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.
