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By Sachin Arora, Partner and Head, Lighthouse, KPMG in India

The world is rapidly transitioning to a data-driven era. The rise of the internet, new devices, pervasiveness of social media and ‘meme’ culture, and the power of algorithms have had a major impact in our behaviours, transactions and conversations. This, in turn, has impacted the kind of data we generate; organisations 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.

Take the Know Your Customer (KYC) process at any financial institution. What was once a static, form-filling exercise to collect demographic information has now been transformed into a dynamic, real-time data-gathering process. Through multiple channels (websites, mobile apps, chatbots), institutions reach out to customers either explicitly soliciting or implicitly gathering information on location, lifestyle choices, personal and professional interests, commercial transactions etc.

While providing visibility into previously unknown facets of the decisions and operations of customers, data offers opportunities to innovate and pilot solutions across sales and marketing, customer experience, operations and drive returns on investment (ROI).

 

Advantages of cloud data lakes

Conversations on cloud, big data, machine learning are moving towards standardised, 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 analysing large volumes of messy, complex data from a variety of sources including  ERPs, sensors and social media.[NS1]  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 (TATs). 

Drivers of cloud adoption

For businesses to remain competitive and productive, digital transformation is the need of the hour, especially in the wake of the COVID-19 pandemic. The crisis is driving clarity in technology investments, with 56 per cent of global enterprise leaders agreeing that cloud migration has become an absolute necessity, according to the Enterprise Reboot survey conducted by KPMG International and HFS Research. The report, in which 56 of the 900 companies surveyed were from India, points out that many enterprises are “zeroing in on mature technologies such as cloud, automation and analytics that will drive quick ROI” as they plot a path towards recovery.1

The ease and simplicity offered by many platforms are driving rapid adoption. Cross-cloud integrations further strengthen the infrastructure, while adhering to evolving privacy regulations.

Navigating challenges

To seamlessly ensure adoption, businesses would need to address the following implementation 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.

Cloud is the ideal platform for leveraging data effectively to drive experimentation. Evaluating options carefully and assembling the right teams would enable better informed and faster decisions in order to survive and sustain in a rapidly evolving environment.

  1. Enterprise reboot, 2020 Global Emerging Technology Survey Report, KPMG International and HFS Research, August 2020