GARTNER Data & Analytics Summit
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About this event
Gartner Data & Analytics Summit — Buyer/Attendee Research Brief (Global Event Analysis)
The Gartner Data & Analytics Summit is a high-impact, strategy-heavy conference that brings together data, analytics, AI, governance, and decision-intelligence leaders across multiple industries. Unlike purely technical meetups, this summit typically emphasizes executive-level guidance, business value frameworks, platform and operating model decisions, and roadmaps for scaling analytics programs. For attendee-list and buyer-reach research, the most valuable audiences usually sit in leadership and transformation roles: CDO/CDO-equivalent, VP/Director of Data, Analytics leaders, governance and risk owners, BI/Insights leaders, and platform decision-makers.
1) Who attends (BUYERS / ATTENDEES)
The event’s audience is primarily enterprise decision-makers and data/analytics transformation stakeholders. While practitioners also attend, the buyer-rich layer is generally the group setting analytics strategy, vendor direction, budget priorities, and enterprise-wide operating models.
Main attendee groups
- Chief Data Officer (CDO), Deputy CDO, Head of Data Strategy
- VP/Director of Data & Analytics, Director of Analytics Engineering
- Head of Business Intelligence, VP Insights, BI Program leaders
- Data Governance leadership: Director/Manager Data Governance & Stewardship
- Data Quality and master data management (MDM) program owners
- Analytics/AI adoption leaders: Head of Applied AI, AI Transformation, Analytics Product owners
- Enterprise Architecture and platform owners involved in modernization (cloud, data platforms, integration, interoperability)
- Security, privacy, and risk stakeholders involved in data handling and compliance alignment
- IT leadership tied to data platform investment and standardization
- Technology and services providers’ sales, partnerships, solutions architecture, and customer success teams (sponsors/exhibitors)
Buyer behavior to expect: attendees generally come prepared to evaluate strategic direction (not just products). Many buyers attend to validate roadmaps, learn market benchmarking, and identify vendor/partner fit for their data platform and analytics operating model.
What “buyers” look like for list targeting
- People who influence budget ownership or program funding for data/analytics/AI
- Owners of data platform selection and governance frameworks
- Leaders responsible for analytics scaling, operational analytics, or decision intelligence
- People tasked with improving data quality, lineage, compliance, and auditability
- Transformation leaders building the enterprise analytics operating model
2) Where the show is happening + attendee geographic origin
The summit’s location varies by edition; however, Gartner’s Data & Analytics Summit typically draws a global enterprise mix because many data/analytics programs operate cross-regionally. The attendee origin commonly includes a strong share from:
- North America (U.S. and Canada), especially for enterprise transformation leaders and hyperscaler/data platform buyers
- Europe (UK, Germany, France, Nordics, Benelux) due to strong compliance-driven data governance demand
- Middle East & APAC (depending on edition) where large enterprises are modernizing analytics and scaling AI initiatives
- International participants from multinationals aligning data strategy across regions
Best geographic targeting approach for attendee lists: use role-based targeting (data platform strategy, governance, BI/insights, analytics transformation) and then localize by region if your offering requires regional support, implementation partners, or data-residency alignment.
3) Audience reach (Local / National / Global)
This is best categorized as a Global reach event (enterprise buyers across multiple countries, plus vendor organizations with worldwide operations). While the physical attendee base concentrates around the host region, the strategic topic scope (data governance, analytics operating models, AI readiness) attracts multinational enterprises. The business relevance is global, especially for data platform and governance initiatives that must work across borders.
Implication for buyer-fit research: the highest-value list usually comes from mapping roles that make global platform/strategy decisions, rather than relying only on location.
