Azure Synapse Analytics
The smooth and successful execution of businesses requires the integration of several valuable services and analytical systems. Data lakes and data warehouses are two such critical analytical systems that organizations need. However, using the services separately can be a hassle for your company.
Instead, if you have a cloud-based platform where you can achieve the functions of both the warehouse and the data lakes, you can work more freely. This is where the Microsoft Azure Synapse comes into the picture. It works as a data warehouse but has several other features that make it a smart choice for data analysis.
What Is Synapse Analytics?
Azure synapse analytics is a multipurpose and unlimited analytics service that is also cloud-based. Its key components include Spark, Synapse SQL pools, and Synapse Pipelines. It provides a common platform for Big Data analytics and data warehousing. In addition to its many functionalities, synapse allows the re-creating of data through snapshots that help in data recovery.
It has the capability to save, process, and query non-relational data. It facilitates machine learning and has business intelligence integrations. Being embedded with Microsoft technologies, it supports more integrations. It also allows organizations to use its features as per their requirements and pay only for what they use.
Uses of Azure Synapse Analytics
The features that Microsoft Azure Synapse is loaded with give plenty of reasons to organizations to use it. Some of the common uses that the synapse can be put to are discussed here.
● Managing Datasets — Together with Azure Data Analytics, the synapse helps in processing unstructured data or a set consisting of both unstructured and structured data. This task is achieved Azure Data bricks, Azure Data Lakes Analytics, Spark, and Hive LLAP. When synapse deals with structured data, it works at high speed and computes heavy read operations.
● Analyzing Real-Time Data — Synapse enables the ingestion of real-time data using Stream Analytics. Its HTAP implementation technology combines with Synapse Link to support the real-time analysis of operational data without bringing any negative impact on the operational systems.
● Multiple Integrations — The Azure synapse integrates well with the features of Microsoft applications. This allows organizations to enjoy the services of both the synapse and the Microsoft.
● Managing Complex Queries — Synapse has an MPP architecture that enables managing huge datasets. It achieves this task while its data analytics is still operational.
● Data Warehousing — Synapse supports a complete data warehousing that facilitates stored procedures and relational data models. The Data Warehouse is also called SQL Pool. It allows the loading of Dimension or Fact tables. It also lets users pause the SQL Pool and enhance performance by increasing computation.
● Supports Machine Learning — Synapse enables the use of machine learning Apache Spark MLlib. Using the Machine Learning Studio, users can create their ML Models.
Thus, the Azure Synapse is a platform that enables the accomplishment of various tasks. It has features that are suitable for data engineers, data analysts as well as data scientists. It allows organizations to assess their business performances on a real-time basis. It also makes the process of collating and managing data hassle-free.
