Big Data, Data Science, and AI in SQL Server 2019

• Big Data Clusters: Integrates SQL Server with Hadoop Distributed File System (HDFS) and Apache Spark for large-scale data processing and analytics.

• Machine Learning Services: Supports R and Python for executing machine learning and data science scripts directly within SQL Server.

• Data Virtualization: Allows querying across various data sources, including big data platforms, using PolyBase without moving the data.

• Integrated AI Capabilities: Enables the deployment and scoring of AI models within SQL Server using in-database machine learning.

Before learning Big Data, Data Science, and AI in SQL Server 2019, you should have the following skills:

1. Basic SQL Knowledge: Understanding of SQL queries, stored procedures, and database management.

2. Familiarity with Data Science Concepts: Knowledge of data analysis, machine learning principles, and common algorithms.

3. Programming Skills: Proficiency in R and Python for data science and machine learning tasks.

4. Understanding of Big Data Technologies: Basic knowledge of big data concepts and tools like Hadoop and Spark.

By learning Big Data, Data Science, and AI in SQL Server 2019, you gain the following skills:

1. Big Data Integration: Ability to integrate and manage big data within SQL Server using tools like PolyBase.

2. Data Analysis and Manipulation: Skills in querying and analyzing large datasets using T-SQL and integrating R or Python scripts for advanced analytics.

3. Machine Learning Model Development: Knowledge of building, training, and deploying machine learning models directly within SQL Server.

4. Data Visualization: Proficiency in visualizing data and analysis results using SQL Server Reporting Services (SSRS) and other visualization tools.