Benefits of Data Store Solution for Your Company

Marcin Nowak
February 28, 2024

Imagine having $10 million in cash, but having to carry it around on you all the time. Imagine paying for petrol and a bag of potato chips $52 at a gas station, and reaching to your $10 million money bag to grab a bank note. Having $10 million is always nice, but if you have to carry it around, it becomes troublesome.

That's how data works. You want to keep your precious historical data stored safely on data storage devices, but you don't want to carry it around wherever you go. Meaning, you don't want your systems and processes query the whole database each time.

That's where Operational Data Store comes in. Using only data you require at the moment, while keeping historical data, makes you faster and agile.

The Definition of Operational Data Store

An Operational Data Store (ODS) is a centralized repository that collects and integrates data from various source systems within an organization for reporting and data analysis purposes. It is designed to facilitate timely access to up-to-date information supporting day-to-day operational decisions and functions. 

Unlike data warehouses, which are optimized for analyzing historical data, an ODS focuses on current or near-real-time data to support operational processes. It maintains a broad overview of an organization's operational data, allowing for detailed reports that reflect the current state of business activities. 

This enables organizations to respond quickly to changing operational requirements and supports activities such as customer service, disaster response, and internal operations oversight. The ODS serves as a dynamic environment where data is refreshed frequently to ensure accuracy and relevance for operational reporting and decision-making.

Key Characteristics

Key characteristics of data stores encompass scalability, to support growing data volumes; flexibility, to handle different data types including structured, unstructured, and semi-structured data; and performance, ensuring data can be accessed, updated, and managed efficiently. These features are foundational to supporting the dynamic needs of insurance and finance industries, where data volume, variety, and velocity are constantly increasing.

Characteristic Operational Data Store (ODS) Data Warehouse Data Lake
Primary Purpose Support day-to-day operations with up-to-date transactional data Aggregate and organize data from various sources for analysis and reporting Store vast amounts of raw data in its native format until needed
Data Freshness Real-time or near-real-time Historical, batch updates Real-time to historical
Data Type Structured, occasionally semi-structured Highly structured Structured, semi-structured, and unstructured
Users Business professionals for operational reporting and decision making Analysts and decision-makers for strategic planning Data scientists, analysts for exploratory data analysis
Query Speed Fast, optimized for quick reads and writes Varies, optimized for complex queries over large datasets Slower, due to the volume and variety of data
Storage Cost Moderate, depending on the volume of transactional data High, due to large volumes of historical data Lower, raw data stored without transformation
Optimization For transactional processes, fast queries For analysis, reporting, complex queries For data mining, machine learning, deep analytics
Use Case Operational reporting, customer service, real-time monitoring Business intelligence, trend analysis, strategic decision making Big data processing, machine learning models, data discovery

Benefits of Implementing a Data Store Solution

Improved Data Quality and Availability

Implementing a data store solution significantly enhances the quality and availability of data. By consolidating data into a single, coherent system, data stores minimize inconsistencies and errors, thereby improving data integrity. Real-time data processing capabilities ensure that data is readily available, supporting timely and informed decision-making critical for the insurance and finance sectors.

Enhanced Data Management and Analytics

Data store solutions facilitate advanced data management and analytics by providing robust tools and frameworks for data integration, processing, and analysis. This enables businesses to uncover actionable insights, optimize operational efficiencies, and drive strategic initiatives. For insurance companies, this means better risk assessment, personalized policy offerings, and improved customer service.

Cost-effectiveness and Scalability

The adoption of data store solutions offers cost-effectiveness by leveraging economies of scale associated with cloud storage and virtual storage technologies. This reduces the need for expensive physical storage infrastructure and maintenance. Additionally, the scalable nature of modern data storage solutions allows businesses to adjust their data storage capacity based on current needs, ensuring they are not paying for unused resources.

Security and Compliance

Data security and regulatory compliance are paramount in the insurance and finance industries. Data store solutions provide advanced security features, including encryption and access controls, to protect sensitive information against unauthorized access and breaches. Compliance with regulatory standards is also ensured through comprehensive data management policies and procedures, aiding in the adherence to industry regulations and standards.

Disaster Recovery and Business Continuity

An essential benefit of data store solutions is their role in disaster recovery and business continuity planning. By enabling reliable storage and backup of data, these solutions ensure that critical business data can be recovered swiftly after any disruptive event, minimizing downtime and ensuring continuous business operations.

Operational Data Store Solution for Insurance - Decerto

Introduction to Decerto’s ODS Solution

Decerto offers a state-of-the-art Operational Data Store Solution specifically designed for the insurance industry. This solution is tailored to meet the unique data management and analytics needs of insurance companies, facilitating real-time data processing, seamless integration with existing systems, and advanced analytics capabilities.

Key Features and Advantages

The Decerto Operational Data Store (ODS) solution offers a range of benefits designed to enhance the efficiency and security of data management for insurance companies:

  • Data Security - At the heart of the Decerto ODS is a strong commitment to data security. This includes measures to prevent the accumulation of customer data in logs, encryption of sensitive information in messages, and the use of secure login methods such as Single Sign-On (SSO) and OAuth2. Connections to Decerto applications are encrypted, adding an extra layer of security. The approach has earned high ratings from independent security audits, underscoring its reliability and trustworthiness.
  • Scalability - The architecture of Decerto's products is designed with scalability in mind. By building products to be either stateless or capable of synchronizing their state using external tools like databases or queues, Decerto ensures that deploying multiple instances of each module is straightforward. The use of Kubernetes allows for dynamic control over the number of instances based on system load, facilitating efficient scaling in response to demand.

Conclusion

Throughout this discussion, we've navigated the complex landscape of data storage, from the foundational storage devices to the advanced realms of storage virtualization and relational databases. We've seen how the integration of multiple physical devices and sophisticated storage systems can enhance data accessibility and reliability, supporting a wide range of business processes. The contrast between single data store solutions and the deployment of multiple devices highlights the flexibility and scalability that modern enterprises require.

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