The data engineer is responsible for the proper functioning of information storage platforms, particularly databases. They design an appropriate storage space based on an in-depth analysis of the company’s needs.
Maintenance, security, continuous administration, and improvement of storage systems are also part of the data engineer’s responsibilities.
The following training programs aim to:
Possible certifications upon completing your training include:
The AZ-204, titled “Developing Solutions for Microsoft Azure,” represents a crucial certification for professionals seeking to master development on Azure. Designed for Azure developers, this course focuses on creating, implementing, testing, and maintaining cloud solutions using a range of Microsoft Azure services and tools. The course teaches developers how to build comprehensive solutions in Microsoft Azure. Students will learn to implement Azure compute solutions, create Azure Functions, implement and manage web applications, develop solutions that use Azure storage, implement authentication and authorization, and secure solutions using Key Vault and managed identities. Students will also learn to connect to and consume Azure and third-party services, and incorporate event-based and message-based models into their solutions. This training also covers monitoring, troubleshooting, and optimizing Azure solutions.
This training is a comprehensive preparation for the AZ-204 exam to earn the Microsoft Certified: Azure Developer Associate certification.
This course covers the methods and practices for implementing and managing enterprise-scale data analytics solutions with Microsoft Fabric. Students will learn to use dataflows, pipelines, and Fabric notebooks to develop analytical resources such as semantic models, data warehouses, and lakehouses.
This course is designed for experienced data professionals qualified in data preparation, modeling, analysis, and visualization, such as those with the Microsoft Certified: Power BI Data Analyst Associate (PL300) certification.
Learners should have prior experience using one of the following programming languages: Structured Query Language (SQL), Kusto Query Language (KQL), or Data Analysis Expressions (DAX).
This comprehensive training enables data professionals to master lakehouse implementation with Microsoft Fabric. Participants will learn to design, deploy, and manage modern lakehouse solutions, combining the advantages of data lakes and data warehouses. The course covers setting up data pipelines, storage optimization, analytics tool integration, and best practices for ensuring data governance and quality in a Microsoft Fabric environment.
This comprehensive training enables data analysts and BI professionals to master the development of dynamic reports with Microsoft Power BI. Participants will learn to create advanced interactive visualizations, implement complex DAX calculations, and design responsive reports optimized for various devices. The course also covers best practices for data modeling, integration of diverse data sources, and report performance optimization for effective data-driven decision making.
This four-day Microsoft certification training provides students with the knowledge and skills necessary to administer a SQL Server database infrastructure for cloud, on-premises, and hybrid relational databases, and to work with Microsoft’s PaaS relational database offerings. Additionally, it will be useful for those developing applications that deliver content from SQL-based relational databases.
This training is a comprehensive preparation for the DP-300: Administering Microsoft Azure SQL Solutions exam to earn the Microsoft Certified: Azure Database Administrator Associate.
This four-day Microsoft certification training teaches students the data engineering patterns and practices for using batch and real-time analytics solutions with Azure data platform technologies.
Students will start by understanding the core compute and storage technologies used to build an analytical solution. They will then explore how to design analytical service layers and focus on data engineering considerations for working with source files. Students will learn how to interactively explore data stored in files within a data lake. They will learn various ingestion techniques that can be used to load data using the Apache Spark functionality found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. Students will also learn the different ways to transform data using the same technologies used for data ingestion. The course includes time spent learning how to monitor and analyze the performance of the analytical system to optimize data load performance or query performance. They will understand the importance of implementing security to ensure data is protected at rest or in transit. Students will then demonstrate how data from an analytical system can be used to create dashboards or build predictive models in Azure Synapse Analytics.
This training is a comprehensive preparation for the DP-203: Data Engineering on Microsoft Azure exam to earn the Microsoft Certified: Azure Data Engineer Associate certification.
This comprehensive training enables data professionals to master data analytics implementation with Azure Databricks. Participants will learn to design, develop, and optimize large-scale data analytics pipelines, using Databricks’ advanced features for data processing and transformation. The course also covers best practices for data engineering, performance optimization, and implementing robust analytical solutions in an Azure cloud environment.
This one-day instructor-led course aims to provide learners with instruction on dedicated and serverless SQL pools and Spark pools. It also covers data wrangling and the ELT process with Synapse pipelines, a process very similar to Azure Data Factory (ADF) for moving data into the Synapse dedicated pool database.
This comprehensive training enables data professionals to master Machine Learning implementation with Azure Databricks. Participants will learn to develop, deploy, and manage ML models using Databricks’ advanced features, including MLflow for experiment tracking and model management. The course also covers ML workflow optimization, training pipeline automation, and best practices for large-scale model deployment in an enterprise environment.
This course teaches developers how to use the Azure Cosmos DB for NoSQL API and Software Development Kit (SDK). Students will learn about query execution, resource configuration, SDK operations, and design strategies for modeling non-relational data and data partitioning.
Unleash the power of data management and analysis with our CompTIA DataSys+ training.
In this comprehensive program, you will dive into the world of data systems and learn how to design, implement, and optimize data solutions that drive business success. Whether you are an IT professional looking to expand your skills or a data enthusiast eager to enter the field, this course will provide you with the knowledge and hands-on experience needed to excel in the dynamic world of data management. From understanding data life cycles to mastering data security and compliance, our expert instructors will guide you through fundamental concepts and practical skills essential for a successful career in data systems. Join us and become a proficient data professional, capable of harnessing the full potential of data for organizations of all sizes.
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