The data specialist is a multi-disciplinary role that employs expertise to design, manipulate, analyze, sort, and export various types of information that the organization uses.
The specialist uses techniques to manage large-scale information, such as Machine Learning technology, and tools to sort and present information to different audiences. This role may also handle the management of virtualized storage platforms.
The following training programs aim to:
Possible certifications upon completing your training include:
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 Microsoft certification training explores how to leverage cloud-scale machine learning solutions using Azure Machine Learning. This course teaches you how to utilize your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and monitoring of machine learning solutions in Microsoft Azure.
This training is a comprehensive preparation for the DP-100: Designing and Implementing a Data Science Solution on Azure exam to earn the Microsoft Certified: Azure Data Scientist 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 course provides comprehensive preparation for the DP-600: Implementing Analytics Solutions Using Microsoft Fabric exam, leading to the Microsoft Certified: Fabric Analytics Engineer Associate certification.
This course covers methods and practices to implement data engineering solutions by using Microsoft Fabric. Students will learn how to design and develop effective data loading patterns, data architectures, and orchestration processes. Objectives for this course include ingesting and transforming data and securing, managing, and monitoring data engineering solutions. This course is designed for experienced data professionals skilled at data integration and orchestration.
This course provides comprehensive preparation for the DP-700: Microsoft Fabric Data Engineer exam, leading to the Microsoft Certified: Fabric Data Engineer Associate certification.
The Microsoft DP-420 course stands out as a crucial resource offering individuals the opportunity to explore the intricacies of designing and implementing data solutions on Azure. This comprehensive course is designed to equip participants with the skills needed to design robust and scalable data solutions, leveraging the power of Microsoft Azure services.
This four-day Microsoft certification training teaches developers how to create an application using the SQL API and the SDK for Azure Cosmos DB. Students will learn to write efficient queries, create indexing policies, manage and provision resources, and perform common operations using the SDK.
This training is a comprehensive preparation for the DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB exam to earn the Microsoft Certified: Azure Cosmos DB Developer Specialty.
This comprehensive training enables IT professionals to master storage security in Azure Files and Azure Blob Storage. Participants will learn to implement robust security strategies, configure access controls, and protect data stored in the Azure cloud. The course covers encryption best practices, identity management, firewall configuration, and data protection solutions for cloud storage environments.
This learning path explores how Azure AI and Azure Machine Learning Services integrations, available through the Azure AI extension for Azure Database for PostgreSQL – Flexible Server, enable you to develop intelligent applications powered by artificial intelligence.
During this training, participants will identify and describe key data concepts such as relational data, non-relational data, Big Data, and analytics, and explore the implementation of this technology with Microsoft Azure. They will delve into the roles, tasks, and responsibilities in the data world. Participants will explore relational data offerings, provisioning, and deployment of relational databases, and querying relational data through cloud data solutions with Microsoft Azure. They will investigate non-relational data offerings, provisioning, and deployment of non-relational databases, and non-relational data stores with Microsoft Azure. Participants will explore processing options available for creating data analytics solutions in Azure, including Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. They will also learn about Power BI, including its building blocks and how they interact.
This course provides comprehensive preparation for the DP-900: Microsoft Azure Data Fundamentals exam, leading to the Microsoft Certified: Azure Data Fundamentals certification.
This course enables you to master the fundamental principles of Microsoft’s dialect of the standard SQL language, which is Transact-SQL. The topics comprehensively cover advanced querying and data modification in relational databases hosted in Microsoft SQL Server database systems, including: Microsoft SQL Server, Azure SQL Database, and Azure Synapse Analytics.
You will develop complete expertise in using Transact-SQL to create sophisticated queries, optimize performance, and efficiently manage data in modern Microsoft SQL environments.
This learning path enables you to master the migration of SQL Server workloads to Azure SQL. You will develop complete expertise in evaluating SQL Server components and migration compatibility using the Azure SQL migration extension and Data Migration Assistant. You will also discover how to efficiently provision and configure optimized Azure SQL resources.
You will gain comprehensive practical experience to select the optimal migration strategy based on specific business requirements regarding downtime, advanced migration state management, and proactive database migration monitoring.
Additionally, you will master critical post-migration tasks, including disaster recovery and continuous monitoring. These skills are essential to ensure a smooth and efficient transition to Azure SQL and guarantee optimal performance after migration.
This learning path enables you to master the development of data-driven applications with Microsoft Azure SQL Database. You will develop complete expertise in creating and configuring an optimized Azure SQL Database, creating and deploying database projects using GitHub Actions and Azure Pipelines, and advanced automation of the publishing process.
You will also discover how to effectively leverage the Data API builder for Azure SQL Database and how to develop a high-performance Data API with Azure Web Apps and Static Web Apps. Additionally, you will acquire the strategic skills necessary to import data via external REST endpoints, export data using Azure Functions, and robustly secure an Azure SQL Database.
These essential skills will enable you to efficiently develop and manage modern applications with Azure SQL Database, ensuring optimal performance and enhanced security.
Azure Database for PostgreSQL is a high-performance PaaS database service available in the Microsoft cloud. It builds on the open-source PostgreSQL relational database and integrates native high availability, automatic backup and restore, as well as advanced security features. The pay-as-you-go pricing model provides predictable performance and near-instant scaling.
In this comprehensive learning path, you will master the key features of PostgreSQL and their optimized implementation in Azure Database for PostgreSQL. You will explore the different implementation options for Azure Database for PostgreSQL and learn to configure a server tailored to your specific business needs.
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 professionals to master data warehouse implementation with Microsoft Fabric. Participants will learn to design, deploy, and optimize modern data warehousing solutions, using Fabric’s advanced capabilities for data integration, transformation, and management. The course also covers best practices for dimensional modeling, performance optimization, and establishing efficient data pipelines in an enterprise environment.
Master the ingestion, transformation, and analysis of real-time streaming data with Microsoft Fabric. This comprehensive training enables you to develop complete expertise in leveraging Microsoft Fabric’s real-time analytics capabilities, including configuring streaming data pipelines, implementing advanced transformations, and creating high-performance analytics solutions to process massive volumes of continuous data. Explore modern streaming data processing techniques and optimize your data architectures for instant insights and real-time decision-making.
Master the complete data science process and discover how to perform advanced Machine Learning model training to accomplish artificial intelligence in Microsoft Fabric. This comprehensive training enables you to develop complete expertise in leveraging Microsoft Fabric’s data science capabilities, including data exploration and preparation, implementation of sophisticated machine learning algorithms, and creation of high-performance AI solutions to solve complex business problems. Explore modern data science techniques, optimize your ML models, and transform your data into actionable predictive insights for strategic decision-making.
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.
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