How Microsoft’s Azure Synapse Analytics Will Help Developers &#038; Businesses
One of the important announcements of the recently-concluded Ignite conference by Microsoft was Azure Synapse Analytics. This comes along as an exciting innovation that promises to fill the gap between data warehouse and data lakes. Data warehouse and data lakes are an essential requisite for many companies. However, the challenge till now has been that these two do not work in concert with one another, making the decision-making process quite inefficient. With Azure Synapse Analytics, Microsoft aims to bring data warehouses and data lakes together in a single experience and improve the BI and machine learning capabilities. As it integrates Power BI and Azure Machine Learning, it will enable the improved ability for organisations to both glean insight from its data and apply machine learning to all of its intelligent applications. It will, therefore, allow users to connect and analyse more data across the analytics pipeline. Azure Synapse Analytics comes at an exciting point when hyperscale vendors are looking to better unify their growing number of analytics, big data and AI-bases services. It is currently in preview and not yet available in the general market. What Is Azure Synapse Analytics? Azure Synapse Analytics is being described as the next evolution of Azure SQL Data Warehouse. As Rohan Kumar, corporate vice president for Azure Data, mentions in a blog post, it has been built to address the problem that many of its customers have been facing. While the mass migration to the cloud had led to advantages such as flexibility, large-scale computing and data storage, bringing the next iteration of that tech revolution to use data to reap tangible benefits wasn’t heading anywhere. While many technology providers worked to build a variety of systems to collect, retrieve and analyze enormous troves of information, but they sold as individual products and services. They could not connect with one another and required the users to learn how to operate them separately. “Instead of trying to add more features to each of our services, we decided to take a step back and figure out how to bring their core capabilities together to make it easy for customers to collect and analyze all of their increasingly diverse data, to break down data silos and work together more collaboratively,” said Raghu Ramakrishnan, Microsoft’s chief technology officer for data. Azure Synapse Analytics came into the picture and it allows anybody working with data in those disparate places to manage and analyze it from within a single service. It can be used to analyze relational and unstructured data, using standard SQL. The deeper interaction between Power BI and Azure Machine Learning reduces the time required to process and share data. Some of its features are: Easy integration with Power BIEasy-to-use business intelligence and reporting toolAzure Machine Learning for building modelsCode-free environment for managing data pipelinesAzure Synapse studio provides data professionals with a single workspace for prepping and managing their dataA unified workspace — the Azure Synapse Studio — provides tools for data prep, data management, data warehousing, big data, and AI tasksIt can also support DevOps strategy What Do Developers Get? Microsoft stresses that this new product will help engineers to gather insights from all of their data in a single go. They will not be needing to copy TBs of data from various data storage systems in the enterprise, which has been a pain point for data lakes and warehouses for a long time. The new product will further allow enterprises to choose their own data analytics engine. Microsoft describes it to be a risky surgery as it involved rewriting the guts of the SQL query processing engine to optimise it for cloud and make it capable of instantly handling big bursts of work as well as large and diverse datasets. It is also easy to use, regardless of employees’ technical expertise. It means that business professionals, even with minimal technical expertise can locate and collect data from multiple sources. It also promises to significantly reduce the time of delivering useful business insights from weeks or even months to a few days. How It Stands Out This upgraded solution from Microsoft allows developers to put all their data more quickly, productively and securely while pulling insights from all data sources, data warehouses and big data analytics systems. The company also claimed that compared to its contemporaries such as Google BigQuery, it can run the same query over a petabyte of data in 75% less time. Microsoft also noted that Synapse could handle thousands of concurrent users, unlike some of its competitors. Also, it is a more intuitive platform for data scientists to build an end-to-end data pipeline in one place, while also allowing them to look at the underlying data in ways that are natural to them. Concluding Note While Azure Synapse Analytics promises to bring some breathtaking changes in the developer community, there are others such as Presto, AWS Athena who are offering very similar solutions. Microsoft will definitely benefit from the new product offering, which will help many of their enterprise cloud customers find more value in their offerings. This new development also allows Microsoft to marry Azure Synapse Analytics with the existing cloud products and as a result transforming into a much more complete cloud company.
One of the important announcements of the recently-concluded Ignite conference by Microsoft was Azure Synapse Analytics. This comes along as an exciting innovation that promises to fill the gap between data warehouse and data lakes.  Data warehouse and data lakes are an essential requisite for many companies. However, the challenge till now has been that […]
This comes along as an exciting innovation that promises to fill the gap between data warehouse and data lakes.
["Azure Machine Learning", "Microsoft Azure"]
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["AI", "machine learning", "analytics", "Aim", "RAG", "AWS", "Azure", "R", "SQL", "Go"]
Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.