What is the Data Lake Analytics? And Its Benefits?
Our Data lake analytics is a powerful data architecture that allows businesses to store, blend data for analysis & scale at magnitudes in near real-time.
Our Data lake analytics is a powerful data architecture that allows businesses to store, blend data for analysis & scale at magnitudes in near real-time.
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Today, large enterprises are faced with an ocean of data. Modern IT teams are inundated with raw or semi-raw data captured from every corner of the company, from online shopping analytics to Internet of Things sensor data. In order to make use of all of this non-defined, schema-less data, these entities have begun dumping it into a data lake. Microsoft's Azure Data Lake provides a robust cloud-based repository for big data that has not yet reached its full potential. The purpose of this glossary is to describe what the Azure Data Lake is and how it can be used for massive data analytics.
The Azure Data Lake is a public cloud repository of information. With today's big data, organizations can house data in the cloud with a secure, virtually limitless solution.
A key component of the Azure Data Lake is the Hadoop File System, which ensures massive computing of petabyte-sized files. Azure Data Lake is more than just a Grand Canyon-sized holding tank; it also allows data scientists, marketers, and analysts to run data lake analytics to begin understanding the data and maximizing its potential.
In addition to Microsoft's Azure Data Lake, the company now offers tools for data visualization and data lake analytics that can completely change the way enterprise organizations handle their data capture and management processes. Regardless of industry or market, these tools provide real business insights for enterprise organizations.
By allowing enterprise organizations to query, process, and store data rapidly, Azure Data Lake helps streamline data storage efficiency. The Azure Data Lake has the advantage of being hosted in the cloud, making it incredibly flexible and scalable. Moreover, data lake analytics can run concurrently; you can pull key business insights from hundreds of terabytes of data more quickly than ever before.
Additionally, Azure Data Lake integrates well with data warehouses and other platforms so raw data can be moved to a more structured environment.
All your raw and semi-structured data can be analyzed in the Azure Data Lake at high throughput. This is the perfect solution for organizations looking to merge a data lake with a data warehouse. Using Azure Data Lake and data lake analytics together, your business can gain real-time actionable insights.
READ MORE: Data Management Strategy With Data Warehouse And Data Lake