BDMs and TDMs rely on different channels to build confidence in their decision — TDMs through a trusted buying network, and BDMs through consultative conversations and straightforward value articulation from the provider. TDMs place greater trust in peer networks and technology partners, often seeking validation from others who have implemented similar solutions. BDMs, on the other hand, value direct engagement with sales reps who can translate technical capabilities into business outcomes.

For example, while TDM buyers more commonly cited consensus or independent purchases (52% and 33% of TDMs, respectively), BDM buyers more often cited committee purchases (32% of BDMs vs. 15% of TDMs). Across the purchase process, IT and business leaders are heavily involved in each stage (see Figure 2). IT may lead the purchasing process but in close partnership with the business.

Sixty-five percent of data TDMs from Forrester’s budget planning survey plan to increase budgets for data and analytics staffing/personnel (24% of respondents plan to increase the budget by 5% to 10%, and 7% of respondents by more than 10%).

For example, buyers most commonly cite participating in a consensus purchase (typically a medium-sized purchase where a group or team of people across several departments agree to the purchase), with 47% of TDM buyers and 49% of BDM buyers doing so.

Test environment (TE) and test data management (TDM) services are below par, mainly due to a heavier focus on in-house accelerators than on external off-the-shelf TE and TDM products. Reference customers’ testimonials valued the disruptive approach and innovative AI solutions. As Qualitest expands its global presence, reference customers have expressed concerns about pricing flexibility, hoping for more adaptable pricing as services scale.

Teams tasked with maintaining a B2B organization’s sales and marketing operational data must be able to successfully measure results and manage performance. The metrics used to accomplish this must reflect the current state of marketing data, relevant data management activities, and resulting improvements in data value. This report shows operations teams how to apply the Forrester Metrics Spectrum to better communicate their data management story and provides practical advice for building data management performance reporting.

Application development is constantly evolving as developers look to innovate. At the same time, organizations seek to improve customer experience and achieve growth targets. This leads developers to seek out techniques and best practices such as using TuringBots (AI-enhanced software development tools). This report highlights application development trends from our latest data in Forrester’s Developer Survey, 2025.

AI fails when enterprise data lacks context, and most enterprise data still lacks the structure, semantics, and connective tissue modern AI systems require. AI-ready data is not a clean break from the past; it’s the unfinished work of decades of uneven data management that never fully scaled. This report describes Forrester’s vision for how enterprises must evolve data management into context-rich data foundations built on shared semantics and designed to make meaning, relationships, trust, and governance explicit and machine-navigable, so AI systems can deliver accurate, explainable, and business-relevant outcomes.

In our evaluation of master data management (MDM) solution vendors, we identified the most significant ones and researched, analyzed, and scored them. This report shows how each vendor measures up and helps you select the right one for your needs.

In our evaluation of data management for analytics (DMA) platform providers, we identified the most significant ones and researched, analyzed, and scored them. This report shows how each provider measures up and helps you select the right one for your needs.