Abstract

With the increase in high volume, velocity, and variety of data, the traditional data analysis approaches are not adequate to handle diverse analysis challenges. Traditionally, a data warehouse is being used which is an integrated repository from various sources used for management and decision-making in business. Data is already in a transformed and structured format stored in a costly but reliable storage device. The data warehouse does not include all the data that may be not required at the time of construction of the data warehouse. With the advent of big data and to handle the data silos problem, the concept of Data Lake is introduced to handle data analysis. Data lakes have not replaced the data warehouse but rather complement it. In this chapter, firstly Data Lake is introduced and compared with predecessor technologies, then various tools and techniques are discussed to implement Data Lake.