Data Lakes and Digital Implementations

Array of mammoth demands are gradually built on insurance enterprises over the past couple of years, not just by the pandemic alone. Radical disruptions in digital technology, dynamic expectations of evolving tech-savvy customers on an everyday basis, insurance value chain uprisings, evolving digital technology developments, all have had their own part to play. Insurance experts recommend every one of today’s enterprises to try every means to convert their mammoth mines of generated everyday data into precious, insightful assets to gain productive business outcomes. To do this, today’s highly advanced digital technology protocols recommend strengthening insurers’ data repositories into data lakes. Data lakes are the perfect platform for any enterprise to optimally utilize their digital analytics, and AI/ML implementations.

The power of data lakes

Insurance and technology specialists go one step further to reiterate the tremendous power that data lakes wield as the fundamental steppingstones for tactical data management. Today’s fast-moving digital technology world and analytics and AI/ML and ecosystem implementations call for capturing varied ranges and categories of data. They are far unlike traditional database management systems that simply rely on inflexible database infrastructure capturing only internally generated data with pre-determined layouts. Data lakes on the other hand facilitate sourcing data from disparate data locales, ability to flexibly manipulate and play around with the sourced data. They provide those powerful business insights thus assimilating elementary data access for crucial decision-making. Business orientation, with a keen customer requirement focus is the main aspect that has provoked today’s insurers’ to go in for data lake implementations. Data lakes are those robust data repositories that allow today’s insurance enterprises to proactively predict the exact channel independent customer requirement(s) even before they themselves are aware of it.

Data lakes have become the very basis for going digital

For instance, if an enterprise intends to diversify its business line with newer opportunities using their data repository and ML technology, consolidating their data into data lakes is the best bet. Data lakes render an aspect of continuity of data supply providing users with the precise data they need at the right time, based on the usage. They in fact facilitate an insurer the flexibility to probe their data and capture valuable business insights in terms of claims pattern or customer’s activities. Data Lakes have now become the very foundation on which seamless customer and user experiences (CX and UX) are being built. Data lakes leverage on the simulated real-time practices using their data as well as analytics implementations. There are now an increasing number of insurance enterprises who have migrated from massive, siloed data into the most upbeat and Nordic model data repositories in the form of data lakes.

Data lakes, key for enterprise evolvement, especially insurance

Data lakes no doubt has emerged the sole key to every digital implementation of a global enterprise. Especially for insurances enterprises that churn out massive data on an everyday basis, data lakes have turned out to be the most economic data storage solutions. Data lakes combine the potentials of analytical tools, basic hardware commodities, and the unified technology bundles of open-source data. For today’s global insurance enterprises data lakes are main migration solution to the next generation of data storage, warehousing and analytics technology implementations. Data lakes leverage on complex, high tech analytics algorithms to churn out precise real-time business insights from all fundamental insurance processes and for all insurance users. They have now emerged as the crucial platform on which newer business opportunities and insurance products are being launched.

Innovative data lakes technology, instantly spot your customers

The other crucial aspect of data lakes implementation for a global enterprise is to spot and facilitate customer and market capture. Many global insurers with massive portfolio of customer base types, use data lakes technology to build market and customer prediction models that can easily execute complex minimum viable product (MVP) based algorithms. The basic raw material for any MVP execution is the data lakes that provide their analytics, AI and ML solutions with just the most precise data from diverse data sources. Data lakes also provide them with the much-needed data experimentation and democratization flexibility.

Valuable insurance business insights like never

Data lakes implementation thus have brought in business insights generation to a next newer level of technology capability. Customer and market predictions are now an integrated technology stack of internal enterprise level predictions, and real-time, customer interaction-based predictions. They provide even those crucial business insights based on organizational structure and the necessary updates required to be adopted in the business. Many of the crucial areas where data lakes greatly radicalize business processes include:

• Instant flexibility in productizing and pricing
• Sales and marketing process optimization
• Augmented CX and real-time 24X7 customer interaction flexibility