4) Sample buyer company names (BUYERS ONLY) + Websites
Below are example buyer organizations that are typically active in data/analytics transformation (or are likely to have relevant enterprise data leadership attending). We recommend validating the final list against our client’s exact needs, timeline, and geography requirements.
| Priority | Company | Website | Best Title to Target | Why This is a Good Buyer Fit |
|---|---|---|---|---|
| 1 | Bank of America | https://www.bankofamerica.com/ | VP, Data & Analytics / Head of Data Governance | Large-scale enterprise analytics and compliance-driven data governance priorities; strong relevance for governance, quality, and decision intelligence use cases. |
| 2 | JPMorgan Chase & Co. | https://www.jpmorganchase.com/ | Director/VP, Data Strategy & Analytics Transformation | Complex data environments across lines of business; buyers commonly evaluate analytics operating models, lineage, quality, and scalable analytics. |
| 3 | Citigroup | https://www.citigroup.com/ | Head of Enterprise Data & Analytics | Global analytics programs and governance requirements make data platform and operating model decisions highly relevant. |
| 4 | Verizon | https://www.verizon.com/ | Director, Data & Analytics / Head of Insights | Consumer and network data scale drives need for analytics modernization, data quality, and AI-ready governance. |
| 5 | Microsoft | https://www.microsoft.com/ | Chief Data Officer equivalent / Data Platform Strategy Lead | As a technology and cloud leader, Microsoft teams often lead advanced data and analytics architecture decisions and operating models. |
| 6 | Amazon (Enterprise/Services Buyer) | https://www.aboutamazon.com/ | Director, Data Analytics Platform / Head of Data Governance | Large analytics footprint and modernization programs; relevant for analytics scaling, governance, and decision-intelligence frameworks. |
| 7 | Walmart | https://corporate.walmart.com/ | VP/Director, Data & Analytics / Enterprise BI Leader | Retail-scale insights programs require consistent governance, data quality improvements, and analytics operating model maturity. |
| 8 | Target | https://corporate.target.com/ | Head of Data & Analytics / Director, Insights Platform | Buyer relevance for analytics modernization and AI-ready data foundations supporting personalization and forecasting. |
| 9 | Comcast | https://corporate.comcast.com/ | VP, Data Strategy & Analytics / Director, Data Governance | Massive telemetry and customer datasets; strong alignment to governance, data quality, and scalable analytics. |
| 10 | Shell | https://www.shell.com/ | Director, Data & Analytics / Digital Transformation Data Lead | Operational analytics and enterprise data modernization; strong need for governance, lineage, and trusted analytics at scale. |
| 11 | BP | https://www.bp.com/ | Head of Data Governance & Analytics / VP Data Transformation | Cross-site data and compliance requirements; buyers likely to evaluate scalable analytics and governed data platforms. |
| 12 | Siemens | https://www.siemens.com/ | Head of Digital Data & Analytics / Director Analytics Engineering | Industrial data and analytics modernization needs alignment with analytics operating models and data product thinking. |
| 13 | Volkswagen Group | https://www.volkswagenag.com/ | Director, Data Strategy & Analytics / Enterprise Governance Lead | Complex vehicle, supply chain, and manufacturing data; strong governance and analytics scaling demand. |
| 14 | Unilever | https://www.unilever.com/ | VP, Data & Analytics / Global Insights Lead | Global consumer data programs benefit from governed analytics and consistent decision-making frameworks. |
| 15 | Nestlé | https://www.nestle.com/ | Head of Data & Analytics / Director Data Governance | Data-driven supply chain and marketing analytics; alignment to data quality, lineage, and scalable analytics foundations. |
| 16 | Pfizer | https://www.pfizer.com/ | Director/Head, Data Strategy & Analytics / Data Governance Lead | Highly regulated environment creates strong demand for governance, compliance, and trustworthy analytics. |
| 17 | Johnson & Johnson | https://www.jnj.com/ | VP/Director, Data & Analytics Transformation | Enterprise-grade analytics and governance needs; data quality and lineage are often core evaluation criteria. |
| 18 | Salesforce (as a buyer organization for internal transformation) | https://www.salesforce.com/ | Director, Data & Analytics Platform / Data Governance Leader | Enterprise data/analytics platform leadership and operating model alignment for analytics scaling initiatives. |
| 19 | IBM (as buyer for internal data programs) | https://www.ibm.com/ | Head of Enterprise Analytics & Data Governance | Strong internal analytics and data governance maturity; relevant buyer research for enterprise operating model topics. |
| 20 | Accenture (as buyer organization for enterprise data transformation) | https://www.accenture.com/ | Director, Data & Analytics Transformation / Data Governance Lead | Consulting-scale operations require structured analytics and governed data practices across global teams. |
Top buyer samples to prioritize for outreach: Bank of America, JPMorgan Chase, Verizon, Walmart, Shell. These represent common summit-relevant buyer archetypes: governance-heavy regulated analytics, large-scale BI/insights programs, and enterprise transformation leadership.
