Data Insurance

The Importance of Having a Modern Data Platform

Data has become the gamechanger in the age of digital transformation, as enterprises today are racing to leverage data and drive competitive advantage. While tech-savvy newcomers are disrupting the industry with technology that maximizes data capabilities, many enterprises are still struggling with traditional technologies that offer limited capabilities and an infrastructure that doesn’t support speed.

In the digital era, it is crucial for organizations of all sizes to become data-driven, not only to derive insights, but also to drive business outcomes at speed. For insurers, this means looking at data to develop and roll out new and personalized products and services quickly; optimize internal processes to increase efficiencies; and apply analytics to decrease risk and grow market share. In order to drive these business outcomes, it is essential for insurers to modernize their data environment. But how can insurers start on this modernization journey? Here’s a 3-step framework to guide you on your path to a modern data platform in insurance.

3-Step Framework to a Modern Data Platform 

Transforming the data environment to support business growth requires insurers to fully address the data challenges in their organizations. For most insurers, this comes down to addressing three major parts: the data architecture, the data management practices, and the data warehouse capabilities.

3-Step Framework to a Modern Data Platform

  1. Employ Data Architectures

    Many insurers continue to operate on legacy systems, on-premise servers, and siloed data in various formats that are not efficiently accessible by the right parties at the right times. Though the capacity to collect real-time data has improved with the development of artificial intelligence (AI), legacy sources largely fail to process the variety of data that is becoming more available to insurers. Insurers must employ data architectures that can store an array of both traditional and nontraditional data. This includes but is not limited to: paper forms, smartphones, videos, wearables, drones, and more. An effective data architecture will allow insurers to scale their data up and down based on business needs.

  2. Streamline Data Management

    Along with the ability to store vast amounts of data, insurers struggle with management of data. Organizing multiple data streams—including both historical enterprise data and third-party sources—and enabling analysis can be time-consuming and labor-intensive. AI-powered automation and machine learning will be crucial to streamline data management. Insurers will further benefit from advanced delivery methods such as Agile and DevOps to advance their data management systems, maximize continuous integration/continuous delivery, and accelerate speed-to-market for new capabilities. Ultimately, insurers must centralize data access, curate raw data for business analytics, and ensure security and compliance for proper management and utilization of data.

  3. Adopt a Data Warehouse

    As data sources and data volume increase, the ability to scale storage and access innovative tools for data computation becomes more and more necessary to compete. While Insurtechs have been employing data technology early on to disrupt legacy companies in the industry, insurers have been slower to adopt new technology. This trend is changing, however, as incumbent insurers are employing cloud technology and transitioning to cloud infrastructures to support their data initiatives. Cloud data warehouses are a platform many are considering or taking up to leverage their varied data sources and the new technologies in AI and ML to maximize data analytics.

One Insurer’s Journey to a Modern Data Platform  

A regional property & casualty insurance company thought through their data architecture, data management, and data warehouse as they set out to increase data accessibility and provide cloud-specific tools for their business users to leverage data. With on-prem SQL servers and data warehouse, over 4 terabytes of data, 200+ tables of data and some tables with over 1 billion records, the insurer wanted to migrate their data to the Snowflake Cloud Data Warehouse in order to leverage cloud tools for data analytics.

  • The Project: Data Migration to the Cloud
    To migrate its data to the cloud, the insurer needed to develop a proper cloud infrastructure to store and access data. With the desire to complete the migration in three weeks’ time—a time frame that is challenging given the size and complexity of their data—the insurer partnered with the ValueMomentum DateLeverage Team to help set up, configure and provision the Snowflake data warehouse for the data migration.
  • The Process: Provisioning Accelerators
    The ValueMomentum Data team created a data structure in Snowflake to house the insurer’s legacy data. Then three accelerators were built, which were provisioned to understand the location of the SQL server, name of the data warehouse, its destination of migration, and rapidly sort through and make sense of the varieties of data.The accelerators were implemented in a dry run test to identify any bugs or issues and fix them before the actual data was moved to the live environment. Then, through automation, the accelerators performed the data migration end-to-end with no manual intervention or input. From inception to execution, the accelerator was able to move 200+ tables of data in five days—a process that is 20 times faster than the normal pace.
  • The Benefits: Open Access
    With their data efficiently migrated to a cloud data warehouse, the regional insurer can now apply their data management processes, leverage AI-based tools for analytics and democratize access to their data, encouraging more business users to look at data to derive insights and drive business decisions.

The Future of Data Modernization 

Insurers understand that data is key in the age of digital transformation. As they race to modernize their data environment and make use of the incredible diversity of data, equipping themselves with the right data architectures, sufficient processes and systems to manage their data, and innovative platforms and tools to store and apply analytics will put them in a better position to stay competitive and drive business success.

Ready to jumpstart your Data Modernization? Check out ValueMomentum’s Modern Data Platform services to see how we can help you modernize your data platform and prepare you for data-driven success.