Cloud computing is the biggest innovation in the computing technology, which makes a splendid progress for the organisations searching for larger datasets to suffice their customers growing needs. After cloud computing, Big Data was the most emerging technology utilized and implemented by approximately 45% of the online organisations and big brands according an ICT survey of 2014. The ability of big data to work and manage large data sets leads many to think of improving acknowledgement of the retrieval of data requests and concept of Data Lake engineered to manage the growing prerequisites to handle data.
The Data Lake is a gigantic, easily available, centralized data warehouse of great volumes of structured and unstructured information. A heavy object-based storage repository holds data in its native format until it is required. The raw data is stored and served in its native format until the request. The Data Lake is assembling of data about data (metadata) where data instances (packets) can be plucked and served as per the requirements of database. The emerging demand for data lake technology arises because to manage large data sets of big data a collection of data was very important to acknowledge the petition.
The Data Lake architecture is built and store every single bit of data in an unstructured and raw format approaching to big data. Initial incoming data were not classified when it was stored in the origin. As a result, data preparation is eliminated. A data lake is thus unstructured compared to a conservative data warehouse. When the data is required only then the data packets were classified, organized or analysed to the acknowledgement. The working diagram of traditional data warehouses is different from the Data Lake, in traditional warehouse data was analysed and structured at the first time they enter and stored in the unique request with specific analysis and applications while data residing in lakes are still waiting for applications to discover ways to manufacture insights. A data lake uses a flat architecture to stock data. Each raw data element in a lake is allocated a unique metadata tag identifier to know the unstructured data to store large data sets.
The growing need of large databases for big platforms flexibly served from Data Lake because unstructured data identifier, and storage mechanism allow fast access of stored data instances in many ways for different platforms. The triangle of cloud computing, big data and data lakes concept is growing to serve multiple data channels with unrecognized value to manage incoming data. In a quickly rising world of big data, the Data Lake concept is gaining popularity and increasing exponentially. Data Lake is useful to lower the costs of storage, the ability to store more data types, scale multiple data types, advanced capacity, data analysis and designed and deployed to reduced risk for future data management.
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