5) Job profiles, industries & event type
Best job profiles to target
- Chief Data Officer (CDO) / Head of Data / Deputy CDO
- VP/Director of Data & Analytics / Analytics Transformation Director
- Head of Enterprise BI / VP Insights / Director, Analytics & Intelligence
- Data Governance Director / Data Stewardship Lead / Data Privacy Analytics lead
- Data Quality Manager / MDM Program Lead
- Analytics Engineering Lead / Data Platform Product Owner
- Enterprise Architecture (data platform modernization)
- Program or Transformation leaders (Digital Transformation, Data Operating Model)
- Cybersecurity and compliance stakeholders connected to governed data access
Industries most likely to be represented (based on summit theme fit)
- Financial Services and Insurance (governance, risk, analytics at scale)
- Telecommunications (customer & network analytics)
- Retail and Consumer Goods (personalization, forecasting, demand planning)
- Energy and Industrial Manufacturing (operational analytics, reliability analytics)
- Healthcare & Life Sciences (regulated analytics and quality governance)
- Technology and Consulting (data platform operations, AI readiness)
Event type classification
Enterprise Data Strategy & Analytics Transformation Conference with executive tracks, vendor/partner presence, and research-led sessions focused on: data platform modernization, AI-enabled analytics, data governance, operating models, and measurable business outcomes.
6) Estimated attendance (expected total footfall)
The summit typically operates at a scale where total attendance can range from hundreds to several thousand depending on edition, host region, and co-located formats (if any). Footfall is usually concentrated among enterprise teams attending multi-session tracks, with additional sponsor and speaking footprints.
Buyer-density expectation: the quality of attendee roles (data leadership, governance owners, analytics transformation directors) is generally strong. Even when overall attendance is moderate, buyer density tends to be higher than broad consumer/vertical conferences.
If we need to be exact for a specific edition (city/date), we can tighten the estimate once the host city and dates are confirmed.
7) Key focus areas & buyer engagement
Key focus areas (what buyers come to learn/evaluate)
- Analytics modernization: moving from legacy BI to scalable insight platforms and analytics engineering
- AI-ready data: governance, quality, lineage, and enabling high-trust data for ML/AI initiatives
- Data governance and stewardship: operationalizing policies, roles, and accountability
- Data quality and reliability: reducing decision errors, improving correctness, and measuring trust
- Enterprise data operating models: roles, processes, and how analytics work gets done
- Cloud and platform strategy: choosing architectures that support scale and control
- Security, privacy, and compliance alignment: governed access, auditability, and risk controls
Buyer engagement (how to position and talk to them)
For attendee list outreach, the engagement angle should match executive concerns: business outcomes, speed-to-value, risk reduction, governance maturity, and enterprise scalability. Many buyers attend to validate how their internal roadmap compares to leading practices.
- Use messaging that ties to measurable outcomes (faster analytics delivery, reduced rework, fewer compliance incidents)
- Target leaders who own operating models, not only tool evaluators
- Offer “architecture-to-governance” mapping: how the platform, quality, and policies work together
- Position value for both technical governance and business decision trust
8) Client-product fit note + requirement for client website (Buyer matching)
We can produce the best buyer/attendee targeting for this summit only after we review the client product details. Based on your internal rule, we always align attendee-list recommendations to what buyers are most likely to purchase and implement.
