microsoft synapse

10 Reasons Synapse is the Answer for Modernizing Analytics

A leading commercial real estate investment and management company was expanding quickly and experienced common growth-limiting pains of rapidly scaling up a business. Their data was siloed across the organization and in many different formats and sources. In order to cut their legacy growth-limiting systems and processes, the firm sought a robust unified data platform for increased transparency of its portfolio & operations, near real-time forecasting & capital planning insights and smarter asset optimization. They chose Azure Synapse to extract value from their data and future-proof their business.

Synapse is an end-to-end data platform that offers limitless analytics and serverless on-demand or provisioned resources at scale to meet different business needs for ingesting, wrangling and serving data for business intelligence and machine learning. In short, its capabilities are far more defined than a rebranded SQL Data Warehouse.

Synapse shows great potential for modern cloud-based data analytics and here are the ten most important reasons why it deserves your attention and consideration:

#1 Unified limitless analytics services

Synapse’s powerful unified analytics capability enables high level of productivity & collaboration among data professionals and allows delivery of big data solutions at scale.

The platform merges capabilities spanning the needs of data engineering, business intelligence and machine learning without creating silos in processes and tools. It’s now possible to explore data, run assessments, develop pipelines and operationalize solutions from a single intuitive code-free web-based UI.

The best of breed capabilities support the solution development lifecycle using features like ingesting data using import mechanisms and pipelines, build of data flows, data experiments using notebooks and scripts and visualizing data for reporting & dashborading purposes. Data teams have the ability to author artifacts, debug , optimize performance by reviewing metrics and integrate with CI/CD tool sets.

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#2 Accelerate time-to-insight at global scale

Synapse utilizes capabilities like massively parallel processing (MPP), result-set caching, clustered columnstore indexes and near-infinite scaling of storage & compute resources to accelerate time-to-insight and empower business agility.

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Source: GigaOm Field Tests

#3 SQL pools – Just dive in

SQL is popular and the universal interface for data analysis. With Synapse, you can use a serverless SQL pool (“built-in” pool) for running on-demand SQL queries against CSV, TSV, Parquet, and JSON without the need for preparing and running dedicated computing resources or clusters.The system automatically adjusts based on your requirements, liberating you from managing your infrastructure and picking the right size for your solution, charging you for the amount of data read.This is an excellent way for the business analysts to explore data in the storage accounts / data lakes or build virtualized semantic data consumption layers.

#4 Low code environment for managing data pipelines

Synapse has an integrated orchestration engine, connectivity to 90+ data sources and data flow capabilities to create data pipelines and rich data transformations using low code environment and visual based UI. Businesses are using these features to meet the customer demands faster and provide effortless integration and extensibility for their applications.

#5 Deeper Insights with Integrated Power BI and Machine Learning (ML)

Azure Synapse leverages Azure Machine Learning and the Power Platform to help teams create end-to-end solutions. With Power BI workspace integration, you can access reports & datasets in Synapse studio and expand the discovery of new data insights. Teams can significantly reduce development time to embed analytics into the BI and ML projects effortlessly.

#6 Enable hybrid transaction/analytical processing (HTAP)

Organizations have struggled connecting their OLTP and OLAP systems for decades, resulting in complex extract, and transform, load pipelines (ETL) and delayed insights. Azure Synapse Link and Cosmos DB analytical store (created automatically) are bridging this gap. The Synapse link bypasses that complex pipeline system and reduces the load on operational systems, which cuts down on costs and provides near real time data for faster and more accurate insights.This service currently available in Azure Cosmos DB. Microsoft plans to release it in Azure SQL, Azure Database for PostgreSQL, Azure Database for MySQL, and other database services soon. This enables business leaders to perform, in the context of operational processes, much more advanced and sophisticated real-time analysis of their business data

#7 Enhanced In-built security and access control

A full arsenal of security and privacy features are built into Azure Synapse, providing capabilities like automated threat detection, private link, azure active directory authentication, and always-on data encryption. The sensitive data discovery and classification, column and row-level security, dynamic masking for real time data protection enables use cases of business data exchange with sensitive information and compliance with national and international regulations.

#8 Seamless integration with data stream analytics

Synapse has seamless integration with Event Hubs and IoT hubs, allowing business users to execute analytical queries on streaming data directly on their data warehousing environment. This supports the most demanding real-time analytics and data processing needs.

#9 Superior workload optimization and management

Synapse facilitates query performance tuning and optimization via limitless concurrency, workload isolation, and workload management. Workload isolation allows you to reserve resources, exclusively, for a workload group with increased flexibility and control over data warehouse resources. This new functionality allows management of heterogeneous workloads and provides flexibility and control over data warehouse resources that improve execution predictability and enhances the ability to satisfy predefined client SLAs.

#10 Integration with Apache Spark

Synapse offers Spark pool which is a provisioned and fully managed Spark service, you pay for the resources provisioned and these can be automatically started up and paused when the Spark pool is in use. Collaborating, sharing and operationalizing workflows that use statistical technique is effortless and Data Science processes within Synapse are visible, understandable and maintainable.

microsoft synapse architecture

Microsoft Synapse Architecture