Azure Synapse is a versatile analytics service that seamlessly integrates enterprise data warehousing and Big Data analytics. It empowers users to query data according to their preferences, utilizing either server-less or provisioned resources on a large scale. The unified experience offered by Azure Synapse streamlines the process of ingesting, preparing, managing, and serving data, catering to immediate business intelligence and machine learning requirements. In 2019, at an Ignite conference in Orlando, Florida, Microsoft introduced Azure Synapse Analytics. A platform proclaimed to be a hyper-competitive and cutting-edge initiative and an attempt to fuse and make sense out of an extremely clogged space of Data and Analytics Platforms.
About half a decade ago, when a fast-paced migration to the cloud was happening in the wake of advantages of large-scale computing and data storage, Microsoft noticed a significant problem from the customer perspective. There were many widespread apps offering storage, analysis and computation, but something was adrift.
These platforms were built solely and didn’t offer a way to connect, leading to wastage of time, effort and cost in learning each platform and reliance on Information Technology. Cynically, these applications were supposed to offer self-service capabilities to business users.
What Is Azure Synapse Analytics?
It is basically an extension of Azure SQL Data Warehouse (DW) with significant enhancements like on-demand query as a service. With deeper integration with other tech stacks, it allows users to securely take data from sources such as a Data Lake, data warehouse, and extensive data analytics systems, therefore, speeding up the journey from raw data to business insights in a perfect way.
Furthermore, the platform allows customers to leverage pioneering technologies such as - Azure Machine Learning, Power BI, and AI, the exact tech stack that is utilized to set up intent-based search engines or weather forecasts.
In short, it is a one-stop solution platform to analyze all the data without copying or moving terabytes of data, thus furthering the self-service abilities. Organizations with minimal technical know-how can pull data across departmental silos.
Azure Synapse analytics is a limitless service that gives its users, extensive features like- Workload Isolation, Provisioned Compute, Azure ML & Apache Spark, Integration with Power BI, Hybrid Data Ingestion, Streaming Analytics, Column and row-level security, Dynamic Data Masking and more.
How does it work?
As discussed earlier, the Azure Synapse brings together the enterprise data warehouse and big data analytics, therefore bringing the two worlds together and giving an ultimate experience to prepare, manage, ingest, and serve data for immediate ML and BI operations.
It furthers the claim by offering complete data analysis services across both serverless (that offers dependability to scale up when there is a need for colossal computation) or provisioned resources options.
So how does it work? These are the four critical components of Azure Synapse:
Synapse SQL: Complete T-SQL based analytics
SQL pool (pay per DWU provisioned)
SQL on-demand (pay per TB processed)
Spark: Deeply integrated Apache Spark
Data Integration: Hybrid data integration
Studio: unified user experience
Key Synapse SQL Components
T-SQL: Users send T-SQL or Transact commands to the Control Nodes. T-SQL commands consist of various add-on features over SQL, like - error & exception handling, transaction control, row processing, and more.
Control Nodes: Acts smartly and the only way for entry into the SQL Synapse. It runs the MPP engine to facilitate and optimize queries in an easy way.
Compute Nodes: It offers the compute Power according to the availability of compute nodes. These nodes range from 1 to 60 depending on the availed service level for Synapse SQL.
Azure Storage: Azure Synapse grips Azure Data Lake Storage Gen2, which is charged separately depending on the storage usage. The data here is sharded into distributions to optimize the system performance.
Benefits of Azure Synapse Analytics
With this enhanced version, Microsoft has made amends for some missing functionalities in Azure Data Warehouse. Have a look.
Limitless scale
Azure Synapse brings insights from all your data across the extensive data analytics system and data warehouses faster. With this improved version, data experts can bring together both non-relational and relational data in the data lake utilizing the simple SQL query. For important workloads, you can easily streamline the performance of all questions with innovative workload isolation, workload management, and a genuinely limitless concurrency.
Deeper insights
This end-to-end analytics solution is strongly integrated with Power BI and machine learning (ML). It significantly expands insights from all your data and applies Machine Learning models to all the intelligent apps. You can reduce the deployment time of your Business Intelligence and Machine Learning projects utilizing a seamless analytics service at your disposal. This service gives you intelligence over all your crucial data smoothly – from Dynamics 365 to Office 365, to SaaS service supporting Open Data Initiative, and effortlessly shares that data.
Real-time analytics experience
Organizations can get an ultimate experience with Synapse Analytics. It gives an integrated workspace for data management, big data, and AI tasks. For managing data pipelines, data experts can use a code-free visual environment which is by far very good. By utilizing the same analytics service, business analysts can use Power BI to build dashboards in less time and data scientists can create POCs.
Advanced privacy and security
Azure is one of the safest and most secure cloud platforms in the present scenario. The crucial features are fabricated in Synapse, like - threat detection and active data encryption. For granular access control, companies can ensure the security and privacy of the data by utilizing native column-level and row-level security. Besides, dynamic data masking automatically protects crucial data in real-time.
What’s more, you can grasp with Azure Synapse Analytics
Other than offering the newest features with Synapse Analytics, Azure further simplifies the setting-up and using modern data platforms. Instead of having different tools in different interfaces, it delivers a single interface where the user can perform multiple tasks:
- Advancement of orchestration for ingesting data (powered by Azure data factory)
- Visualizing and Building reports in self-service mode by using Power BI
- The analysis of data (utilizing SQL or Python Notebooks ) on Spark (powered by Databricks) or SQL (powered by Azure Data Warehouse)
- The management of Enterprise Data Warehouse allows you to build dimensional models in a DW using the Azure Data Warehouse technology
Therefore, Azure Synapse Analytics is a missing link that allows organizations to discover large data volumes with fewer glitches, maximizing value for organizations.