- Full Microsoft Fabric Mastery:
- Become an expert in the most advanced data analytics and BI platform.
- Improved Decision Making:
- Learn how to design and use real-time reports and dashboards with Power BI.
- Data Life Cycle Optimization:
- Efficiently manage data from ingestion to transformation and analysis.
- Data Science and Engineering Skills:
- Develop and deploy machine learning models and scripts in Python, SQL, and Spark.
- Automation and Data Governance:
- Implement alerts and automated processes that improve information monitoring and security.
- Practical Application in Real Business:
- Applies knowledge in real business scenarios, improving the efficiency and productivity of organizations.

The introduction of this comprehensive Microsoft Fabric course highlights the current importance of comprehensive data platforms for real-time data engineering, science, and analytics. Microsoft Fabric is presented as an innovative solution that unifies multiple tools and services to optimize data management and analysis, covering everything from governance and storage to visualization and process automation. With statistics demonstrating significant growth in the adoption of data analytics solutions and the integration of AI in companies, the course underscores the need for advanced skills in technologies such as Azure Data Factory, Azure Synapse Analytics, and Power BI, essential for transforming data into valuable insights and making strategic decisions in real time.

This course is designed for professionals from various sectors and active job profiles. Although it will focus primarily on the industrial field for practical examples, it is accessible to anyone interested in the subject. Prior technical knowledge is valued, but is not an essential requirement, as a detailed explanation of the concepts will be provided from the beginning of the course.

1. Understand Microsoft Fabric Architecture:
Gain fundamental knowledge of data governance, data storage, processing, transformation, and analytics in Microsoft Fabric.

2. Manage Data and Access to Information:
Learn how to manage data storage and access through Lakehouse, Warehouse, SQL Endpoint, and KQL databases.

3. Design Efficient ETL Processes:
Create and manage pipelines to optimize the data lifecycle, from extraction to transformation and loading (ETL).

4. Create Reports and Dashboards in Power BI:
Design Power BI reports that consume data from multiple sources, using over 150 connectors available in Microsoft Fabric.

5. Transform and Analyze Data:
Use tools like Data Flow and Power Query to apply transformations and prepare data for analysis and reporting.

6. Automate Processes and Define Alerts:
Implement alerts and automations with Data Activator and Microsoft Power Automate to monitor and optimize data management.

7. Implement Data Engineering Processes:
Execute code scripts in Python, SQL, and other languages ​​using Apache Spark inside Microsoft Fabric.

8. Develop Machine Learning Models:
Design, implement, and deploy machine learning models using Microsoft Fabric and Azure Machine Learning.

9. Perform Real-Time Data Analysis:
Ingest and analyze real-time data from IoT devices using KQL databases and other platform tools.

These objectives are designed to provide comprehensive training in Microsoft Fabric, empowering participants to effectively manage and analyze data, and develop solutions that drive data-driven decision making in their organizations.

1. Introduction to Microsoft Fabric:
- What is Microsoft Fabric?
- Microsoft Fabric ecosystem and architecture.

2. Data Governance and Management:
- Data governance.
- Storage in OneLake.
- Lakehouse vs. Warehouse.

3. ETL Processes and Pipelines:
- Design and execution of pipelines.
- Data transformation with Data Flow and Power Query.
- Process integration and automation with Data Activator and Power Automate.

4. Business Intelligence and Power BI:
- Creation of reports and dashboards in Power BI.
- Connectors and data sources.

5. Data Engineering and Science:
- Using Apache Spark to run scripts in Python, SQL, and other languages.
- Design and deployment of machine learning models.
- Real-time data analysis and IoT data management.

6. Security and Compliance:
- Security, resilience and conditional access.
- Compliance with regulations and service labels.

7. Practical Scenarios and Exercises:
- Practical exercises and case studies to apply the knowledge acquired.
- Practical implementation in real business situations.

Course

Onsite

The course is divided into two main parts:

- Theoretical Part (40%): Theory is taught using visual resources such as a whiteboard and projector. Fundamental concepts of the projects are explored, including definitions, objectives, tools and techniques, as well as best practices.

- Practical Part (60%): guided practices are carried out, which represent half of the course time. Participants apply the knowledge acquired in real scenarios, with a focus on problem solving and the use of algorithms.

This balanced methodology provides an effective combination of theoretical and practical learning, allowing participants to acquire applicable skills and solid knowledge for their professional development.

From 7 / 10 / 2024 to 18 / 10 / 2024

Monday Friday

From 09:00am to 14:00am

20 hours

AIDIMME C / Benjamin Franklin 13 (Technology Park) 46980 Paterna (Valencia)

Until October 2, 2024.

Certificate of attendance issued by FEVAMA. Minimum attendance of 80% of class hours.

Free course. Course organized by FEVAMA - Business Federation of Wood and Furniture of the Valencian Community, and 100% subsidized by the Ministry of Innovation, Industry, Commerce and Tourism. General Directorate of Innovation. General Subdirectorate for the Advancement of the Digital Society and Digital Enabling Technologies.
Taught by AIDIMME technical staff.

INFORMATION AND PRE-REGISTRATIONS
AIDIMME - Training Department
961366070 Phone | Fax: 961366185 e-mail: rigual@aidimme.es | www.aidimme.es