Microsoft Azure provides full set of capabilities for Data Driven organizations looking to analyze and get insights from their huge amount of data.
In the following article Ethan Shalev, Senior Big Data Developer at Datacube describes main features we are using while building big data solutions at the most advanced companies in Israel.
Azure Data Lake was made public at the beginning of 2017. Designed for big data analytics, a single Azure Data Lake account can store trillions of structured, semi-structured or unstructured data files originating from a wide variety of sources, where each file can be greater than a petabyte in size.
In the case of a traditional data warehouse, data needs to be extracted from source systems, transformed and loaded into the data warehouse before it can be consumed. Data Lake provides an intermediary stage, holding the data in its raw form, allowing users to consume it at a later stage, if and when needed.
With its built-in analytical capabilities, Azure Data Lake allows its users to store, digest and consume their data in a single location. Analytics can be performed both on a per-transaction basis as the information flows in, as well as in bulk, analyzing huge amounts of data using familiar tools.
Azure data lake architecture. Credit: Microsoft.com
As with the entire Azure suite, the cloud based solution enables you to set up your environment within moments, and scale up or out as your requirements evolve over time.
We will be happy to farther explain and demonstrate those capabilities and to check how it can fit your organization.
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Ethan Shalev, Senior BI Developer,
DataCube