PUBLISHED DATE: 2025-08-13 20:03:46

HFS Horizons Report: Choosing the Best Provider for Data Modernization Services, 2023

Converting legacy data architectures to cloud-native solutions needed to support modern applications, microservices, and governance

May 2023

Authors:

Introduction and the HFS Value Chain

When selecting a services partner for data modernization, enterprise leaders must understand the tools, talent, and technologies required to achieve their firm’s goals across three Horizons. While many aspire to a digital nirvana of ecosystem exchange, the focus must be on transitioning from today’s data estate to a framework that supports better creation, consumption, collaboration, and control of data. Given the complexity of existing data estates, leading services partners are crucial for bringing resources, innovation, and cloud-centric data capabilities into context, setting up frameworks for future visualization, insight, and actionable tools.

What is Data Modernization?

The term “data modernization” encompasses a wide variety of projects, from migrating a legacy Oracle SQL database to an Azure-based PostgreSQL instance, to adopting solutions from Snowflake or Informatica, and applying AI or analytics to improve data relevance and usability. HFS defines data modernization services as a value chain of capabilities and professional services across six areas:

  1. Discovery and assessment
  2. Platform architecture design
  3. Migrate, create, and retire
  4. Integrate, automate, and orchestrate
  5. Govern and secure
  6. Operate, run, and deliver

The goal is to re-architect the data estate from siloed, federated repositories into an integrated, accessible data architecture that business and technology teams can use to build meaningful, actionable insights.

This report focuses on services provided to enterprise clients across the first five aspects of the data modernization value chain.

Why Are Data Modernization Services Important?

Data is the key to an autonomous enterprise. Over the past two decades, enterprises have moved from super stacks of applications to complex cross-platform integrations, SaaS, and robotic process automation, all aiming to put guardrails around data. However, data continued to multiply, and applications struggled to keep up. Technologies like Apache Hadoop clusters and NoSQL databases promised to harness data, but now composable apps, low code, and microservices are accelerating the need for data modernization at a pace many technology teams struggle to address.

Overcoming layers of legacy solutions is a challenge few organizations can tackle alone. As organizations worked on digital transformation, cloud-native adoption, or application modernization, they often put off managing the growing mountain of data. Now, there is nowhere to hide from the daunting task of modernizing data.

This report profiles leading services providers and their capabilities for helping organizations with discrete data modernization needs (Horizon 1), breaking down data silos to build higher levels of cross-organizational trust (Horizon 2), and providers paving the way for customers to unlock new value from data and insights (Horizon 3).

What You’ll Learn from Our Study

The value proposition for data modernization services is shifting from “migrate from legacy” toward value creation across three Horizons:

This report examines the capabilities of 23 services providers and management consultants, assessing them across:

Enterprise users can leverage these insights when developing shortlists for their data modernization journeys.

Data Modernization vs. Data Insights and Decisions

This report focuses on how enterprise customers and services providers work together to adopt a cloud-native architecture for their data estate, improving how data is captured, monitored, secured, and promoted for access, usability, and value creation. The topic of data insights and decisions—how services and advisory firms help customers create a culture of data-driven decision-making—will be covered in a separate HFS report.

Data Modernization Services Focus

Talent and Skillsets

Technology Focus

Core Client Outcomes

Research Methodology

Study Methodology and Inclusion

The Data Modernization Services, 2023 study is an HFS Research Horizons report, designed to assess the innovation and value potential of vendor capabilities across three Horizons:

The study evaluates providers' capabilities across the HFS data modernization value chain model, based on a range of dimensions to understand the Why, What, How, and So What of service offerings.

Methodology

Inclusion Criteria

Sources of Data

How Did We Compare Service Providers’ Capabilities?

Organizations face the challenge of improving their data estate’s functionality, often running new solutions alongside legacy systems. The complexity of databases, data storage, APIs, dashboards, and more, combined with resource costs and staff development, makes selecting new software and cloud partners daunting.

