Today’s post is going to introduce readers with the concept of a data lake and its requirement in the business world. Later on, they will track the data lake access controls for the purpose of stored data security.
If an individual is even tangentially engaged in big data, he/she knows that detecting storage services for the data volumes being originated in every second is most essential. When it is about data management, executives can consider the use of a data lake or a data warehouse as a data repository. It has been observed that the majority of enterprises are already known with the concept of data warehouse but, they are unknown from the data lake. Therefore, let’s first learn what is data lake?
Some people have an assumption – ‘a data lake is simply a 2.0 edition of a data warehouse.’ Although it’s true that both are similar, they have different products that have different functionalities. You can understand this by reading the following statements:
“If you imagine of a datamart as a bottled water store – cleansed, packaged, and structured for effortless consumption – the data lake is a huge water body in a more natural phase. The elements of the data lake stream in from a source to fill up the lake and several persons of the lake can come to analyze, take samples, and dive in.”
A data lake stores record in an unstructured manner where no hierarchy is followed. It maintains data in its rawest manner – it is not analyzed or processed. In addition to this, a data lake accepts and retains all information sources, supports all data schemes and types that are applicable only when data is ready to use. A ‘data lake’ is a centralized repository, which enables you to save all your structure as well as unstructured data at any scale. You can archive your data as-it-is, without having to first architecture the data, and execute different types of analytics – starting from dashboards and visualizations to processing of big data, machine learning, and real-time analytics.
Enterprises, which successfully initiate industry value from their data, will outperform their peers. A survey had shown us that enterprises who implemented a ‘data lake’ are outperforming similar organizations by 9 percent in organic revenue growth. These leaders were capable of using analytics’ new types like machine learning over trending sources like documents, data from click-streams, internet-connected devices, and social media data saved in the data lake. This contributed to identifying, and acting upon opportunities for business development faster by pulling and retaining clients, proactively maintaining devices, boosting productivity, and creating informed decisions.
Fulfilling the requirements of data storage in a business demands for technology and process. Here, we are going to concentrate on technology. As companies build and use platforms to complete their defined set of goals, they must make sure that any approach to offer access control and governance is based on following 6 basic tenets:
For major companies, giving access control and governance on latest, cloud-based data lakes demand for a successful balance in between the user empowerment and securing private data. It is tough to determine correct technology and products for fulfilling the business agility requirements without compromising the security level. Well, organizations can convert their imagining goal into reality by ensuring their strategy to data lake access control and governance that are based in the listed 6 tenets.