Cloud Data Lakes

Cloud data lakes can help innovatively address several complex business scenarios by processing, transforming, and analyzing large volumes of messy, complex data from a variety of sources including ERPs, sensors, and social media.

We are now in data-driven era and playing with internet, new devices, social media and the power of algorithms have had a major impact in our behaviors, transactions and conversations. 

This has impacted the kind of data we generate; organizations across industries are now tracking and monitoring this data to gain a competitive edge in the rapidly evolving environment.

Data provides a wealth of insights--rich, layered, multi-dimensional, and in volumes that we couldn’t have envisaged just a few years ago. Operations, processes, employees, consumers, products and assets generate petabytes of structured and unstructured data that can be processed and mined for business impact and value.

Advantages of cloud data lakes

Conversations on cloud, big data, machine learning are moving towards standardized, accessible, cost-efficient and scalable platforms ready to tap into demand across industries. Data warehouses have traditionally been considered as powerful tools to house data; however, now the focus has shifted to cloud data lakes, which provide an integrated enterprise solution that can not only store, but also process data and create a consumption layer to drive better business performance.

Cloud data lakes offer several business benefits, including:

• Handling the uncertainty caused by various types of data, and the ambiguity triggered by the availability of data.
• Planning investments and overall data strategy more effectively, with targeted investments.
• Offering a low barrier to entry for even small-to-medium enterprises, increasing their appetite and ability to test solutions in a relatively risk-free environment.
• Driving business outcomes and adoption of new solutions through rapid prototyping and experimentation.
• Cloud data lakes can help innovatively address several complex business scenarios by processing, transforming and analyzing large volumes of messy, complex data from a variety of sources including ERPs, sensors and social media. For example, data lakes can support financial services by creating a single source of truth across a complex landscape of multiple core business systems, allowing for improved data integration and governance and shorter turnaround times.

Navigating challenges

Change Management: Ensure early communication and stakeholder buy-in across departments ranging from IT and other support functions to help drive adoption. End-users should be onboarded onto the platforms with full visibility into all the advantages on offer and how to leverage the various functionalities to deliver maximum value

Cloud expertise: Cloud computing and storage are skill areas which require dedicated teams for design and implementation

Domain expertise: The cloud experts should be closely integrated with business units to guarantee the full range of value of business solutions.