Technological Benefits of Data Lakes

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.

All-around Availability of Data — This is the biggest advantage of the Data Lake implementation for any organisation because it gives a surety that all the employees, irrespective of their designation and roles, can have access to data and this term is known as data democratization.

Fetches Quality Data — Data lakes implementation supports many tools and technologies which gives a tremendous data processing power for fetching quality data such as —

Real-time decision analysis — Data lakes take advantage of large quantities of consistent data and deep learning algorithms to arrive at real-time decision analytics by the help of many supportive languages.

Supports SQL and other languages — Conventional data-warehouse technologies support SQL which is good enough for simple analytics. For advanced analytics, other languages are PIG, Hive, Tachyon, Impala and for machine learning, Spark MLlib is over there also.

Operational Analytics Monitoring— Data lakes have all kinds of great benefits for companies, data managers, and data processors. However, with a Data Lake, the necessary data is made available to all levels of employees, irrespective of their level or the designation. Search, explore, filter, aggregate, and visualize business data in near real-time for application monitoring, log analytics, and click stream analytics are easy tasks in Data lake. Just as in the case of Twitter, business user decides whom he wants to connect with or not to connect with, likewise in the case of Data Lakes, a user could choose the required data to meet different business objectives.

Scalable, Versatile and Schema Flexibility- This is the another biggest advantages of Data Lake that data volumes are growing exponentially day by day and unlike traditional data warehouse, Data Leaks offers scalability and is inexpensive as well. There are many technologies (AWS, Azure, Google Cloud etc.) now a days to help you to reduce the cost of your compute usage, like auto-scaling and integration. A data lake can store your versatile data such as XML, logs, multimedia, sensor data, chat, social data, binary, and people data from diverse sources. Hadoop Data Lake enables us to be schema free, or we could come up with multiple schemas for the same data. Meanwhile we can easily separate schema from data, which is good for analytics.