In a world where data is the currency of innovation, enterprises are at a crossroads. AI is driving smarter insights, important decisions are happening in real time, and new regulatory mandates are pushing businesses to rethink their data architectures. The challenge? Legacy IT systems weren’t built for the agility, scale, or intelligence required today.
Businesses are making significant strides in data modernization as they adapt to evolving technology demands driven by data modernization services providers. The 2024 ISG Provider Lens™ Advanced Analytics and AI Services report highlights how data modernization companies are prioritizing cloud migration, automation, and governance frameworks to stay competitive.
Modernizing legacy data systems is no longer a back-burner project. With AI and real-time analytics driving rapid change, outdated systems can no longer keep up. Enterprises that fail to adapt risk being left behind in an increasingly dynamic market.
Gaining the Edge: Modernizing Data for AI Success
The next step of modernization is about aligning data strategies with tangible AI business outcomes for the race ahead.
The companies leading the way aren’t merely experimenting with AI; they’re making sure their data systems are ready to support it. Think of it this way: AI is only as good as the data it works with. Without modernized, streamlined data systems, businesses risk wasting time and money on AI that can’t deliver its full potential. But when companies align their data strategies with AI goals, they unlock smarter decision-making, automate tedious tasks, and even discover new ways to grow revenue.
A solid foundation is what makes AI deliver real impact. Companies that get this right move past simply competing—they innovate, lead, and shape the future of their industries.
Top 13 Data Modernization Service Providers
ISG has assessed data modernization services providers based on their ability to deliver end-to-end solutions that transform legacy IT systems into modern, cloud-native digital platforms. Providers in this quadrant offer comprehensive consulting services, including data modernization assessments, formulating modernization strategies, and executing data modernization roadmaps. They upgrade enterprises with scalable data architectures, data lifecycle management platforms and governance, and data cloud adoption strategies, ensuring strong governance frameworks for the AI race ahead.
Below is a brief overview of the data modernization service providers positioned as a Leader in the Data Modernization Services—Midsize quadrant 2024 ISG Provider Lens™ Advanced Analytics and AI Services, in alphabetical order.
Apexon
This company drives its data modernization efforts through cloud-native and AI solutions with scalable and adaptable service delivery. Its approach integrates real-time analytics and dynamic visualization tools, empowering decisions with precision.
Encora
This organization uses agile frameworks and a modular approach to ensure rapid deployment and tailored data modernization solutions. By consolidating fragmented data through integrated warehouses, it addresses critical challenges in data unification.
EXL
Strengthened by its acquisition of ITI Data, EXL delivers comprehensive data management, governance, and compliance solutions. This expertise allows organizations to operate within complex data environments, extracting reliable and actionable insights.
HARMAN
Supported by proprietary technologies and automated MLOps workflows, HARMAN utilizes its Life-ware.AI platform to deploy scalable cloud-to-edge AI solutions, enhancing operational efficiency for distinct business processes.
Hexaware
Driven by intelligent automation and accelerators, such as its data modernization platform Amaze® with GenAI copilots, Hexaware implements data initiatives to power data pipelines, data visualization, industry data clouds, and metadata frameworks.
HTC Global Services
To ensure seamless data ingestion, transformation, and governance, HTC Global Services offers end-to-end data management solutions through its MAGE DataWorks platform. It also integrates data mesh and graph database capabilities.
Innova Solutions
This company adopts a business-aligned modernization approach, ensuring data strategies align with organizational goals. By focusing on industry best practices, they can navigate digital and AI transformation with precision.
Mphasis
It incorporates pluggable decision models to facilitate seamless integration across heterogeneous environments, fostering business agility and innovation through adaptable data architectures.
Persistent Systems
It offers a comprehensive modernization framework through its Persistent Data Foundry, delivering advanced ingestion, governance, and analytics solutions that support real-time decision-making.
Stefanini
This organization specializes in seamless cloud migrations, strongly focusing on ETL/ELT processes and real-time analytics. Its approach integrates diverse data sources into scalable, multi-cloud environments.
Unisys
Assessing existing data landscapes and executing secure migrations of structured and unstructured data into enterprise-grade data lakes and cloud ecosystems, Unisys provides a structured modernization framework.
UST
With a comprehensive application modernization suite, UST differentiates itself by covering assessment, strategic planning, and cloud migration to ensure optimized, future-ready applications.
Virtusa
Bridging the gap between legacy and modern cloud environments, Virtusa offers a hybrid and multi-cloud data modernization strategy that maximizes past investments while integrating emerging technologies.
