Essential elements of a Data Lake and Analytics solution

Data is the business asset for every organisation which is audited and protected. Data can be any form such as structured, semi-structured and unstructured. To handle any kind of the data, Data Lake comes in the picture as a centralized repository to store the data as-is (relational data from line of business applications, and non-relational data from mobile apps, IoT devices, and social media). The types of raw data that are stored in a data lake can include:

• Audio, images and video
• Communications (blogs, emails, social media, click-streams)
• Operational data (inventory, sales, tickets, tourism)
• Machine-generated data (log files, IoT sensor readings)

The most importantly, data lakes are specifically designed to run large scale analytics workloads in a cost-effective way. Within Data Lake, the necessary data is made available to all levels of employees, irrespective of their level or the designation.

Essential Elements of a Data Lake are:

Data Lake Analytics allow various roles in your organization like data scientists, data developers, and business analysts to access data with their choice of analytic tools and frameworks.