Azure Synapse Analytics was developed as an extension of Azure SQL Data Warehouse (DW), which has certain major enhancements, such as spark pools which gives ability to write spark code, design orchestration pipelines, on-demand querying engine for data in datalake etcas a service. It enables users to pull data from diverse sources through deeper integration with other tech stacks. These sources may include big data analytics systems, data lake and data warehouse, thereby speeding up the journey from raw data to business insights. Additionally, this platform empowers customers to leverage certain pioneering technologies like Artificial intelligence, Azure Machine Learning and Power BI.
Azure Synapse Analytics is a one-stop platform that provides limitless analytics service, and allows people to analyze all their federated data without having to move or copy terabytes of data, subsequently furthering its self-service features. Users having even the minimal technical know-how can pull data across departmental silos through it.
Using Azure Synapse Analytics
Azure Synapse Analytics provides configurations and turnkey setup options on a fully managed infrastructure to aid people to acquire fast results. It has the capacity to deliver superior flexibility and control in regards to pricing by enabling people to select the ideal pricing option for each workload along with dedicated and serverless options.
There are several real-world use cases in which Azure Synapse Analytics has been used by global firms to drive greater business value through data and innovate their processes. Here are a few of these examples:
- Just-in-time inventory: A company specializing in temperature control systems, energy services, temporary power generation and backup power supply uses Azure Synapse to augment their operational efficiency with the just-in-time supply of their distinctive specialist equipment. The data ingestion pipeline of this company was set up to run every 8 hours as it took almost 4 hours to run the ingestion tasks in a batch. Their data warehouse also had to be rebuilt each day owing to storage limitations. As a result, there was around eight to twenty four hours lag between the times when data arrived, as well as when it was made available for data analytics pipelines. Subsequent to adopting Azure Synapse, the company was able to improve its time-to-insight by considerably improving speed and reducing ingestion complexities. This led to reducing ingestion time from four hours to less than five minutes, subsequently saving around 30-40% of the time of the company that was ultimately saved in solving technology issues in their legacy systems.
- Fraud detection: A major Brazil based fraud detection firm used Azure Synapse for the purpose of modernizing their operational analytics data platform. This company enables its customers to verify an average of half a million transactions on a daily basis by making use of the big data analytics technology for the purpose of fraud detection. As their data set doubles in size every two years, the firm requires fraud detection services within seconds, which subsequently makes it important to have a high level of scalability and performance. By making use of Azure Synapse, this company could considerably reduce the time taken to train new models for the purpose of improving their fraud detection capabilities. In their previous on-premises platform, it used to take a week for ingesting, preparing and training ML models, but with Azure Synapse all of this can be completed within six hours.
- Predictive maintenance: A global leader in the development of aviation software and manufacturing airplane engines also provided advanced data analytics to several airlines worldwide. After every flight, the company had to ingest the time series data for the whole flight, which included a large number of data points. With the use of Azure Synapse, it became faster and easier for them to develop complex predictive machine learning models and carry out corrective maintenance in a timely manner.
- Marketing analytics: A multinational retail company sells a variety of goods through both online channels and brick and mortar stores. The brand wanted to leverage data analytics more competently to develop an end-to-end view of their patrons to improve customer experience and increase profit. They were able to achieve this goal through Azure Synapse that allowed them to effectively unite their data, developers, and business users, while also simplifying the ingestion and data processing procedure. This made it easier for the company to have a central data store that holds all operational and historical data which can be refreshed in near real-time.
The limitless, unified, and powerful analytics service delivered by Azure Synapse can help businesses in several ways.