Enterprises are significantly investing in data and AI, yet many are struggling to achieve meaningful returns. The underlying issue in most cases is a weak or fragmented data foundation. Addressing this challenge requires first understanding what data foundation truly means within the enterprise’s context – starting with a clear assessment of data maturity. This Viewpoint introduces the Data Transformation Success Model (DTSM), a comprehensive framework that helps enterprises evaluate and elevate their data maturity across five interconnected pillars: vision and strategy, data technology and consumption, governance, people, and processes. By identifying capability gaps and benchmarking progress, DTSM enables organizations to build a strong, scalable foundation that supports long-term business goals.  The report also highlights common pitfalls in data transformation and offers practical recommendations to overcome them. With DTSM, enterprises can align data strategies with organizational objectives, improve RoI, and drive meaningful transformation. The model’s maturity classification – laggard, typical, or advanced – helps organizations understand where they stand and develop targeted roadmaps to reach their desired state. Scope All industries and geographies Contents In this report, we examine: Why ambitious data and AI initiatives fail How to ensure success with data maturity assessment DTSM and its parameters What different data maturity stages look like Best practices for data officers

Enterprises across North America are advancing their data and AI strategies while grappling with infrastructure, governance, and talent-related challenges. As generative AI adoption gains momentum, organizations focus on scalable, business-aligned solutions that deliver measurable impact. To navigate this evolving landscape, they are turning to specialist service providers with deep domain expertise and advanced AI capabilities. In response, providers are strengthening their offerings through investments in generative AI, cloud-based AI platforms, and industry-specific accelerators. In this report, we evaluate 32 providers featured on Everest Group’s Data and AI Services Specialists – North America PEAK Matrix® Assessment 2025.  

Enterprises are increasingly identifying gaps in their data ecosystems as they seek to harness generative AI’s full potential. To address these gaps, businesses are prioritizing their data strategy to build AI-ready data ecosystems. AI advances have amplified the importance of robust data management and governance. When scaling their AI initiatives, they are realizing the value of trustworthy data to ensure quality, consistency, and security. The focus has shifted to realizing value, with enterprises aiming to drive tangible business outcomes from their data initiatives. Enterprises demand their data strategies to deliver measurable business outcomes, leading to productivity gains, operational efficiencies, and unlocking new revenue streams. Data initiatives are now vital investments that directly contribute to building a competitive advantage in the market. This compendium provides detailed profiles of 31 service providers to assist D&AI service buyers in selecting providers that can serve their needs. The report helps enterprises choose the best-fit provider based on their sourcing considerations and empowers providers to benchmark their performance against their peers. Scope All industries and geographies This assessment is based on Everest Group’s annual RFI process for the calendar year 2024, interactions with leading D&AI providers, client reference checks, and an ongoing analysis of the D&AI services market Contents In this report, we: Examine the D&AI services market Classifies providers into Leaders, Major Contenders, and Aspirants on a capability-market-impact matrix Assess providers’ key solutions, delivery centers, investments, and use cases Lending operations technology solutions/tools: brief descriptions of key technology solutions

As businesses generate and rely on vast amounts of data, managing its complexity becomes a pressing challenge. Without a structured approach, data inconsistencies can disrupt operations, compromise decision-making, and reduce AI-driven insights’ effectiveness. Master Data Management (MDM) serves as a foundational system that unifies essential business data, creating a single, trusted source of truth across systems and departments. This report emphasizes new-age MDM systems’ key characteristics, their enterprise adoption, and the evolving supplier landscape. It outlines a structured approach’s importance in navigating MDM’s complexities. Establishing an efficient MDM system requires a multi-tiered, phased strategy involving key business and technical stakeholders. Enterprises seeking to future-proof their organizational data should invest in MDM with a clear focus on maximizing data value. Scope All industries and geographies Contents In this report, we examine: MDM’s evolution over the years Key trends shaping the MDM landscape The evolving supplier landscape The challenges with MDM adoption and how to overcome them Membership(s) Data & Analytics Sourcing and Vendor Management

Healthcare organizations generate massive data volumes from EHRs, IoT, labs, and billing systems, making effective data management essential. Interoperability, governance, and real-time analytics challenges hinder seamless data flow and insight generation. Healthcare data platforms address these issues by offering AI-driven analytics, ETL pipelines, and EHR connectivity, transforming raw data into actionable insights. These platforms improve operational efficiency, enhance patient outcomes, and enable data-driven decision-making. However, balancing innovation with compliance remains vital as organizations navigate regulatory complexities and privacy concerns. Advanced solutions ensure secure, scalable, and intelligent data management, enabling predictive analytics and real-time interoperability. As the healthcare landscape evolves, data platforms will be pivotal in optimizing workflows, streamlining care coordination, and driving digital transformation across the industry. In this report, we analyze the data platforms landscape, including key solution components, considerations to select the right tool, and leading providers. It highlights healthcare data platforms’ evolution from traditional data storage to AI-driven analytics, real-time interoperability, and predictive insights. The report profiles 15 leading technology providers that offer data platforms, highlighting their capabilities and industry use cases. Scope Industry: healthcare Domain: healthcare data platforms Geography: global Contents In this report, we provide: Each provider’s company overview Provider’s capability, market trends, and innovation dimensions Case studies demonstrating capabilities in the healthcare data management space Membership(s) Healthcare Payer and Provider Information Technology Sourcing and Vendor Management