Please share the client product website URL (or paste the product page text) so we can review and confirm:
- What problem it solves (data governance, quality, observability, MDM, data catalogs, BI acceleration, AI enablement, compliance, etc.)
- Buyer persona match (CDO, data governance, analytics engineering, BI leaders, enterprise architecture, security/privacy)
- Best industries and filtering logic (regulated vs high-volume analytics, customer data vs operational data, etc.)
In the meantime (conditional recommendations): if the client product is oriented toward:
- Data governance / lineage / stewardship / compliance: prioritize Data Governance Director/Head, Data Stewardship, Privacy & Compliance Analytics, Risk-linked data owners.
- Data quality / MDM / trust and reliability: prioritize Data Quality Manager, MDM Program Lead, Enterprise Data Reliability owners.
- Analytics engineering / BI modernization: prioritize Head of BI/Insights, Analytics Engineering Lead, VP Analytics Transformation.
- AI readiness / responsible AI data: prioritize CDO/CDO-equivalent, AI Transformation leaders, governance leaders with “AI governance” scope.
- Data platform modernization: prioritize Enterprise Architecture (data), Data Platform Product Owner, Director Data & Analytics Platform.
Once the website is shared, we will return a ranked “best buyers” list specific to your product requirements, including optimized job titles and the highest-fit industries from the allowed industry set.
9) Suggested industry targeting (aligned to allowed industry taxonomy)
We will select industries based on how well they map to data/analytics transformation buyer behavior. From the provided industry taxonomy, the strongest match groups for this summit are typically:
Primary recommended industries (highest relevance)
- Information Technology & Services
- Computer Software
- Internet
- Financial Services
- Insurance
- Telecommunications
- Retail
- Oil & Energy
- Renewables & Environment (where analytics and monitoring programs exist)
- Hospital & Health Care and/or Pharmaceuticals (for regulated analytics use cases)
Secondary recommended industries (depending on client product fit)
- Computer & Network Security (if the product supports privacy/governed access)
- Market Research (if buyer use case is insights/measurement)
- Logistics & Supply Chain (if analytics is supply chain, forecasting, operations)
- Management Consulting (if your solution is adopted via transformation advisory)
- Industrial Automation and Mechanical or Industrial Engineering (if operational analytics, reliability analytics)
- Media Production / Broadcast Media / Online Media (if analytics supports content intelligence, personalization)
After we review your client website, we will narrow to the top 5–8 industries for the best conversion likelihood and provide corresponding job-title targeting strategies.
Action Plan for Our Next Step (So We Can Build the “Best Buyers” List)
- Send the client website URL (and 1–2 key use cases / target buyer problems).
- Confirm target geography: global or specific regions/countries.
- Confirm buyer priority: enterprise data leadership, governance owners, analytics engineering, IT platform owners, or compliance/security.
- We will return:
- A ranked list of best-fit buyer companies
- Optimized job titles to target
- Industry filtering using your allowed industry taxonomy
- Buyer-fit messaging angles tailored to the product
Required from you: Please share the client product website so we can review and propose the best buyer/attendee targeting for this summit.
Data sheet
| Event Name | GARTNER Data & Analytics Summit |
| Event Date | 8–10 March 2027 |
| Event Status | Upcoming |
| Venue | Gaylord Palms |
| City | Orlando |
| State / Region | Florida |
| Country | United States |
| Organizer | Gartner, Inc. |
| Official Event Website | Gartner Data & Analytics Summit official event page |
| Event Type | Conference / summit |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Business Services; Science & Research |
| Audience Reach | National with selective international participation |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Medium for event identity and venue; low for attendance volume until organizer confirms the current edition |
| Main Purpose of Event | Education, peer benchmarking, technology evaluation, vendor discovery, analytics strategy, and executive networking for data and analytics leaders |
GARTNER Data & Analytics Summit is a major executive event for leaders responsible for data strategy, analytics modernization, governance, AI-enabled decision support, and enterprise information management. It typically brings together business and technology stakeholders who are evaluating platforms, advisory services, and implementation partners that can improve data quality, accelerate analytics adoption, and strengthen organizational decision-making.
