Explore Azure Synapse: Advanced Data Integration

What is Azure Synapse Analytics?

Azure Synapse Analytics is a cloud-based analytics service that offers data processing, storage and analytics features. It allows organizations to receive insights from data by offering a serverless environment for big data, analytics and data warehousing. In addition, Azure Synapse Analytics also consists of built-in artificial intelligence and machine learning capabilities.

Azure Synapse Analytics brings together in a single platform the best features of SQL technologies utilized in enterprise data warehousing, a data explorer for time series and log analytics, Spark technologies for big data, Pipelines for ETL/ELT, and data integration and in-depth integration with multiple Azure services such as AzureML, CosmosDB and Power BI.

In addition to including SQL data and warehouse capabilities, Azure Synapse Analytics comes with certain new features, such as:

• Added integrations with Microsoft technologies
• The ability to save, ingest, process, and query non-relational data
• Business intelligence integrations
• More efficient transformation, ingestion, processing and management of large-volume data
• Machine learning integrations
• Integrations with solutions that are compatible with open data initiative

What Is Azure Synapse Used For?

Azure Synapse Analytics is a cloud-based data warehouse that helps organizations analyze and store large amounts of data. Furthermore: 

• It provides a flexible, cost-effective and scalable solution for data warehousing requirements. 
• Azure Synapse is also utilized to transform, load, and query data from several sources, such as Hadoop distributions, on-premises, and NoSQL databases. 
• In addition, Azure Synapse even offers real-time analysis of streaming data.
• Azure Synapse offers a serverless architecture that allows organizations to scale down or up storage and compute resources as required. This assists in optimizing costs and providing the needed storage capacity and processing power. 
• In addition, it comes with built-in security features that protect data, including data encryption and role-based access control.
• It is also used for multiple workloads, including big data processing, data warehousing, and data lake analytics. 

Hence, Azure Synapse is a good option for organizations that need a flexible and cost-effective platform for data warehousing.

Features of Azure Synapse Analytics

Some of the major features of Azure Synapse Analytics are as follows:

• Azure Synapse ingests each type of data along with non-relational and relational data and lets you explore this data with SQL.
• It provides cloud data dashboards, warehousing, and machine learning analytics in a single platform.
• It uses an MPP database technology or massively parallel processing that allows it to manage analytical workloads and process and aggregate huge sets of data efficiently.
• Azure Analytics consists of the latest privacy and security technologies, such as dynamic data masking, real-time data masking, Azure active directory authentication, always-on encryption and more.
• It allows you to query huge data stores using provision resources or an on-demand serverless deployment.
• It is compatible with multiple programming languages, including Spark SQL, Scala, Java, Python, R, SQL and T-SQL.
• It promotes seamless integration with Azure and Microsoft solutions such as Azure Blob Storage, Azure Data Lake, and more.

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Components of Azure Synapse

This service combines cloud computing power and traditional data warehousing flexibility to manage huge skill data sets. It was created to support real-time analytics on both unstructured and structured data. The major components of Azure Synapse are as follows:

Data Storage

It offers multiple storage options such as SQL server, blob storage, and Hadoop distributed file system. Blob storage stores unstructured data, including images, text files and videos. Moreover, SQL servers store structure data, like relational databases, and HTFS stores extremely large files, such as log files.

Data Processing

It includes multiple data processing options, such as real-time streaming, batch processing, and interactive querying. Real-time streaming processes data in real time, such as fraud detection and clickstream analysis. Moreover, batch processing executes long-running jobs, such as ETL and data mining, and interactive querying runs ad-hoc queries on live data.

Data Visualization

You can access multiple visualization options, such as Tableau, Qlik Sense and Power BI. Power BI builds interactive reports and dashboards. Tableau creates visualizations and static reports, and Qlik Sense crafts interactive visualizations.

Machine Learning

Azure Databricks and Azure ML Studio are some machine learning options you can use on Azure Synapse. Azure Databricks is a cloud-based platform that lets data scientists collaborate on machine learning projects, and Azure ML Studio is a graphical interface that simplifies the building, testing and deploying of machine learning models.

Data Management

For efficient data management on Azure Synapse, you can use different data management options, such as a data warehouse, Azure SQL, Azure Cosmos DB and an Azure data lake store.

Security

Azure Synapse offers strong security options, such as Azure Security Center, Azure Active Directory and Azure Information Protection, to protect important information and monitor the security and safety of your cloud resources.

Pricing

You can avail of different pricing options according to the features you require or the amount of data you want to store. Hence, you only pay for the resources you select and use.

Support

It provides 24/7 support from Microsoft and can be contacted through the mail, phone or Azure Portal.

Documentation

It provides extensive online documentation, including reference material, tutorials, and how-to guides.

Community 

It has an active community of users who contribute to the success of its services. The community offers advice, support, and training on accessing the service.

Azure Synapse Analytics Architecture

Azure Synapse Analytics Architecture consists of 4 major components:

• Synapse SQL
• Spark
• Data Integration 
• Studio

Synapse SQL

It is a managed and scalable analytics service that lets you analyze complicated data through T-SQL queries. It offers two pricing models to fulfill your requirements:

• SQL Pool: This model lets you provision a dedicated SQL pool with specific processing power. It is an ideal option for predictable workloads with large data amounts. It consists of two models:
  • Dedicated SQL pool: These are used especially for dedicated models, and workspaces can have unlimited dedicated SQL pools.
  • Serverless SQL pool: These are used specifically for serverless models, and each workspace only consists of one serverless SQL pool.
  • SQL on demand: This model lets users only process data, which makes it suitable for unpredictable or variable workloads.

Spark: Deeply Integrated Apache Spark

It is a unified and open-source analytics engine for large-scale data processing. It provides an in-depth integrated Apache Spark experience. It can be gained by letting users deploy and develop scalable data pipelines, machine learning models and more.

Data Integration: Hybrid Data Integration

It offers a unified platform for integrating data from multiple sources, including cloud, on-premises, and SaaS applications. It allows you to create, monitor, and schedule data pipelines.

Studio: Unified User Experience

It is an interactive, web-based environment. Its major aim is to combine data scientists, data engineers, and businesses to collaborate on analytics projects. It offers a unified experience for multiple tasks, including debugging, developing and deploying analytics solutions.

Azure Synapse vs Databricks

To learn the differences between Azure Synapse vs Databricks, refer to the table given below:

Conclusion

Azure Synapse Analytics is an amazing cloud-based platform for data warehousing and management. It provides multiple data management, storage features, and robust security features to protect the crucial information stored. However, to utilize the services of Azure Synapse to its best, you must be well-versed with all its features and functionality. If you find it challenging to access and use Azure Synapse, enroll today for the Microsoft Certified Azure Data Engineer Associate: DP 203 course by Simplilearn and master data warehousing, real-time analytics and big data analytics with Azure Synapse.

FAQs 

Q1. Does Azure Synapse use SQL?

Yes, SQL is used in Azure Synapse.

Q2. Is Azure Synapse an ETL tool?

Yes, Azure Synapse is an ETL tool and is used to create ETL pipelines.

Q3. What is the difference between ADF and Synapse Analytics?

ADF focuses on data transformation and movement. However, Synapse Analytics aims at data analytics and offers features for data warehousing, real-time analytics and big data analytics.