity, governance, privacy, and compliance features
  • Module 6: Describe Azure cost management and Service Level Agreements 

Microsoft Data Analyst Associate 

  • Module 1: Prepare the data
  • Module 2: Model the data
  • Module 3: Visualise the data
  • Module 4: Analyse the data
  • Module 5: Deploy and maintain deliverables

Exam Track

As part of this Skills Bootcamp, you will sit the following exams:

DP-900: Microsoft Azure Data Fundamentals

  • Exam code: DP-900
  • Languages: English, Japanese, Chinese (Simplified), Korean, French, German, Spanish
  • Domains:
    1. Describe core data concepts (15-20%)
    2. Describe how to work with relational data on Azure (25-30%)
    3. Describe how to work with non-relational data on Azure (25-30%)
    4. Describe an analytics workload on Azure (25-30%)

DA-100: Analysing Data with Microsoft Power BI

  • Exam code: DA-100
  • Languages: English, Chinese (Simplified), Korean, Japanese
  • Domains:
    1. Prepare the data (20-25%)
    2. Model the data (25-30%)
    3. Visualise the data (20-25%)
    4. Analyse the data (10-15%)
    5. Deploy and maintain deliverables (10-15%)

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