Data Platform Enablement to overcome Data Fragmentation

How a multinational European Insurance powerhouse transformed its data platform to serve the entire business

The Challenge

Integrating data from various entities and business systems is a complex and time-consuming process. Organizations often struggle with differences in data formats, technologies, and communication protocols, making it difficult to consolidate, analyze, and leverage information effectively.

Faced with the reality of the lack of a unified platform, the European insurance company had issues with streamlining operations, ensuring data accuracy, and enabling real-time analytics.

This fragmentation led to inefficiencies, and a lack of a single source of truth for critical business processes. The constant scramble to always validate the data also resulted in project delays and revisiting data consistently to ensure quality and trust.

The Solution

Developing an on-premises Data Platform using Cloudera CDP, integrating various technologies to support efficient data processing and querying.

To address these challenges, Agile Lab played a key role in designing, supporting, and implementing an on-premises Data Platform for the client, based on the Cloudera CDP stack.

This solution was developed in an elaborate 7-step process from capturing real-time data streams to  comprehensive data analysis enablement.

Powering Digital Transformation through Data Platform Enablement

ICONA UP ARROW
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ACCELERATED DECISION-MAKING
ICONA MISSION
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COST SAVING
ICONA ROCKET
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DATA QUALITY IMPROVEMENT
Accelerated Decision-Making

Data-driven organizations are three times more likely to report significant improvements in decision-making speed, helping them to respond faster to market changes

(Source: HARVARD BUSINESS SCHOOL)​

Cost Saving

Data Platforms can allow companies to realize cost savings of up to 15% through minimized redundancies, optimized resource utilization and streamlined processes.

(Source: McKinsey&Company)​

Data Quality Improvement

Companies focusing on structured data management can improve data accuracy and consistency by 10-20% through centralized data platforms

(Source: McKinsey&Company)​

Step 1: Capturing Real-Time Data Streams

Together with our client, we began by leveraging Kafka to capture real-time data streams. This enabled immediate processing and distribution of event-driven data, providing instant access to dynamic information.

 

Step 2: Integrating Structured Data

Next, our combined teams used Sqoop to extract and import structured data from relational databases. Legacy systems integration became possible with this, consolidating structured data into the client's platform and enhancing overall data completeness and consistency.

 

Step 3: Orchestrating Complex Workflows

NiFi was then employed to orchestrate complex workflows and manage data flows efficiently across the platform. This way data moved smoothly through the system, allowing for efficient processing of diverse data types.

 

Step 4: Robust Data Storage

Once acquired, data was stored in HDFS (Hadoop Distributed File System), providing robust and scalable storage capable of handling both structured and unstructured data. With a centralized repository, all data was securely stored and easily accessible, supporting scalability and reliability.

 

Step 5: Real-Time Operational Insights

Next, HBase served as an Operational Data Hub, facilitating fast, real-time access to operational data. Quick retrievals of critical information became possible, which supported immediate insights and decision-making.

 

Step 6: Advanced Search Capabilities

To further enhance data accessibility, Solr was integrated to manage the indexing process, allowing for fast and advanced searches. This feature significantly improved data discoverability, making it easier for users to find the information they needed quickly.

 

Step 7: Comprehensive Data Analysis

Finally, we utilized both Hive and Impala for data retrieval and analysis. Hive supports batch querying, handling large-scale analytical queries efficiently, while Impala enables interactive querying, providing users with real-time insights to support quick decision-making.

This dual capability ensured that our client could conduct both in-depth analysis and generate insights quickly, supporting a wide range of business needs.

Results breakdown

A high-performing data platform

Strategy

Improved Data Management Strategy

With a significant transformation in the customer's data management strategy, and by leveraging real-time analytics and operational efficiency, the organization was able to drive business growth through more informed decision-making.

The platform's ability to process data in real-time allowed for immediate insights, enabling the company to respond quickly to market changes and customer needs. This transformation not only improved data handling but also positioned the organization for long-term success by aligning its data practices with business objectives.

Internal Data Platform

A New and Fully Integrated Data Platform

The new Data Platform was seamlessly integrated into the organization's entire ecosystem, creating a centralized hub for all data-related activities. This integration was crucial in overcoming the challenges of fragmented data systems, which previously hindered operational efficiency and decision-making.

