What is a Data Lake?
18 August 2020
Have you ever heard of a term known as a data lake? If not, you are not alone. Data lake solutions are not common knowledge, however, they are absolutely essential in terms of efficiency and redundancy.
What Exactly is a Data Lake?
A unique virtual storage lake.
The issue associated with data storage is that information often needs to be formatted in a specific manner. Therefore, structuring data can cause errors to occur. The formatting process can take a significant amount of time. This can be in short, time-consuming when dealing with massive amounts of information which needs to be retrieved immediately.
Data lakes have been known storage alternatives that do not require the structure of the data itself to be modified. By preserving its initial format, a great deal of time will be saved.
Data accessed by “schema-on-read” processing method is modified. An example is the Azure Data Lake system offered by Microsoft.
Real-Time Analytics
Data lake information does not need changing prior to storing. Offering a massive benefit due to users ability to run tests and analytics in a real-time operational environment. Some examples include:
- Dashboards
- Visualisations
- Machine learning applications
- Big data processing
These metrics are critical to the operations of organisations, who need on-the-fly modifications, with minimal delay. Accordingly, data lakes are very flexible in regards to the types of information that can be stored. This also includes IoT information, social media, log files, and data derived from clickstreams.
The Ability to Store and Categorise Data
The unique data lake format is beneficial in categorising information for easy retrieval of relational and non-relational data.
Azure Data Lake can handle single files that exceed one petabyte, without changing their structure or format. Therefore, it is possible to index and crawl through data to access a specific file.
Above all, these are some of the reasons why data lakes represent extremely worthwhile options to consider. Streamlined storing of significant amounts of information. All without core architecture modified to files. Solutions impact both the public and private sectors.
