Challenges to Implementing a Modern Data Architecture
Data and analytics platforms built in the cloud are the foundation and accelerant for nearly every digital transformation strategy. That’s why many insurance organizations are migrating their business data to the cloud.
While there are many benefits to be gained – like access to real-time data, modernization of services and goods, and increased customer satisfaction – implementing a modern data integration framework isn’t easy.
What are the top challenges to implementing a modern data architecture?
Real-time change data capture (CDC)
Keeping data up to date, accessing and processing data in real-time
Shortage of skills and staff who have an understanding across cloud and legacy technologies
Making data accessible to users across the business
Spending on maintenance and not innovation
Poor data quality and lack of trust in data
Difficulty leveraging data from legacy systems (mainframes, EDWs, IBM i etc.) with modern cloud platforms
Ability to scale with and process massive data volumes
of newly created data records have at least one critical error
The key to cloud migration success?
With a foundation of data integrity, you:
Break down data silos by connecting traditional systems, such as mainframes, to next-wave technologies in minutes
Gain real-time data delivery to feed business applications and analytics
Design once, deploy anywhere to future-proof your business with easy to-use GUI and self-tuning engine – no coding or tuning needed
Drive innovation with mainframe expertise. Directly access and understand VSAM files, COBOL Copybooks, IMS, mainframe fixed and sequential files, and Db2 data.
Ensure data accuracy and context by building data governance and quality into your data-centric processes