Microsoft SQL – SQL Big Data
$99.00
Learn to deploy and use SQL Server 2019 Big Data Clusters with Kubernetes, Spark, HDFS and machine learning. For DBAs and data engineers, with 7 hours 6 minutes of training across 41 videos.
- Login details sent straight after payment
- Self-paced. Study on any device
- StemBoss Certificate of Completion
- 14-day refund promise
Secure checkout. Pay by card, Apple Pay or Google Pay.
Microsoft SQL, SQL Big Data teaches you how to build and use SQL Server 2019 Big Data Clusters, which combine SQL Server with Spark and HDFS on Kubernetes. It is for database administrators, data engineers and data scientists who need to work with large data sets in one place. You get 7 hours 6 minutes of training across 41 videos, plus 75 test questions.
What you will learn
- What a Big Data Cluster is and when to use one
- How Docker, Kubernetes, Hadoop and Spark fit together in the cluster
- How to deploy Kubernetes and a Big Data Cluster, then check it works
- How to load data into HDFS and query it with T-SQL
- How to virtualise data from other sources with PolyBase
- How to run Spark jobs, use notebooks and move data with Spark SQL
- How to run machine learning with Python, R and MLeap
- How to deploy, run and monitor apps on the cluster
Course outline
- What are Big Data Clusters? Linux, PolyBase, Active Directory and use cases.
- Big Data Cluster Architecture: Docker, Kubernetes, Hadoop, Spark and endpoints.
- Deployment of Big Data Clusters: prerequisites, deployment and checks.
- Loading and Querying Data: HDFS, T-SQL, data virtualisation and restores.
- Working with Spark: jobs, notebooks, CSV transforms and Spark-to-SQL ETL.
- Machine Learning on Big Data Clusters: ML Services, MLeap, Python and R.
- Big Data Cluster Apps: deploying, running and monitoring apps.
- Maintenance: monitoring, management and automation.
Who this course is for
- Database administrators who run SQL Server
- Data engineers who build data pipelines
- Data scientists who want to train models close to the data
- BI developers working with large data sets
- IT professionals new to big data on SQL Server
Before you start
You should be at ease with SQL Server and T-SQL. Some knowledge of Linux, Docker, Kubernetes, networking and Active Directory will help, as the course sets these up as part of the cluster.
Jobs this course supports
- Big data engineer
- Database administrator
- Data scientist
- Machine learning engineer
- BI developer
| Skill level | Intermediate |
|---|---|
| Duration | 7 Hours 6 Minutes |
| Videos | 41 Course Videos |
| Questions | 75 Test Questions |
| Prerequisites | Some knowledge of SQL Server, Linux, Docker, Kubernetes and Active Directory. |
| Best for | Database administrators, data engineers, data scientists, BI developers |
| Topics covered | Big Data Clusters, Kubernetes and Docker, HDFS, data virtualisation, Spark, machine learning with Python and R, cluster apps, monitoring |
| Format | Online video lessons, self-paced |
| Language | English |
| Closed captions | Yes |
| Certificate | StemBoss Certificate of Completion |
What is inside this course
8 modules and 41 lessons. Here is the full outline.
Module 1: What are Big Data Clusters?3 lessons
- 1.1 Introduction
- 1.2 Linux, PolyBase, and Active Directory
- 1.3 Scenarios
Module 2: Big Data Cluster Architecture6 lessons
- 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 Clusters5 lessons
- 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 Clusters5 lessons
- 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 Clusters7 lessons
- 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 Clusters5 lessons
- 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 Apps6 lessons
- 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 Clusters4 lessons
- 8.1 Introduction
- 8.2 Monitoring
- 8.3 Managing and Automation
- 8.4 Course Wrap Up
Your learning path
Where Microsoft SQL - SQL Big Data fits. Build your skills one step at a time.
Frequently asked questions
What is a SQL Server Big Data Cluster?
It is a SQL Server 2019 feature that runs SQL Server, Spark and HDFS together on Kubernetes, so you can store and query large data sets in one system.
Do I need to know Kubernetes before this course?
Some knowledge helps. The course shows you how to deploy Kubernetes for the cluster, but basic Linux and container skills will make it easier.
Does the course cover machine learning?
Yes. One module covers Machine Learning Services and running models with Python, R and MLeap on the cluster.
Which version of SQL Server does this course use?
It is based on SQL Server 2019, the release that introduced Big Data Clusters.
How long is the course?
It runs for 7 hours 6 minutes across 41 videos and includes 75 test questions.
Do I get a certificate?
Yes. You get a StemBoss Certificate of Completion when you finish the course.
Can I get a refund?
Yes, within 14 days if you have completed less than 20% of the course. See our refund policy for details. Read the refund policy.