The summit matters because Gartner events are widely used as market education and vendor-shortlisting environments for enterprise buyers. For suppliers, the event offers access to senior data, analytics, BI, governance, and transformation decision-makers who are actively shaping budgets, roadmaps, and technology selections. It is especially relevant for B2B lead generation, intent-driven outreach, and account-based targeting in software, consulting, cloud, data infrastructure, and related services.
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Data & Analytics Leaders | Enterprise, mid-market, and public sector organizations | Strategy owner, budget influencer, platform evaluator | Primary target for analytics platforms, governance tools, data products, and advisory services |
| CIO / CTO / IT Leadership | Large enterprises, digital-native firms, public agencies | Technology budget authority and vendor approval | Relevant for data platforms, cloud, integration, security, and architecture offerings |
| Business Intelligence / Reporting Teams | Companies with mature reporting and KPI environments | Tool users, shortlist contributors, solution validators | Good fit for dashboards, visualization, semantic layers, and analytics workflow tools |
| Data Governance / Data Quality Teams | Regulated industries, large enterprises, data-mature organizations | Policy owners, compliance influencers, tool evaluators | Strong target for MDM, catalog, lineage, stewardship, and quality vendors |
| Digital Transformation / Enterprise Architecture | Large commercial and public sector organizations | Solution design, roadmap coordination, standards setting | Relevant for consulting, integration, cloud modernization, and data operating model services |
| Procurement / Vendor Management | Enterprises purchasing software and services | Commercial review, sourcing, contracting | Relevant for attendees involved in renewals, pricing, and supplier selection |
| Consultants / Advisors / Systems Integrators | Consulting firms, SIs, MSPs, boutique analytics advisors | Influencers, recommenders, implementation partners | Useful for partner recruitment and channel development |
| Public Sector / Education / Healthcare Buyers | Government agencies, universities, health systems | Program owners, digital data leads, procurement influencers | Relevant for compliant analytics and reporting solutions |
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Host city: Orlando | Florida-based enterprise, tourism, healthcare, education, and public sector attendees | Medium | Convenient for regional attendees and national travel access |
| Host state: Florida | Statewide enterprises, agencies, universities, and healthcare systems | Medium | Strong regional draw from Jacksonville, Tampa, Miami, and Atlanta corridor travelers |
| Nearby business hubs | Atlanta, Tampa, Jacksonville, Miami, Charlotte, Raleigh, Dallas, New York, Washington DC | High | These markets host many large enterprise buyers and consulting firms |
| National reach | U.S. enterprise data and analytics leaders across industries | High | Gartner brand typically attracts nationwide executive attendance |
| International reach | Canada, UK, Europe, and select APAC or Latin America executives | Medium | International participation is plausible but not publicly quantified |
| Reach Level | Assessment | Explanation |
|---|---|---|
| National | Primary classification | The summit is expected to draw U.S.-based enterprise decision-makers from multiple industries and regions. |
| Global | Secondary reach description | Gartner-branded events often attract a limited but meaningful international audience of executives, partners, and solution providers. |
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Gartner, Inc. | Organizer / market influencer | Relevant benchmark organization and ecosystem influencer for data and analytics vendors | gartner.com | Research Director, Event Partnerships, Conference Marketing | Confirmed Speaker Organization |
| Microsoft | Enterprise technology buyer / platform user | Large data and analytics environment; relevant for cloud, BI, governance, and AI | microsoft.com | CIO, VP Data & Analytics, Director of BI | Strong Market Fit, Attendance Not Confirmed |
| Walmart | Retail buyer / enterprise data user | Massive analytics need across retail operations, supply chain, and customer insights | walmart.com | VP Analytics, Data Governance Lead, Enterprise Architect | Strong Market Fit, Attendance Not Confirmed |
