Sangam17

Data lake is relatively a new term when compared to all fancy ones since the industry realized the potential of data. Industry is planning their way out to adopt big data lake as the key data store but what challenges them is the traditional approach. Traditional approaches pertaining to data pipelines, data processing, data security still hold good but architects do need to leap an extra mile while designing big data lake. This session will focus on this shift in approaches. We will explore what are the road blockers while setting up a data lake and how to size the key milestones. Health and efficiency of a data lake largely depends on two factors - data ingestion and data processing. Attend this session to learn key practices of data ingestion under different circumstances. Data processing for variety of scenarios will be covered as well.