Microsoft Azure Synapse Analytics

Azure Synapse Analytics is an analytics solution that combines data integration, data warehousing and data analytics. Azure Synapse Analytics offers everything from flexible, individual data queries, to exploring, processing, managing data, to delivering the data to out-of-the-box business intelligence and machine learning applications in a unified interface.

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What is Azure Synapse Analytics?

Azure Synapse Analytics is an integrated enterprise analytics service that accelerates insights from data warehouses and big data systems. Azure Synapse Analytics combines the best technology from different areas: SQL technology for enterprise data warehousing, Spark technology for bigdata purposes, pipelines for data integration and ETL/ELT, and deep integration with other Azure services, e.B. PowerBI, Cosmos DB, and Azure Machine Learning.

Azure Synapse Analytics Architecture

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Azure Synapse - Industry-Leading SQL

Azure Synapse SQL is a distributed query system for T-SQL that can be used to realize data warehousing and data virtualization scenarios and extend T-SQL to streaming or machine learning scenarios.

  • Azure Synapse SQL provides both serverless and dedicated resource models. Users can create dedicated SQL pools to reserve computing power for data stored in SQL tables to benefit from predictable performance and predictable costs.
  • For unplanned workloads or workloads with peak demand, Azure Synapse can use the always-on, serverless SQL endpoint.
  • Use azure Synapse’s built-in streaming capabilities to transfer data from cloud data sources to SQL tables.
  • Use Azure Synapse to load data into managed tables for the best query performance or to query data directly into Azure Data Lake Storage or Azure Cosmos DB without having to perform regular import tasks or wait for it to complete.
  • Integrate AI with SQL using machine learning models to evaluate data using the T-SQL prediction (PREDICT) function.

Apache Spark for Azure Synapse

Apache Spark for Azure Synapse provides deep, seamless integration with Apache Spark – the most popular open source-based big data engine for data preparation, engineering, ETL, and machine learning. 

  • Azure Synapse provides machine learning models with SparkML algorithms and AzureML integration for Apache Spark 2.4 with built-in support for Linux Foundation Delta Lake.
  • With Azure Synapse, benefit from a simplified resource model that eliminates the need to manage clusters.
  • Azure Synapse provides a fast Spark launch and optimal auto-scaling.
  • With Azure Synapse, leverage C# skills just as with. NET code in a Spark application thanks to built-in support for Spark.

Azure Synapse - Working with a Data Lake

Azure Synapse removes the traditional technology barriers to SQL and Spark sharing. Both solutions can be combined as needed by Azure Synapse.

  • With Azure Synapse, tables defined on files in the data lake are seamlessly consumed by either Spark or Hive.
  • With Azure Synapse, SQL and Spark can directly access and parse Parquet, CSV, TSV, Delta Lake, and JSON files stored in the data lake.
  • Azure Synapse enables fast, scalable loading of data between SQL and Spark databases.
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Azure Synapse - Integradet Data Integration

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Azure Synapse uses the same data integration engine and environments as the Azure Data Factory. This allows users to create large-scale on-demand ETL pipelines without leaving Azure Synapse Analytics.

  • With Azure Synapse, capture data from over 90 data sources
  • With Azure Synapse, no programming effort for ETL thanks to data flow activities
  • With Azure Synapse, orchestrate notebooks, Spark jobs, stored procedures, SQL scripts, etc.

Azure Synapse Provides a Unified User Interface

Synapse Studio provides organizations with a single user interface for building solutions, as well as for management and protection functions.

  • Perform important tasks: capture, investigate, prepare, orchestrate, visualize
  • Monitor resources, usage, users in SQL or Spark
  • Use role-based access control to simplify access to analytics resources
  • Write SQL or Spark code and integrate with enterprise CI/CD processes
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The Benefits of Azure Synapse Analytics

Unified analytics platform

With Azure Synapse, build mission-critical data warehouse on the proven foundation of the industry's most powerful SQL engine.

Serverless and dedicated options

Take advantage of Azure Synapse support for both data lake and data warehouse use cases, while choosing the most cost-effective pricing option for your workloads.

Data Lake exploration

With Azure Synapse, bind relational and non-relational data, and easily query files in the data lake through the same service used to create data warehousing solutions.

Data Warehousing

With Azure Synapse, build mission-critical data warehouse on the proven foundation of the industry's most powerful SQL engine.

Hybrid data integration without code

Create ETL/ELT processes in a code-free visual environment with Azure Synapse to easily capture data from more than 95 native connectors.

Built-in Apache Spark and SQL engines

With Azure Synapse, improve collaboration between data professionals working on advanced analytics solutions. Easily use T-SQL queries for data warehouse as well as spark engines with Azure Synapse.

Cloudnative HTAP solutions

With Azure Synapse, only one click is needed to gain insights from real-time transaction data stored in operational databases such as Azure Cosmos DB.

Selection of programming languages

In Azure Synapse, simply use preferred language, including T-SQL, Python, Scala, Spark SQL, and .NET, for serverless and dedicated compute resources.

Integrated AI and BI

Complete your end-to-end analytics solution by seamlessly integrating Azure Machine Learning, Azure Cognitive Services, and Power BI with Azure Synapse.

End-to-end management and monitoring

Simplify the monotonous but required data tasks that every team needs to perform – protect the Azure Synapse workspace, areto and Microsoft take care of the rest.

areto's Microsoft Azure Reference Architecture

areto’s developed reference architecture offers many advantages.

The use of areto’s reference architecture provides customers with architectural best practices for the development and operation of reliable, secure, efficient and cost-effective systems in the cloud. Areto’s architectural solutions are consistently measured against Microsoft best practices in order to deliver the highest benefit to customers.

The areto reference architecture is based on five pillars: operational excellence, safety, reliability, performance efficiency, cost optimization.

Operational excellence
optimal design of operation and monitoring of the systems as well as continuous improvement of supporting processes and procedures

Security
protection of information, systems, assets, risk assessments and risk mitigation strategies

Cost optimization
maximizing ROI through the continuous process of improving the system throughout its lifecycle

Reliability
ensure security, disaster recovery, business continuity as data is mirrored in multiple redundant locations

Performance efficiency
efficient use of computer resources, scalability to meet short-term requirement peaks, sustainability

With the Microsoft expert team from areto to the data driven company!

Overtake the competition by making faster and better decisions!

Find out where your company currently stands on the way to becoming a data-driven company.
We analyze the status quo and show you what potential exists.
How do you want to get started?

Free consulting & demo appointments

Do you already have a strategy for your future Micrsoft Data Analytics solution? Are you already taking advantage of modern cloud platforms and automation? We would be happy to show you examples of how our customers are already using areto’s agile and scalable Microsoft solutions.

Workshops / Coachings

In our Microsoft workshops and coaching sessions, you will gain the necessary know-how, e.g. for setting up a modern cloud strategy or IBCS-compliant reporting with Power BI . The areto Microsoft TrainingCenter offers a wide range of learning content.

Proof of Concepts

Is Azure the right fit for us? Are the framework conditions suitable for it? What prerequisites need to be created? Proof of concepts (POCs) answer these and other questions. This way, you start your project well prepared.

Why Microsoft ?

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Gartner, Magic Quadrant for Cloud Infrastructure & Platform Services, Raj Bala, Bob Gill, Dennis Smith, Kevin Ji, David Wright, 27 July 2021. Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from AWS. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

Microsoft Azure Synapse Know-How Video Library

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Florian Grell
Teamlead Microsoft
Phone: +49 221 66 95 75-0
E-mail: Florian.Grell@areto.de