Introduction to SQL Big Data & Analytics

Dive into the depths of SQL Server with this Microsoft SQL – SQL Big Data course and discover one of its most invaluable tools, SQL Big Data Clusters. Here, you will fully explore data virtualization and lakes in order to build a complete artificial intelligence (AI) and machine learning (ML) platform directly within the SQL Server database engine.


With internship




Without internship



this course includes

7 Training Hours

41 On-demand Videos

Closed Captions

8 Topics

75 Prep Questions

Certificate of Completion

What you’ll


Microsoft SQL Database Design


Introduction to Microsoft Power BI


Querying SQL Server With T-SQL – Master The SQL Syntax


Microsoft SQL Database Administration : Optimize Your SQL Server Skills


Microsoft Server – SQL Data Analysis


Microsoft SQL – SQL Big Data


SSAS : Microsoft SQL Server Analysis Services

What is Big Data Analytics?

The course begins by answering the fundamental question: what is big data analytics? You’ll learn the big data definition and big data meaning, and how it differs from traditional data analysis. This section will also introduce you to analytics big data, explaining how it can be used for effective decision-making.



Module 1: What are Big Data Clusters?

1.1 Introduction
1.2 Linux, PolyBase, and Active Directory
1.3 Scenarios

Module 2: Big Data Cluster Architecture

2.1 Introduction
2.2 Docker
2.3 Kubernetes
2.4 Hadoop and Spark
2.5 Components
2.6 Endpoints

Module 3: Deployment of Big Data Clusters

3.1 Introduction
3.2 Install Prerequisites
3.3 Deploy Kubernetes
3.4 Deploy BDC
3.5 Monitor and Verify Deployment

Module 4: Loading and Querying Data in Big Data Clusters

4.1 Introduction
4.2 HDFS with Curl
4.3 Loading Data with T-SQL
4.4 Virtualizing Data
4.5 Restoring a Database

Module 5: Working with Spark in Big Data Clusters

5.1 Introduction
5.2 What is Spark
5.3 Submitting Spark Jobs
5.4 Running Spark Jobs via Notebooks
5.5 Transforming CSV
5.6 Spark-SQL
5.7 Spark to SQL ETL

Module 6: Machine Learning on Big Data Clusters

6.1 Introduction
6.2 Machine Learning Services
6.3 Using MLeap
6.4 Using Python
6.5 Using R

Module 7: Create and Consume Big Data Cluster Apps

7.1 Introduction
7.2 Deploying, Running, Consuming, and Monitoring an App
7.3 Python Example - Deploy with azdata and Monitoring
7.4 R Example - Deploy with VS Code and Consume with Postman
7.5 MLeap Example - Create a yaml file
7.6 SSIS Example - Implement scheduled execution of a DB backup

Module 8: Maintenance of Big Data Clusters

8.1 Introduction
8.2 Monitoring
8.3 Managing and Automation
8.4 Course Wrap Up

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Our Talents Work Here

Our talentstories

We connect learners with peers and experts from around the world, facilitating networking and collaboration opportunities.

IBT Training's DevOps course provided a comprehensive and insightful learning experience with valuable hands-on exercises. While the internship placement was beneficial, additional guidance could enhance the overall transition. Overall, IBT Training lays a solid foundation for entering the DevOps field.

Olaniyan Olatunde Kubernetes Admin, Microsoft

Enrolling in this course proved career-defining, offering invaluable knowledge and a guaranteed internship. It set me on a path to success, delivering everything promised—free certification, ongoing learning, and the ability to pass my sec+ on the first try.

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Upon completing the class, I felt confident and prepared to embark on a career in cybersecurity. The skills and knowledge I acquired have already proven invaluable, as I find myself better equipped to tackle real-world challenges and contribute to the protection of digital assets.


"IBT Learning is an outstanding tech school, with experienced teachers. Graduates gain hands-on experience with management tools such as Git, Maven, Nexus, SonarQube, Ansible, Docker for microservices, Kubernetes for container orchestration, and Terraform for Infras as Code"

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Your Questions, Answered

What is the main focus of the Microsoft SQL – SQL Big Data course?

The course primarily focuses on SQL Big Data Clusters, an impactful feature of SQL Server. It aims to teach students about data virtualization and data lakes, which are used to build a comprehensive AI and ML platform within the SQL Server database engine.

Who is this course suitable for?

This course is perfect for data engineers, data scientists, data architects, and database administrators. It’s especially beneficial for those who want to apply data virtualization and big data analytics in their environments​.

What will I learn from this course?

The course covers a variety of topics, including understanding what a Big Data Cluster is, how to deploy and manage it, and how to analyze large volumes of data directly from SQL Server or via Apache Spark. It also shows how to implement advanced analytics solutions through machine learning, and how to expose different data sources as a single logical source using data virtualization.

Who will be my instructor for this course?

Your instructor will be James Ring-Howell, a Microsoft Certified Trainer and Developer with over 40 years of experience in the field. He has developed applications for a variety of industries and has been teaching technology courses for over 20 years.

What does the course structure look like?

The course is divided into 8 modules, each focusing on a specific aspect of Big Data Clusters. It starts with an introduction to Big Data Clusters and their architecture, then moves on to deployment, data loading and querying, working with Spark, machine learning, creating and consuming Big Data Cluster Apps, and finally maintenance of Big Data Clusters​.

How long is the course and what materials are provided?

The course includes 7 training hours, presented across 41 videos and 8 topics. Additionally, there are 75 practice questions to help reinforce your understanding of the material​​.