Enterprises are increasingly recognizing their data ecosystem gaps as they strive to fully harness generative AI’s potential. Consequently, they are prioritizing AI-ready data ecosystems, emphasizing robust data management and governance. When scaling their AI initiatives, they are gradually realizing trustworthy data’s value to ensure quality, consistency, and security. In addition, the focus has shifted toward realizing value, with enterprises aiming to drive tangible business outcomes from their data initiatives. Enterprises demand their data strategies to deliver measurable business outcomes. This has led to a sharp focus on driving productivity gains, operational efficiencies, and unlocking new revenue streams. Data initiatives are now viewed as vital investments to gain a competitive edge in the market. This compendium provides detailed profiles of 27 providers featured on Everest Group’s D&A Services PEAK Matrix® Assessment 2024. This report will help enterprises choose the best-fit provider based on their sourcing considerations, while providers will be able to benchmark their performance against their peers. Scope All industries and geographies The assessment is based on Everest Group’s annual RFI process for the calendar year 2024, interactions with leading specialist AWS service providers, client reference checks, and an ongoing analysis of the cloud services market Contents This report features detailed assessments, including profile overviews, key solutions, delivery centers, investments, and case studies of 27 providers that focus on D&A services. Membership(s) Data & Analytics Sourcing and Vendor Management

Modern Data Stack (MDS) components are the foundational building blocks of any data ecosystem. Over the years, these components have transformed significantly to meet growing enterprise demands due to the increasing recognition of data as a vital asset in enabling digital transformation for a sustained competitive advantage. To navigate this landscape, enterprises must formulate a well-defined data strategy aligning with their unique needs and goals. This strategy should comprehensively evaluate MDS components, identify the most relevant ones, determine their integration, and assess their potential to deliver measurable business impact. Chief Data Officers (CDOs) will be pivotal in this process as they must carefully balance innovation with RoI. Scope All industries and geographies Contents In this report, we examine: Demand themes driving the shift in MDS Overview of MDS 2.0 The technology provider ecosystem for MDS Key considerations for CDOs when exploring MDS Membership(s) Data & Analytics Sourcing and Vendor Management

In the AI and generative AI era, data has evolved from a byproduct of business processes to a strategic asset driving innovation and decision-making. Despite its importance, enterprises face significant challenges in effectively managing and utilizing data, including data silos, low data quality, inefficient discovery processes, and compliance risks. Data catalogs have emerged as a foundational tool to address these issues. By centralizing metadata and providing detailed data inventories, they enable enterprises to discover, understand, and trust their data assets. Modern data catalogs go further by incorporating AI-driven capabilities such as semantic search, knowledge graph visualization, and intelligent recommendations, transforming how organizations access and use data. In this report, we explore data catalogs’ evolution, capabilities, role in solving enterprise data challenges, adoption strategies, and market trends. Scope All industries and geographies Contents In this report, we examine: Data management challenges and business implications for data leaders Data catalogs’ evolution Modern data catalog solutions’ core components Technology provider landscape and innovations The evolving data catalog supplier ecosystem Membership(s) Data & Analytics Sourcing and Vendor Management

As sustainability becomes increasingly integral to corporate strategy, ESG data management providers’ capabilities are emerging as essential for organizations to enhance their performance and accountability. Today, stakeholders demand transparency regarding ESG practices, and these platforms offer advanced solutions that facilitate robust data management processes. By delivering vital sustainability performance insights, they enable companies to identify risks and opportunities while ensuring compliance with evolving regulatory standards. Stringent regulatory frameworks, such as the Global Reporting Initiative (GRI) and the International Financial Reporting Standards (IFRS), drive the evolving ESG data management landscape. These frameworks require comprehensive disclosure of sustainability practices. As public awareness of environmental issues increases, organizations must adopt effective data management processes to meet compliance requirements and improve operational efficiencies. This shift highlights the importance of integrating sustainability into core business practices. In this report, we analyze 26 ESG data management providers’ capabilities, including their platform offerings, key IP/solutions, domain investments, and case studies. The report equips organizations with insights to select tailored ESG data management solutions that align with their unique needs. It also empowers companies to advance sustainability initiatives and drive meaningful operational change. Scope All industries and geographies This assessment is based on Everest Group’s annual RFI process for the calendar year 2024, interactions with leading ESG data management platform providers, client reference checks, and an ongoing analysis of the ESG data management platform market Contents In this report, we evaluate 26 ESG data management platform provider profiles and include: ESG data management platform market trends Key factors and technologies shaping the ESG data management platform market An overview of providers’ vision, presence across enterprise segments and geographies, key solutions / intellectual property, partnerships, and recent developments in capabilities Case studies highlighting ESG data management solutions implemented by providers Membership(s) Sustainability Technology and Services Outsourcing Excellence

The Data and Analytics (D&A) and AI market continues to grow rapidly, fueled by expanding enterprise data and AI-ML advances. Organizations are turning toward D&A and AI solutions to drive digital transformation, enhance decision-making, and scale operational efficiency. At re:Invent 2024, AWS showcased its commitment to advancing the D&A and AI ecosystem with impactful updates to its platforms and tools and introducing new generative AI foundational models. These enhancements emphasize scalability, multi-model flexibility, and enterprise readiness, addressing the complete AI life cycle, from data processing to model deployment, while maintaining a strong focus on security and governance. In this report, we analyze AWS’ latest announcements from re:Invent 2024, identifying growth opportunities, enterprise challenges, and the company’s competitive positioning. The report further delves into AWS’ key offerings, major differentiators, and areas where additional refinements could enhance its value proposition. Scope All industries and geographies The assessment is based on Everest Group’s participation in and monitoring of announcements made at the AWS re:Invent 2024 event Contents In this report, we: Key themes driving and inhibiting enterprise demand for D&A and AI AWS’ current positioning in the D&A and AI market Announcements from AWS re:Invent 2024 Membership(s) Data & Analytics Artificial Intelligence (AI) Sourcing and Vendor Management