A data lake is an easy to access data repository that stores and processes big data. There are a number of data lake benefits over traditional data warehouses that are used to optimize data by storing some of the data attributes.
A data lake is fashioned in such a manner that it retains all the attributes of data in a centralized system. Unlike traditional warehousing systems, data lakes do not store information in files and folders. Instead, data lake benefits stem from the use of a flat architecture. In this architecture, each dataset is assigned a unique identifier and its metadata is also tagged along with it.What are the industrial data lake benefits?
Data lake is also implemented using the Internet of Things. IoT harnesses the capabilities of the cloud and interconnects machines that are embedded with sensors and sophisticated software. The data lake provides both enterprise and industrial enterprise solutions. It can also perform basic design review, exploration, and testing. This results in production and storage of real-time data, which gives a new context and decision-making directions. Machine learning and automation are also helping businesses in taking accurate business decisions. Thus, the scalable data lake and IoT, along with predictive analytics, are increasing sustainability of devices and optimizing resources, thereby transforming the façade of our technological innovations.
In today’s healthcare industry scenario, a vast amount of data that gets produced is still stored in relational structures or gets pulled out into relational forms. The data lake is the new found solution to replace the relational data warehousing architecture. A data lake consists of a flat architecture and capacity to hold huge volumes of raw data. This raw data is stored in its native format until someone queries for that data. This data modelling approach is allowing medical researchers and doctors to pull out structured datasets, along with unstructured data like clinical pretexts and notes. Thus, implementing a data lake approach can speed up the data retrieval processes and content gets deployed from multiple sources easily.
The solar engineering and clean energy market have been working to find out ways to sift the growing pools of information and make big data analysis on basis of that information. By using a data lake, they are able to store all the raw data in its original format and sift through it when needed. This has made processing information two thousand times faster and ten times cheaper than existing traditional methodologies. Thus, a data lake provides a centralized, low-cost, and fast access to information, thereby helping maintain and improve a company’s operational processes.
The data lake has delivered its promise of speeding information retrieval and giving appropriate insights into the market without hassles inflicted by IT-centric data warehousing processes. There is a huge potential in industrial applications of data lake, and the above data lake benefits are just the beginning.