Why it's important to unify data into a single data store

Top 10 Reasons to Unify Data Into a Single Data Store

Published March 2023

Often companies find themselves with data stored in disparate data stores.  The use of legacy systems and subdivisions within a company using their own systems are two common reasons for this scattered data storage.  In this article we explain 10 reasons why it is important and beneficial for companies to unify data from disparate sources into a single data store.

#1 Improved Decision Making

A unified data store provides a single source of truth for business operations, which enables organizations to make better-informed decisions. A retail company, for instance, can use a single data store to analyze sales, inventory, and customer data to identify trends and improve their products and services.

#2 Better Data Accuracy

Unifying data from different sources ensures data consistency, reducing the risk of errors and improving the quality of data. For example, an e-commerce company can use a unified data store to manage customer data across multiple channels, ensuring consistency in customer profiles.

#3 Increased Efficiency

A unified data store reduces the need for manual data integration, saving time and resources. A healthcare organization can use a unified data store to manage patient data across multiple departments, reducing the need for manual data entry.

#4 Improved Collaboration

A unified data store enables teams to collaborate more effectively, leading to better outcomes and increased innovation. A marketing team can use a unified data store to access customer data from sales teams, enabling them to develop targeted marketing campaigns.

#5 Enhanced Data Analysis

Unifying data from disparate sources enables businesses to analyze data more effectively, identifying insights and opportunities for improvement.  A logistics company, for instance, can use a unified data store to analyze data from different sources, such as shipping data and inventory data, to optimize their operations.

#6 Increased Agility

A single data store enables organizations to quickly adapt to changes in the market, reducing response times and improving competitiveness.  A financial services company can use a unified data store to quickly respond to market changes and adapt their services accordingly rather than access many data stores and piece the information together afterwards.

#7 Improved Customer Experience

A unified data store enables organizations to create a complete view of their customers, which can help them provide better products and services. A telecommunications company can use a unified data store to manage customer data from different channels, such as mobile and internet services, to provide a better customer experience.

#8 Simplified Compliance

A unified data store helps organizations comply with data privacy regulations by providing a single point of control for data management.
For example, a banking company can use a unified data store to manage customer data in compliance with regulations such as GDPR or CCPA.

#9 Reduced Costs

Unifying data can help reduce the costs associated with maintaining multiple databases, reducing infrastructure and management costs. A manufacturing company can use a unified data store to manage production and inventory data, reducing the need for separate databases for each department.

#10 Improved Data Security

A unified data store helps organizations ensure data security by providing better visibility and control over data access and usage. For example, a government agency can use a unified data store to manage sensitive data across multiple departments, ensuring data security and compliance.

Have OpenSearch Questions?

Managed OpenSearch on your environment with
24/ 7 support.

Consulting support to implement, troubleshoot, and optimize OpenSearch.

Schedule a call with a OpenSearch solution architect.

Published by

Dattell - Kafka & Elasticsearch Support

Benefit from the experience of our Kafka, Pulsar, Elasticsearch, and OpenSearch expert services to help your team deploy and maintain high-performance platforms that scale. We support Kafka, Elasticsearch, and OpenSearch both on-prem and in the cloud, whether on stand alone clusters or running within Kubernetes. We’ve saved our clients $100M+ over the past six years. Without our guidance companies tend to overspend on hardware or purchase unnecessary licenses. We typically save clients multiples more money than our fees cost in addition to building, optimizing, and supporting fault-tolerant, highly available architectures.