Data modernization services: Upgrading your stack

Legacy systems can really hold you back, causing slow decision-making, broken pipelines, and a lack of confidence in your own data.

Data modernization services help you update and improve your underlying infrastructure, bridging the gap between outdated legacy systems and agile cloud-native architecture.

In this guide, we explain what data modernization services are and why they’re important, and share a few examples of popular tools on the market today.

What are data modernization services?

Data modernization services are solutions offered by third-party companies that evaluate and improve the status of your data architecture. Since modernization is a complex process requiring careful planning and deep technical knowledge, these services can dramatically speed up your move away from legacy systems.

Different companies have different approaches, but some broad services they’re likely to offer include:

• Data integration: Extracting data from different sources and loading it into a centralized platform. Reliable and automated ingestion pipelines are a big part of modernization, helping to eliminate data silos.
• Data cleansing: Identifying and fixing errors and normalizing incoming data. These transformations ensure information is accurate, improving analytics and boosting trust in company data.
• Data warehousing: Centralizing and democratizing content into cloud-based storage optimized for reporting and scalability. Cloud data warehouses (and, increasingly, data lakes) offer flexibility and scalability and can deal with larger data volumes.
• Data governance: Establishing policies and controls for accuracy and compliance. These ensure your content remains trustworthy and aligns with regulatory requirements.

Why is data modernization important?

Legacy systems were built for a different era of business. Modern workloads require split-second decisions, real-time insight, and high volumes, velocities, and varieties of data.

By modernizing your data architecture, you can break down data silos, centralize your content, and scale your systems to your needs through cloud resources. Here are a few core reasons why modernization is so important:

• Endless scalability: Modernizing to cloud architecture means you can take advantage of on-demand provisioning. If you need more space or computing power, the system will scale to meet demand without affecting performance.
• Cost reduction: Modernization unlocks usage-based pricing — you’ll only pay for what you use and can cut back on infrastructure provisioning and maintenance costs.
• Real-time decision-making: Removing legacy systems allows you to move away from batch pipelines and embrace continuous data movement. You’ll be able to deliver insights to your analytics engines in near real-time, facilitating timely data-driven decision-making.
• AI and ML readiness: To produce accurate predictions, AI systems rely on huge amounts of training data. Modernization comes with better governance, structure, and data processing setups, meaning higher-quality content to feed into these systems.

Top 3 data modernization services

Data modernization solutions identify the best ways of updating your existing architecture, mapping out key strategies, technical requirements, and migration protocols. To help guide your efforts, we’ve selected three companies that offer some of the most popular cloud modernization services on the market.

Accenture

Accenture offers comprehensive modernization services across strategy development, cloud migration, embedding analytics, and AI readiness. Gartner named Accenture a Leader in its 2026 Magic Quadrant report for Digital Technology and Business Consulting Services.

Beyond just moving companies away from legacy solutions, Accenture builds tailored solutions designed to unlock the most growth for businesses in the future. This includes full governance and security considerations, keeping you aligned with regulatory requirements throughout any infrastructural change. The company even maps out how best to wrangle and engage with your data, with ingestion and transformation tools that streamline data movements.

Deloitte

Through its Data Modernization and Analytics service, Deloitte provides strategic updates for businesses looking to unlock their data’s full potential. It focuses on building reliable pools of data that organizations can use in analytics engines to support data-driven decision-making. By modernizing legacy environments with cloud-native solutions like Snowflake, Databricks, Google Cloud, Azure, and AWS, Deloitte ensures your company always has the resources it needs to meet demand.

Deloitte’s expertise allows you to implement automated, governance-first systems across your infrastructure. If you’re looking to implement AI systems, Deloitte also offers consulting packages to make sure you hit the ground running.

Cognizant

Cognizant provides cloud migration, cloud-native app and web development, and full DataOps implementation support. The company’s end-to-end approach means your business gains access to consistent, high-quality data that you can use in analytics, AI initiatives, and decision-making.

While operational strategy is important to Cognizant, the company specializes more on the technological side than others on this list. It has an expansive range of partnerships and tools in place, helping you move to the cloud, reduce costs, and improve your infrastructure. 

Build a reliable data pipeline with Fivetran

Data modernization services can help you plan and execute your move away from legacy systems, but your architecture will only ever be as effective as the information you feed it. 

Fivetran offers end-to-end, fully managed data pipelines that deliver high-quality, accurate data. The platform handles schema drift, incremental updates, and connector maintenance completely automatically, giving your engineers more time to focus on analytics and creating value from your data. 

Level up your modernized infrastructure even further with Fivetran Reverse ETL (rETL). Rather than insights sitting unused in your data warehouse, rETL allows you to push trusted, centralized data back into your operational systems, like Hubspot or Salesforce. By looping in dashboards and the insights generated within them, this gives your teams even more visibility over their modern data stack.

Discover why Fivetran is an invaluable part of modern data stacks by arranging a demo today. 

FAQs

How does data integration work within platform modernization?

Data integration is the process of extracting data from sources like databases, SaaS apps, and IoT sensors and loading it into a warehouse or other storage facility. Modernized architecture uses automated platforms like Fivetran to provide you with fresh data with no need for manual or batch jobs.

What are the 5 R’s of modernization?

The five R’s of modernization each refer to a different method of moving a legacy app to the cloud. They are:

• Rehosting
• Replatforming
• Refactoring
• Rearchitecting
• Rebuilding

Some services use one approach more than the others. For example, application modernization services generally opt for a replatforming strategy.

How long does a database modernization project take?

The length of a modernization project depends directly on the total volume of data you’re migrating, whether there are any complexities to consider (like dependencies and legacy components), and how prepared your company is to modernize. Small projects in more agile companies can be done in a few weeks, but larger ones could take upwards of a year.

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