Query Data by Using Azure Synapse Analytics

Providing insight from data should be a quick and straightforward process. This course will teach you how to write efficient queries against the data stored in Azure Synapse Analytics pools.

Providing insight from data should be a fast and efficient process. In this course, Query Data by Using Azure Synapse Analytics - DP-500, you’ll learn to perform exploratory data analysis in Azure Synapse Analytics. First, you’ll discover the key components of the Azure Synapse Analytics platform. Next, you’ll understand how to leverage various file types to explore the data from serverless SQL pools, and how to query the relational data stored in dedicated SQL pool. Finally, you’ll learn how to use a machine learning PREDICT function to take your queries to another level. When you’re finished with this course, you’ll have the foundational understanding of the data exploration process in Azure Synapse Analytics that will enable you to explore and query the data in Azure Synapse Analytics and get you ready for the DP-500 exam.

What's inside

Syllabus

Course Overview

Identifying an Appropriate Azure Synapse Pool When Analyzing Data

Querying Various File Types with Serverless SQL Pool

Querying Relational Data in a Dedicated SQL Pool

Enhancing Queries with PREDICT Function

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by Nikola Ilic, who are recognized for their work in providing data insights from SQL Servers and Azure Synapse

Students who are preparing for the DP-500 exam will find it helpful

Develops skills needed for students to perform exploratory data analysis in Azure Synapse Analytics

Covers key components of the Azure Synapse Analytics platform

Helps students learn how to query relational data in a dedicated SQL pool

May be helpful for students with an interest in data analysis

Develops skills needed for students to query various file types with serverless SQL pool

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Query Data by Using Azure Synapse Analytics - DP-500 with these activities:

Compile a collection of useful resources on Azure Synapse Analytics

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Centralize your learning materials by compiling a collection of helpful resources, including tutorials, documentation, blog posts, and videos, to have quick access to relevant information.

Browse courses on Azure Synapse Analytics

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Gather resources from Microsoft Learn, Azure documentation, and community forums
Organize the resources into categories or topics
Share your compilation with other learners

Follow tutorials on Azure Synapse Analytics best practices

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Supplement your learning by exploring official tutorials and documentation to gain insights into best practices for designing and implementing Azure Synapse Analytics solutions.

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Access the Microsoft Learn platform and search for Azure Synapse Analytics tutorials
Review documentation on best practices for data ingestion, query optimization, and security
Attend webinars and online workshops offered by Microsoft

Query data in a Serverless SQL pool

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Practice writing queries against data stored in a serverless SQL pool to familiarize yourself with the syntax and techniques.

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Load sample data into a serverless SQL pool
Write a query to retrieve specific columns from the data
Use filters and aggregation functions in your queries
Optimize your queries for performance

Four other activities

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Query relational data in a dedicated SQL pool

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Gain hands-on experience querying relational data stored in a dedicated SQL pool to understand its capabilities and limitations.

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Create a dedicated SQL pool and load data into it
Write queries to join tables and perform complex operations
Use stored procedures and functions to enhance your queries
Configure security and access permissions for your pool

Enhance queries with the PREDICT function

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Explore the capabilities of the PREDICT function to incorporate machine learning predictions into your queries, enabling more advanced data analysis.

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Understand the syntax and parameters of the PREDICT function
Use the PREDICT function to make predictions on new data
Evaluate the accuracy of your predictions and make adjustments as needed
Integrate the PREDICT function into your existing queries

Develop a custom dashboard to visualize data

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Create an interactive dashboard that visualizes data from Azure Synapse Analytics to enhance your understanding and identify trends.

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Connect Azure Synapse Analytics to a data visualization tool like Power BI
Design a dashboard layout and select appropriate visualizations
Configure filters and drill-down options to enable interactive exploration
Present your dashboard to stakeholders and gather feedback

Build a data pipeline to automate data ingestion and processing

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Apply your knowledge by creating a data pipeline that automates the process of ingesting and processing data, providing valuable insights for decision-making.

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Define the data sources and target data store
Use Azure Data Factory to orchestrate data movement and transformations
Schedule and monitor your pipeline for reliability and efficiency
Evaluate the performance and make necessary optimizations

Career center

Learners who complete Query Data by Using Azure Synapse Analytics - DP-500 will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data analysis plays a critical role in today’s businesses. A data analyst is someone who is skilled at extracting, transforming, and analyzing large datasets. Data analysts combine their technical skills with their business acumen to provide insights that drive better decision-making. The Query Data by Using Azure Synapse Analytics - DP-500 course can help you become a data analyst by teaching you how to write efficient queries against the data stored in Azure Synapse Analytics pools.

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Data Scientist

Data scientists are responsible for developing and applying statistical and machine learning models to extract meaningful insights from data. They use their knowledge of mathematics, statistics, and computer science to solve complex business problems. The Query Data by Using Azure Synapse Analytics - DP-500 course can help you become a data scientist by teaching you how to use Azure Synapse Analytics to perform exploratory data analysis and build machine learning models.

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Business Intelligence Analyst

Business intelligence analysts use data to help businesses make better decisions. They collect, analyze, and interpret data to identify trends and patterns. They then use this information to create reports and presentations that help businesses understand their customers, competitors, and market position. The Query Data by Using Azure Synapse Analytics - DP-500 course can help you become a business intelligence analyst by teaching you how to use Azure Synapse Analytics to gather and analyze data.

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Database Administrator

Database administrators are responsible for managing and maintaining databases. They ensure that databases are running smoothly and that data is secure. They also work with developers to design and implement database solutions. The Query Data by Using Azure Synapse Analytics - DP-500 course can help you become a database administrator by teaching you how to manage and query Azure Synapse Analytics pools.

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Data Engineer

Data engineers are responsible for building and maintaining the infrastructure that supports data analysis. They work with data scientists and business intelligence analysts to design and implement data pipelines. They also develop tools and processes to automate data management tasks. The Query Data by Using Azure Synapse Analytics - DP-500 course can help you become a data engineer by teaching you how to use Azure Synapse Analytics to build and maintain data pipelines.

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Software Engineer

Software engineers design, develop, and maintain software applications. They work with users to understand their needs and then design and develop software solutions that meet those needs. They also work with other engineers to integrate software applications with other systems.

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Data Architect

Data architects design and build the data infrastructure that supports an organization's data needs. They work with business stakeholders to understand their data requirements and then design and implement data solutions that meet those requirements. They also work with data engineers to build and maintain data pipelines.

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Machine Learning Engineer

Machine learning engineers develop and deploy machine learning models. They work with data scientists to identify and prepare data for machine learning models. They also develop and train machine learning models and deploy them to production environments.

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Statistician

Statisticians collect, analyze, and interpret data. They use their knowledge of mathematics and statistics to solve problems and make predictions. They work in a variety of fields, including healthcare, finance, and marketing.

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Operations Research Analyst

Operations research analysts use mathematical and analytical techniques to solve complex problems in a variety of industries. They work with businesses to improve efficiency, reduce costs, and make better decisions.

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Financial Analyst

Financial analysts use data to make investment decisions. They analyze financial data to identify trends and patterns. They also develop financial models to forecast future performance.

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Market Research Analyst

Market research analysts collect and analyze data about markets and consumers. They use this data to help businesses understand their customers and make better decisions about product development and marketing.

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Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. They work in a variety of fields, including insurance, finance, and healthcare.

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Epidemiologist

Epidemiologists study the distribution and determinants of health-related states or events (including disease), and apply this knowledge to the control of diseases and other health problems.

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Biostatistician

Biostatisticians apply statistical methods to problems in biology, medicine, and public health.

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