| JPMorgan Chase | Financial services buyer | Highly regulated, data-intensive enterprise with advanced analytics requirements | jpmorganchase.com | Chief Data Officer, Analytics Director, VP Data Governance | Strong Market Fit, Attendance Not Confirmed |
| Cigna | Healthcare buyer | Healthcare analytics, reporting, compliance, and data governance use cases | cigna.com | VP Analytics, Director Data Management, CIO | Strong Market Fit, Attendance Not Confirmed |
| Procter & Gamble | Consumer goods enterprise buyer | Enterprise-scale demand for analytics, forecasting, and master data management | pg.com | VP Insights & Analytics, Data Platform Director | Strong Market Fit, Attendance Not Confirmed |
| The Home Depot | Retail / supply chain buyer | Analytics-heavy retailer with omnichannel, inventory, and operations needs | homedepot.com | Director Data Analytics, VP Supply Chain Analytics | Strong Market Fit, Attendance Not Confirmed |
| State of Florida | Government buyer | Public-sector data, reporting, and digital transformation initiatives | florida.gov | Chief Data Officer, IT Director, Procurement Officer | Strong Market Fit, Attendance Not Confirmed |
| University of Florida | Higher education buyer | Research, student, finance, and institutional analytics needs | ufl.edu | CIO, Data Governance Lead, Institutional Research Director | Strong Market Fit, Attendance Not Confirmed |
| Lockheed Martin | Defense / aerospace buyer | Complex enterprise data environments and secure analytics needs | lockheedmartin.com | Director Data Strategy, CIO, Analytics Architect | Strong Market Fit, Attendance Not Confirmed |
| Accenture | Consulting / implementation partner | Advisory and implementation influence across enterprise data programs | accenture.com | Managing Director, Data & AI Lead, Client Partner | Strong Market Fit, Attendance Not Confirmed |
| Deloitte | Consulting / implementation partner | Common attendee profile at executive analytics summits | deloitte.com | Partner, Analytics Lead, Alliance Director | Strong Market Fit, Attendance Not Confirmed |
| Snowflake | Data platform vendor / ecosystem buyer | Relevant partner, sponsor, and enterprise reference organization | snowflake.com | Field CTO, Industry GTM, Partner Manager | Strong Market Fit, Attendance Not Confirmed |
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Chief Data Officer | Data / Information | C-level | Owns data strategy, governance, and platform direction |
| 2 | VP Data & Analytics | Analytics / Digital | VP | Primary budget owner and vendor evaluator |
| 3 | Director of Analytics | Business Intelligence | Director | Common decision-maker for BI and analytics tooling |
| 4 | Director of Data Governance | Data Governance | Director | Evaluates catalog, lineage, quality, and stewardship solutions |
| 5 | CIO | IT | C-level | Sets enterprise tech priorities and platform investments |
| 6 | Enterprise Architect | Architecture | Senior manager / Director | Influences system integration and target-state architecture |
| 7 | Procurement Director | Procurement | Director | Supports sourcing and contract review for software/services |
| 8 | Strategic Sourcing Manager | Procurement | Manager | Handles vendor comparison, pricing, and supplier due diligence |
| 9 | Program Manager, Data Transformation | PMO / Transformation | Manager / Senior manager | Coordinates implementations and stakeholder requirements |
| 10 | Director of Business Intelligence | BI / Reporting | Director | Often the hands-on owner of analytics platform decisions |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Information Technology & Services | Core audience for data platforms, integration, and analytics | Software, cloud, and consulting targeting |
| 2 | Computer Software | Major buyer and vendor segment around data tooling | Platform, BI, and analytics applications |
| 3 | Financial Services | Data-intensive and regulated buyer segment | Governance, risk, reporting, and AI analytics |
| 4 | Hospital & Health Care | Strong demand for operational and clinical analytics | Data modernization and compliance tools |
| 5 | Retail | High analytics use across merchandising and supply chain | Forecasting, category analytics, and inventory insights |
| 6 | Consumer Goods | Enterprise analytics and demand planning user base | Data products and planning solutions |
| 7 | Management Consulting | Influential advisors and implementers | Partnerships, referrals, and resale channels |
| 8 | Government Administration | Public-sector modernization and reporting requirements | GovTech analytics and compliance solutions |
| 9 | Higher Education | Institutional research, student success, and finance analytics | Dashboards, data governance, and reporting tools |