HFS compared nearly two dozen services and advisory companies, focusing on each provider’s ability to bring thought leadership, tools, industry knowledge, talent, and pricing models to solve customer talent, technology, and budgeting challenges. Each participant was scored on:

Horizons Assessment Methodology

The 2023 HFS Horizons report evaluates service providers’ capabilities across dimensions to understand the Why, What, How, and So What of their service offerings. Assessment is based on client and partner inputs, augmented with analyst perspectives.

Assessment Dimensions

Horizons Definitions

The Evolution of Data: From Data to Decisions to the Autonomous Enterprise

IT departments have evolved from application-centric to data-centric:

Data Modernization: The Data Record Lifecycle

  1. Generation: Data is created by interaction, transaction, or event
  2. Collection: Data is entered into a system of record or database
  3. Processing: Data is processed, automated, configured, compressed, or encrypted
  4. Storage and Security: Data is stored in warehouses, lakes, or RAM, with security applied
  5. Management and Governance: Rules and policies manage data organization, storage, and retrieval
  6. Analysis: Data is processed into insights via algorithms, AI, or machine learning
  7. Visualization: Data is represented graphically for easier communication
  8. Interpretation: Users gain insights to plan for implications, opportunities, and change

Principles of the Autonomous Enterprise

  1. Leadership understands the data needed for success
  2. Teams know processes and interactions in digital detail
  3. Infrastructure breaks down data silos
  4. Trusted automation capability
  5. AI continuously finds patterns in data
  6. Robust governance across all decision cycles

Four Pillars of Data Modernization

Customer and Partner Insights on Data Modernization Journeys

Executive Summary

  1. Drivers: Top factors include access to talent with industry knowledge, strong SaaS/ISV partnerships, and hybrid cloud expertise
  2. Challenges: Main challenge is resources, talent, and budget for migrating legacy to cloud-native solutions (39%), followed by regulatory (16%) and security concerns (11%)
  3. Partnerships: Providers engage at an advisory level, focusing on usage and outcomes earlier than cloud migration or application modernization
  4. Value: Leading impediment is time and resources to transform legacy data models; automation and business process knowledge are critical
  5. Key Themes: Need for strategies using data-as-an-asset and data-as-a-product; planning for data structure and management differs based on chosen model

What Customers Need from Service Providers

Top Three Desired Qualities

  1. Willingness to co-innovate and make data actionable
  2. Talent and industry experience to define and achieve business outcomes
  3. Optimization of enterprise service catalog and resource management

Top Three Areas for Improvement

  1. Deeper understanding of business needs and proactive suggestions
  2. Ability to innovate and keep platforms relevant and cost-effective
  3. Stay on top of emerging data technologies and help firms adopt them

Top Data Modernization Challenges (Respondent Data)

Why Use a Service Provider? (Respondent Data)

What Partners Want

Partner Strengths

Partner Challenges

Emerging Data Brands in Partner Ecosystem

Horizons Results: Data Modernization Services, 2023

Service Providers Covered

HFS Horizons—Data Modernization Services, 2023

Horizon 3 – Market Leaders

Horizon 2 – Enterprise Innovators

Horizon 1 – Disruptors

Summary of Providers Assessed

Each provider is profiled with a summary of their approach, strengths, development opportunities, key offerings, ecosystem (M&A and partnerships), key clients, global operations, and flagship internal IP. (See the detailed profiles in the original document for each provider.)

HFS Research Authors

Joel Martin
Executive Research Leader
joel.martin@hfsresearch.com

Nikhil Bhaskar
Senior Analyst
nikhil@hfsresearch.com

About HFS

HFS is a unique analyst organization combining deep visionary expertise with rapid demand-side analysis of the Global 2000. HFS introduced terms such as “RPA” (Robotic Process Automation) and more recently, Digital OneOffice™ and OneEcosystem™. The HFS mission is to provide visionary insight into major innovations impacting business operations, such as Automation and Process Intelligence, Blockchain, the Metaverse, and Web3. HFS has deep business practices across all key industries, IT and business services, sustainability, and engineering.

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