By consolidating data from various sources, the platform ensured that all departments had access to consistent and accurate information, fostering a unified view of the business. This integration also facilitated better collaboration among teams, as everyone worked from the same data foundation, leading to more cohesive business strategies.

Resource Allocation

More effective resource allocation

The improved data accessibility, accuracy, and consistency provided by the Data Platform enabled more effective resource allocation across the organization. With reliable data insights, managers could identify areas of inefficiency and allocate resources more strategically. This led to optimized operational processes, reduced waste, and enhanced productivity.

By making data-driven decisions, the company was able to maximize its resources, ensuring that investments were aligned with business priorities and market opportunities. This strategic resource allocation was a key factor in driving business growth and maintaining a competitive edge.

Specific use cases

Industry-specific use case development

The implementation of the Data Platform paved the way for the development of industry-specific use cases that directly addressed the customer's business needs. For instance, the platform supported claims management by providing real-time data on claims processing, allowing for faster resolution and improved customer satisfaction.

Additionally, back-office automation streamlined internal processes, reducing manual errors and increasing operational efficiency. Enhanced service provisioning for customers and the agency network was also achieved through personalized services and real-time updates, further solidifying the organization's position in the market. These use cases not only improved internal operations but also enhanced the overall customer experience, driving loyalty and growth.

Improved Data Management Strategy

With a significant transformation in the customer's data management strategy, and by leveraging real-time analytics and operational efficiency, the organization was able to drive business growth through more informed decision-making.

The platform's ability to process data in real-time allowed for immediate insights, enabling the company to respond quickly to market changes and customer needs. This transformation not only improved data handling but also positioned the organization for long-term success by aligning its data practices with business objectives.

A New and Fully Integrated Data Platform

The new Data Platform was seamlessly integrated into the organization's entire ecosystem, creating a centralized hub for all data-related activities. This integration was crucial in overcoming the challenges of fragmented data systems, which previously hindered operational efficiency and decision-making.

By consolidating data from various sources, the platform ensured that all departments had access to consistent and accurate information, fostering a unified view of the business. This integration also facilitated better collaboration among teams, as everyone worked from the same data foundation, leading to more cohesive business strategies.

More effective resource allocation

The improved data accessibility, accuracy, and consistency provided by the Data Platform enabled more effective resource allocation across the organization. With reliable data insights, managers could identify areas of inefficiency and allocate resources more strategically. This led to optimized operational processes, reduced waste, and enhanced productivity.

By making data-driven decisions, the company was able to maximize its resources, ensuring that investments were aligned with business priorities and market opportunities. This strategic resource allocation was a key factor in driving business growth and maintaining a competitive edge.

Industry-specific use case development

The implementation of the Data Platform paved the way for the development of industry-specific use cases that directly addressed the customer's business needs. For instance, the platform supported claims management by providing real-time data on claims processing, allowing for faster resolution and improved customer satisfaction.

Additionally, back-office automation streamlined internal processes, reducing manual errors and increasing operational efficiency. Enhanced service provisioning for customers and the agency network was also achieved through personalized services and real-time updates, further solidifying the organization's position in the market. These use cases not only improved internal operations but also enhanced the overall customer experience, driving loyalty and growth.

The Result

A high-performing platform with an integrated architecture and a new data management strategy.

 

By implementing this integrated architecture, the customer has successfully transformed its data management strategy, leveraging real-time analytics and operational efficiency to drive business growth. The Data Platform has improved data accessibility, accuracy, and consistency across the organization, enabling better decision-making and more effective resource allocation.

 

Furthermore, this architecture has paved the way for industry-specific use cases such as claims management, back-office automation, and enhanced service provisioning for customers and the agency network.

The Results Achieved for this Enterprise Insurance Customer
Cost Saving

Our approach resulted in lower storage, data integration costs and data transaction costs. This reduction in expenses has enhanced the organization's financial efficiency and resource allocation.​

Efficiency

We achieve streamlined Data Management processes and improved Governance by implementing structured guidelines and technical solutions. This led to smoother operations and better utilization of resources across the organization.

Stakeholders Confidence

Demonstrable improvements in Data Management increased stakeholder trust. This support was crucial for securing ongoing investments and resources for future Data Management initiatives.

Contact us today and get in touch with one of our Data Platform Experts to discover how our comprehensive solutions can streamline your data lifecycle and enhance efficiency across your organization.