Data Modernization Trends Shaping the Future
Modernization does not merely involve replacing old systems. It’s about reimagining how data flows, integrates, and delivers value at scale. Here are the key trends shaping data-driven companies:
- AI-driven Data Quality and Governance
Data fuels innovation, but only if it’s trusted. Companies are using AI-powered tools to automate data cleansing, profiling, and validation. Bad product data is a common problem for e-commerce, making it harder for customers to find what they need, hurting sales, and costing companies nearly USD 13 million a year, according to research. - Data Democratization in Cloud Setups
Data access is no longer limited to IT teams. Enterprises are embracing low-code/no-code platforms that allow business users to query, analyze, and act on data themselves. Insurers giving underwriters a self-service analytics platform can significantly reduce underwriting time and better customer response rates. - Hyperscale, Sustainable Cloud Architectures
Cloud computing is no longer just cost savings. It’s scale, security, and sustainability. Companies are investing in hyperscale data centers, massive facilities designed to handle vast amounts of data with unmatched scalability, optimizing AI workloads while watching their environmental impact. - Real-time Insights with Edge AI and IoT
As IoT and edge computing converge, companies move from batch to real-time data analytics. In industries like manufacturing, transportation, and healthcare, every millisecond counts. For instance, automotive companies that integrate edge AI into their assembly lines can witness defect detection time going from hours to minutes, improving quality and reducing waste. - Data Mesh: Decentralizing Data for Speed
Data mesh architectures allow businesses to scale data and AI initiatives without bottlenecks. By decentralizing ownership, enterprises maintain governance while enabling teams to manage data independently and innovate without relying on overloaded central systems.
Data Modernization Best Practices
Enterprise data transformations succeed when they align with business goals and customer outcomes. Here’s what leaders are doing differently:
- Define a Clear Modernization Roadmap– Align data modernization initiatives with strategic business objectives. Focus on clearly defined areas like customer analytics, for instance, using a phased approach to deliver measurable outcomes.
- Leverage AI and Automation– The future of data management is intelligent. Automate migration, cleansing, and governance to minimize human error.
- Adopt a Multi-cloud Strategy—Flexibility is key for modern businesses. Enterprises are optimizing costs and performance with hybrid and multi-cloud solutions.
- Strengthen Data Governance– Compliance is no longer an afterthought. Enterprises are embedding governance frameworks that balance security with accessibility.
- Build a Data-driven Culture– Technology is just the enabler. Leaders need to invest in enterprise-wide data literacy programs to empower decision-makers at every level.
Beyond Technology: Building a Comprehensive Data Ecosystem
Today, data modernization experts assert that modernization goes beyond the technology upgrade, as seen in data modernization services providers. A comprehensive approach means strategic alignment, cross-functional collaboration, and a roadmap for short-term and long-term goals. One of the biggest data modernization challenges is integrating multiple data sources—a task that gets harder as we move to different cloud environments, edge solutions, and scattered applications. To address this complexity, we must orchestrate data from ingestion to transformation to business use.
Data security and privacy are just as important. As regulations like GDPR, CCPA, and industry-specific mandates get stricter, enterprises must adapt to a world where compliance is not just a responsibility but a key trust factor. Enterprises with good data governance practices stand out, gain a competitive edge, and avoid costly legal repercussions. Encrypting data at rest and in transit, role-based access controls, and continuous monitoring can strengthen data posture.
Even AI can fail if the workforce isn’t ready to use it. Ongoing upskilling, from data literacy programs to technical training, ensures employees can adopt new tools and methods. Encouraging a culture of experimentation and collaboration enables innovation as teams become more open to trying new technologies and unconventional approaches to data problems. That means rapid prototyping, fast feedback loops, and shorter time to results.
Sustainability and ethics are also at the top of the priority list. While hyperscale data centers deliver massive computational power, they also have a huge environmental footprint. We can align our modernization efforts with our broader ESG goals using green computing, workload optimization, and partnering with carbon-neutral data center providers. At the same time, ethical AI frameworks—transparent, with minimal bias, and model interpretability—are becoming a key part of modernization, as outlined by top data modernization services providers.
Forward-thinking companies recognize that data modernization is more than just upgrading—it’s about upgrading their data modernization strategy by supporting people, processes, and technology to treat data as an asset throughout its life cycle. That deals with immediate operational problems and sets the stage for advanced analytics, IoT, and AI. In short, the journey to be data-driven is about putting data into the enterprise’s DNA so it’s at the heart of every decision and interaction.
Hexaware: Redefining Data Modernization with AI-powered Solutions
The best data modernization services providers, such as Hexaware, deliver a comprehensive suite of data modernization services with its GenAI embedded platform Amaze® for Data and AI, improving data quality, automation, and operations at scale. Additionally, its industry-specific metadata-driven frameworks simplify the handling of batch and real-time data, allowing stakeholders to gain faster insights.
Hexaware helps businesses extract maximum value from their data assets by emphasizing scalability, flexibility, and intelligent data management. For example, facing operational inefficiencies, a multinational retailer partnered with Hexaware to modernize its data architecture. By deploying Amaze®, the retailer achieved a 40% reduction in migration time and a 30% improvement in data quality, gaining real-time insights for personalized marketing. In another engagement, a leading healthcare provider implemented Hexaware’s Data Wiki Solution to overhaul its governance framework. The result was 50% faster compliance reporting, improving regulatory adherence while safeguarding patient data.
The Future Belongs to Data-driven Enterprises
The enterprises that thrive over the next decade will be the ones that can break the shackles of legacy data modernization. The modernization of data represents something greater than a technical upgrade: it’s a strategic transformation that involves embracing data modernization services. The partners highlighted in the ISG report are leading this evolution by helping enterprises rethink their data ecosystems in terms of agility, intelligence, and competitive advantage.
There is no question about the future: companies that implement modern data practices today will be at the forefront tomorrow. The real question is, are you prepared to capitalize on every aspect of your data with data modernization services?
