Simplify ! Data Integration, Data Warehousing, and Big Data : All Together with Azure Synapse Analytics

Over the past 12 months I’ve blogged (April 2019, October 2019 and November 2019) that Azure Synapse is a leader for price/performance, for both TPC-H and TPC-DS Decision Support benchmarks and has abilities to deliver insights from all data; across data warehouses and big data analytics systems.

Azure Synapse brings these two divided worlds together into a single service. This not only simplifies a business’ analytics platform but also breaks down siloes that currently exist.

This week at Build, Microsoft announced that Azure Synapse Analytics is moving to Public Preview.

The simplification that Azure Synapse provides, is multi-faceted:

1. Architecture: Synapse simplifies the Modern Data Warehouse, removing much of the glue required to integrate, secure and optimise the myriad PaaS services that comprise the Modern Data warehousing architecture:

Ingestion, orchestration, transformation, data science, exploration and modelling services are all combined, integrated and optimised into a single PaaS based analytics service.

2. Delivery: Synapse simplifies the delivery process across both engineering and data science disciplines. Engineers and data scientists can collaborate, use languages of their choice (e.g. T-SQL, Scala, Python and .NET) against both structured and unstructured data from both the warehouse and the lake.

3. Exploration: Data exploration is hugely simplified, irrespective of where it lives within Azure Synapse. Query the lake using T-SQL or explore your structured data using the big data processing power of Apache Spark, this flexibility provides persona aligned access to all data, using languages of their choice.

Data engineers

Simplify the steps to wrangle multiple data types from multiple sources, including streaming, transactional, and business data. Use a code-free visual environment to easily connect to data sources and ingest, transform, and place data in the data lake.

Data scientists

Build a proof of concept in minutes and easily create or adjust end-to-end solutions. Provision resources as needed or simply query existing resources on demand across massive amounts of data. Work with the language of your choice—T-SQL, Python, Scala, .Net, and Spark SQL.

Business Analysts

Typically, a data savvy professional, able to access and create datasets using Power BI and Analysis Services for ad-hoc and exploratory analysis within Azure Synapse.

Business Users

Securely access datasets and use Power BI to build and consume dashboards available within Azure Synapse. Securely share data within and outside your organisation through Azure Data Share

Additional roles of note

Database administrators

The traditional role evolves to match expanding responsibilities for data warehouses and data lakes. Use familiar languages and tools, such as T-SQL. Run as many workloads as you want with ease. Assign resources to escalate critical workloads based on intelligent workload importance, workload isolation, and enhanced concurrency capabilities.

IT professionals

Protect and manage your organisation’s data more efficiently. Enable big data processing with both on-demand and provisioned compute. Secure access to cloud and hybrid configurations through tight application integration with Azure Active Directory. Enforce privacy requirements using data masking as well as row-level and column-level security.

The Data Lakehouse 

As outlined recently by Databricks, 2020 sees a paradigm shift that combines the best elements of data lakes and data warehouses; the Data Lakehouse.

Azure Synapse is primed to perfectly align to that paradigm shift by bringing these two worlds together. Interestingly, this is not a completely new concept to the Microsoft ecosystem; the Common Data Service provides an abstracted storage layer, for operational solutions, akin to both Synapse and the Data Lake House concept, the analytical solution equivalent.

A New Wave of Analytics

As a result, Azure Synapse ushers in a new wave of agile analytics that will break down siloes that exist because of data types, teams, and skills, providing Insights for All.

Key items that make this possible are:

1. Ability to analyse all types of data in Azure Synapse (structured, semi-structured, and unstructured)
2. Bringing data lakes and data warehouses into a unified analytics service
3. Deeply integrated Apache Spark and SQL engines
4. A single analytics service that brings together data engineers, database administrators, data scientists, IT pros, and business analysts
5. Bringing data skills together into a single service—those familiar with SQL can continue using SQL and those that prefer Python, Scala, SparkSQL, or .Net can do so as well…all from the same analytics service
6. Inherent agility to rapidly build solutions through enhanced productivity, enabling innovation, cost savings and experimentation.

Agility is often linked with how businesses push new products through to market faster or quickly adapt to everchanging customer preferences – this is during normal times. In today’s environment, organisations — public and private alike — are pivoting as fast as they can to answer the challenges posed by the spread of the coronavirus (COVID-19) and for many businesses it means questioning, analysing, trialling and monitoring effectively at speed, in order to potentially just survive. Azure Synapse provides the platform for tactical, organisational and strategic agility during normal and the now new and volatile times of the [immediate] future.

Azure Synapse Analytics and Adatis

Adatis, a Microsoft Gold Partner, are an Azure Synapse launch partner and based in the UK.  We work with Microsoft UK and US to support organisations in their journey to data-driven insights utilising Azure Synapse.

Please contact us to discuss how we can help support you on your Azure Synapse Analytics journey.

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