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One of the key announcements of the recently-concluded annual Ignite conference in Orlando, Florida, by Microsoft, was the newest Azure service for enterprises: Azure Synapse Analytics. It’s the latest enhancement of the Azure SQL Data Warehouse that promises to bridge the gap between data lakes and data warehouses. Since the coordination between these two is not proper, the decision-making process becomes quite ineffective. With Azure Synapse Analytics, Microsoft aims at bringing both data lakes and data warehouse together for a unique experience and also to enhance the machine learning and business intelligence capabilities.

Solution providers, including Microsoft, have created various systems to collect, fetch, and analyze an extensive set of information that would exhibit market insights and trends, making way for a new age of enhanced customer service, efficiency, and innovation. However, those systems were created independently by different teams of engineers and sold as separate services and products. These products and services weren’t designed to connect, and customers would need to learn to operate those individually.

So, instead of adding new features to each of their services, Microsoft decided to take a step back and explore how they could combine their key capabilities. This will help customers gather and analyze all the varying data, to solve data inefficiency, and work together.

Moreover, Synapse’s integration with Azure Machine Learning and Power BI will allow the improved ability for organizations to get insights from its data as well as execute machine learning to all its smart apps. Thus, it will enable users to connect and analyze more data.

In this post, we summarize some key points. Read on to know more.

Azure SQL Data Warehouse

Before understanding what Azure Synapse is, you need to understand what Azure SQL Data Warehouse is all about!

Released by Microsoft as Gen 1 in 2016, and Gen 2 in 2018, a first-rate cloud-native OLAP data warehouse. According to its definition by Microsoft, Azure SQL data warehouse is a managed petabyte-scale service having the control to manage computing and storage independently. In addition to the flexibility around compute workload elasticity, it also allows users to pause the compute layer while persisting the data to reduce costs in a pay-as-you-go environment. Some of its competitors are Amazon Redshift, Google BigQuery, Snowflake, and Presto.

What Azure Synapse Analytics adds new to the table?

According to Microsoft, Synapse Analytics will help customers use their data much more efficiently, productively, quickly, and securely by combining insights from all the data sources, warehouses, and big data analytics systems.

Moreover, this offering will enable businesses to benefit from the game-changing technologies such as artificial intelligence and data analytics. These technologies are helping experts better understand the weather conditions, workers to handle their tedious tasks better, and search engines to recognize people’s goals behind typing a query.

What’s more, Azure Synapse Analytics is specifically designed to support the continuously growing DevOps strategy. Here, the operations and development staff closely work together to create and execute services that work better throughout their life cycles.

With this enhanced version, Microsoft has made amends for some functionalities that were missing in Azure Data Warehouse. Thus, it is more than just a simple re branding.