What is Azure Data Lake?
The Azure Data Lake is part of Microsoft’s public cloud offering. It allows for the storage of virtually limitless amounts of data. This data can then be accessed and analyzed by data scientists and analysts. Having such a big data store is a huge boon for organizations that wish to get the most value and insights from their data. A standard data lake definition is that it is a large-scale repository of all of a company’s data. Analytics can then be run on this data to get insights into the business.
Microsoft has built on their experience of data processing for their own operations, including Windows, Skype, and Bing, to build a platform that they feel is fit for purpose. The Azure Data Lake makes ingesting and storing data simpler. It also greatly speeds up streaming and the performance of interactive analytics on the data. This allows for better optimization of big data programs.
Users can easily integrate their existing operations or data warehouses through Azure. The common functions that one expects from data lakes, such as being highly scalable and providing a centralized storage location, are also features of Azure Data Lake. For creators and users of big data, Azure provides a cost-effective and highly secure platform for uploading and processing their data.
Azure Data Lake uses a pipeline process to bring data from ingestion to analysis. This means that it is first taken from many sources in its original format. This then goes through a preparation stage, where it is tidied up and put in a schema. It is then stored and can be accessed for a wide variety of different processing needs.
With the Azure Data Lake, analysis is made even easier by the integration of Hadoop and Apache Spark. These allow for better resource management and easier querying of data through SQL requests.
