This article will discuss the fundamental concept of one of the tools that Azure owns internally. Azure Synapse Analytics is a service offered by Microsoft within Azure, focused on efficiency by generating ideas through systems such as data centers and big data. This service has one of the best tools used by organizations such as: • Spark for handling large amounts of data.
• Data explorer for analysis of logged events.
• Pipelines for data integration and ETL/ELT processes.
• Power BI, CosmosDB, and Azure Machine Learning are Azure aggregated services.
T-SQL (Transact-SQL)
It is an extension of the language known as SQL specifically to work with Microsoft SQL Server, where additional functions or statements are integrated. With this language, we can perform operations such as:
• Get data from a single row.
• Insert new rows.
• Get more than one row.
• BULK INSERT command allows the user to import a file into a table or view it in a specific format.
• Includes aggregation and ranking functions.
• Character and data processing.
SQL Query-leading language
Synapse SQL has a query system for Transact-SQL (T-SQL) that is enabled in different storage and virtualization environments. Use T-SQL to cover real-time scenarios and machine learning. Other Synapse SQL features include:
• Serverless and dedicated models, for successful performance and cost, creation of dedicated SQL groups to separate data processing capacity into tables. In the case of having triggers use the serverless model, a service is always available.
• Streaming functionality to send data from cloud source to SQL tables.
• Integration of artificial intelligence with SQL through learning models to map different data using T-SQL PREDICT statements.
Apache Spark
Apache Spark is integrated within Azure Synapse. It is one of the most popular systems for data preparation, data engineering, ETL processes, and Machine Learning (ML). Among the main functions of Spark, we have the following:
• As for Machine Learning, SparkML and AzureML are integrated with Spark 3.1, which is included with the support of the Delta Lake Linux foundation.
• Spark simplifies the resource model, avoiding worrying about cluster management.
• It has a quick start and scales automatically.
• Support for .NET; allows you to reuse your code in C# within a Spark application.
Working with Data Lakes
Azure Synapse removes the incompatibility of using SQL and Spark together. This can be blended as required depending on your experience. Either Spark or Hive consumes tables defined in files in a Data Lake. SQL and Spark can directly explore and analyze files: parquet, CSV, TVS, and JSON stored in the Data Lake. Fast data loading into SQL and Spark.
Data integration
Azure Synapse has the same data integration engine and experience as Azure Data Factory, allowing you to create custom ETL pipelines without having to leave Azure Synapse Analytics. It will enable you to insert information from more than 90 data sources. ETLs processes with data flow activity can be generated. It also lets you handle notes, jobs in Spark, stored procedures, SQL scripts, and more.
Data Explorer
This tool allows you to make queries interactively, from log files to data telemetry. To complement SQL and Spark, Data Explorer is optimized for analyzing logs using index technology that automatically cleans and partially structures the information.
Use Data Explorer to create real-time log analytics with low latency and IoT solutions to:
• Pattern recognition, anomaly detection, forecasts, and more.
• Replace log search in infrastructure to save costs and increase productivity.
• Create IoT solutions.
• Create SaaS solutions to offer services to your internal or external customers.
Unified experience
Synapse Studio provides a single way to build, maintain and secure everything in the focus of a single user. Execute critical tasks such as inserting, exploring, preparing, directing, and visualizing. The unified experience also allows you to monitor resources, usage, and users through SQL, Spark, and Data Explorer. Role-based access control (RBAC) is also part of the Azure Synapse collective experience to simplify access to analytics resources. We can write in SQL, Spark, or KQL and integrate them with different organizations’ CI/CD processes.
CONCLUSIONS
• Azure Synapse can be understood as a service or added value within Azure.
• Azure Synapse is an Azure service that allows us to obtain information optimally and quickly and, in turn, represent it in different ways for a better understanding for the end user.
• Transact-SQL is a language that serves to query a database just as the SQL language does. In addition, however, it has additional statements dedicated to data analysis.
• Spark is integrated within Azure Synapse, and this compatibility between the two increases productivity when generating reports since Spark is one of the best services for information analysis.
-Blog by: Servio Romero
