Azure Synapse – Limitless Solution to Big Data

azure synapse analytics overview

Azure Synapse – Limitless Solution to Big Data

In the technology-competent world, everyone is aware of how critical it is to have valuable data insights. To thrive in the competitive market every organization irrespective of its size requires collecting, integrating, and utilizing massive data over data warehouses, data lakes, and data analytics systems.  To consume these data in the most effective and fast-paced manner, businesses require an agile infrastructure to get the accurate and limitless process of data and improve query performance. With the exactly very reason Microsoft launched Azure Synapse in 2019 the evolved version of Azure SQL warehouse.  

In 2019, Microsoft unveiled Azure Synapse Analytics, a groundbreaking service described as a limitless analytics solution. In this blog, we’ll explore the expansive capabilities of Azure Synapse Analytics, detailing its innovative services and features.

What is Azure Synapse Analytics? 

Azure Synapse offers a relentless analytic solution through the combination of big data analytics and enterprise data warehousing.   Synapse gives user the freedom to query data on their terms through provisioned or server-less resources. Azure Synapse is a wrap of several Azure existing parts as a single unit with the support of a robust and scalable data processing engine. It offers and unifies experience to ingest, prepare, manage and serve data for immediate BI and machine learning needs. 

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Key Components of Azure Synapse  

Let us look at the key components of Azure Synapse and its functionalities.  

azure synapse analytics architecture


Source: Microsoft

Serverless SQL pool  

SQL Serverless, an on-demand SQL pool in Azure Synapse Analytics, enables T-SQL queries over files stored in a data lake for data exploration, ad-hoc queries, and data transformation, such as converting CSV files to Parquet. This serverless service requires no infrastructure, supports various file formats like Parquet, CSV, and JSON, and charges on a price-per-terabyte model for query execution. It offers features like automatic schema inference, easy data transformation, logical data warehousing on Azure storage, and auto-scaling, and it supports any T-SQL querying tool, with no upfront costs or resource reservations. 

SQL pool in Azure Synapse

Source: Microsoft 

Dedicated SQL pool  

Dedicated SQL pools in Azure Synapse Analytics provide a data warehouse solutions reliable for organizing large data volumes and complex billing. It offers users control over compute nodes and hourly billing. SQL’s dedicated pool is built on MPP architecture that separates storage and computing with performance measured in data warehouse units (DWU). Evolving from Azure SQL Data Warehouse, Azure Synapse includes features like T-SQL machine learning predictions with the predict function and an improved COPY statement that enables faster data transfer. Moreover, Synapse SQL pool sets a benchmark in delivering competitive price performance in comparison to many other SQL pools like Snowflake, Google BigQuery, and Amazon Redshift ranking second in GigaOm’s annual big data analytics report. 

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Apache Spark  

Azure Synapse consist Azure Spark configuration that is a set of metadata simplifying resource management by eliminating the need to manage clusters, offers fast Spark start-up, and features aggressive auto-scaling. Additionally, it includes built-in support for .NET for Spark, enabling you to leverage your C# expertise and existing .NET code within Spark applications. Apache spark is a leading open-source big data engine that is efficient in data preparation, engineering, ETL, and machine learning. It supports Spark ML algorithms and Azure ML integration for Apache Spark 2.4, including Linux Foundation Delta Lake. 

Data Integration Tools 

Azure Synapse offers a comprehensive suite of data integration tools and services designed to ingest, prepare, and transform data from multiple sources seamlessly. Key components include: 

  1. Data Factory: A cloud-based data integration service that allows you to create data-driven workflows for orchestrating data movement and transforming data at scale. It supports a wide range of data sources and destinations, making it easy to collect, transform, and load data.
  2. Data Flow: A feature within Data Factory that enables data transformation using a visual interface. It allows for data transformations such as joins, aggregations, and sorting, with no need for writing code, making it accessible to data engineers of all skill levels.
  3. PolyBase: A technology that simplifies querying data by allowing you to use T-SQL to access and query data stored in external sources like Azure Blob Storage, Azure Data Lake, and even on-premises SQL Server. It facilitates seamless data integration by enabling high-performance data loading and querying across diverse data sources. 

Azure Data Lake 

Data lake is the main storage of Azure Synapse used for saving large amounts of file-based and semi-structured data. It supports common data models that make data sharing easy across applications like Power apps, Power BI, and Dynamics 365. Moreover, it also supports relational storage through SQL Pools and can integrate with Spark tables and Cosmos DB via Azure Synapse Link. 

Azure Synapse Studio

Azure Synapse Studio offers enterprises a unified portal to build, maintain, and secure solutions within a single user interface, streamlining critical tasks such as data ingestion, exploration, preparation, and orchestration. It enables resource monitoring across SQL, Spark, and Data Explorer, manages security and user administration, provides an IDE for development tasks including SQL, Spark, and KQL, and supports enterprise CI/CD integration. Additionally, it integrates directly with Power BI for seamless data analysis and visualization. 

Key Reasons for Using Azure Synapse  

Azure Synapse is a power tool for enterprises of all sizes, helping them in accumulating business data storage and big data analysis. With its integration ability of Power BI and Machine learning, it can provide a single service that helps companies to uncover the value of their data at scale. 

Let us get in detail the other aspects enterprises are making most out of using Azure Synapse for their business. 

  1. Unified Analytics: The key differentiator of Azure Synapse is unified analytics that boosts productivity and collaboration along with offering big data solutions at scale. These features also entail many other capabilities to meet other enterprise requirements like business intelligence, machine learning and data engineering.
  2. Power BI Integration:  Synapse also provides direct integration with BI workspace. This helps businesses access datasets and reports within Synapse analytics and to create new datasets & reports with the existing data in Synapse Studio. This integration provides advanced data solutions to business as well as data professionals.
  3. Query data on your own terms: There have been other services that allow SQL queries over data sources and formats. However, Synapse goes beyond that by providing the option to run the workloads through a serverless computer model or SQL pools. 
  4. Analytics Over your Data Lake: The limitation of the traditional approach of using SQL and Spark together. It gives the user the flexibility to mix and match the technologies based on their needs. The feature of metadata integration enables users to leverage fast data movement and analysis in a data lake with SQL or Spark.  
  5. Enhanced security and access controls: Azure Synapse offers full-fledged integrated solutions of security suite and privacy provisions. Offering business several security features like Azure active directory, data encryption, auto-threat detection, and private link.  
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Bottom Line 

In this blog we have seen the overview the comprehensive analytic platform Azure Synapse which combines various services and technologies within a unified workspace. It is an efficient solution to meet seamless data integration and analysis needs for both unstructured and structured data. Data professionals can leverage advanced analytics and insights through diverse data sets. Azure Synapse diverse components and features offers users secure data collaboration and integration helping them in enhance data-driven decision-making.  

To learn more about Azure Synapse and other Azure services, reach out to us at Stridely Solutions. We are here to help you embark the enterprise brilliance with the power of Microsoft Azure. Contact us today.


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