| 10 | Insurance | Highly data-dependent decision making | Risk analytics, governance, and automation |
| 11 | Pharmaceuticals | Regulated environment with strong data needs | Data quality, compliance, and advanced analytics |
| 12 | Logistics & Supply Chain | Operational analytics and forecasting use cases | Supply chain visibility and performance tools |
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Not publicly confirmed | Confirmed unknown | Organizer has not publicly confirmed a current-year figure in accessible event materials | Use as a lead-gen event, but do not rely on attendance count for forecasting |
| Exhibitor count | Not publicly confirmed | Confirmed unknown | No verified current-year exhibitor directory reviewed here | Likely vendor ecosystem presence, but count not stated |
| Buyer count | Not publicly confirmed | Confirmed unknown | Gartner summit attendee mix typically includes buyers, but no figure is published | Strong prospecting value due to executive buyer density |
| Speaker count | Not publicly confirmed for this edition | Confirmed unknown | Agenda not reviewed with a verified speaker count | Likely mix of Gartner analysts, customer speakers, and sponsors |
| Historical attendance | Not included without verified source | Not used | No verified prior-year organizer figure included in this report | Attendance figure not publicly confirmed by the organizer. |
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Data Governance | Control, stewardship, lineage, ownership | Executive sessions on risk reduction and operating model maturity | Catalog, lineage, quality, MDM, stewardship platforms |
| AI / Advanced Analytics | Predictive and prescriptive decision support | Demo AI use cases tied to measurable business outcomes | ML platforms, analytics apps, AI governance tools |
| Cloud Data Platforms | Scalable storage, compute, and analytics modernization | Position migration accelerators and architecture best practices | Cloud warehouses, lakehouse tools, integration services |
| BI / Reporting | Self-service insights and KPI visibility | Show dashboard modernization and user adoption | Visualization, semantic layer, reporting software |
| Data Security & Privacy | Access control, privacy, compliance | Discuss regulated-environment readiness and controls | Security, masking, governance, privacy management tools |
| Consulting / Advisory | Program design and implementation support | ABM toward transformation leaders and program sponsors | Strategy, architecture, implementation, managed services |
| Data Literacy / Change Management | Adoption and capability building | Target leaders responsible for adoption and training | Training, enablement, analytics governance programs |
| Public Sector Analytics | Compliance, transparency, service delivery metrics | Highlight procurement-friendly, secure implementations | GovTech BI, reporting, and data management solutions |
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Very High | The summit is centered on data and analytics decision-makers with active buying authority or influence. |
| Decision-maker availability | High | Gartner events typically attract senior executives and functional leaders. |
| Data collection potential | High | Strong fit for attendee list enrichment, account mapping, and job-title-based segmentation. |
| Apollo targeting potential | Very High | Clear match to data, analytics, IT, procurement, consulting, and regulated-industry filters. |
| Geographic targeting potential | High | Useful for Florida, Southeast U.S., and national enterprise targeting. |
| Best outreach approach | Very High | Account-based outreach with analytics-specific messaging, executive pain points, and proof-based demos. |
| Overall lead quality | Very High | One of the strongest event types for enterprise data, BI, governance, and analytics lead generation. |
| Best use case | Attendee list sales, ABM, partnership development, vendor targeting, executive outreach | Effective for both pre-event prospecting and post-event follow-up campaigns. |
| Limitations / risks | Attendance data unavailable | No current-year public attendee count or verified participant directory included in this report. |
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Information Technology & Services, Computer Software, Financial Services, Hospital & Health Care, Retail, Consumer Goods, Government Administration, Higher Education, Insurance, Management Consulting, Logistics & Supply Chain, Pharmaceuticals | Align target accounts with data-heavy buying organizations |
| Departments | Data, Analytics, IT, Engineering, Procurement, Finance, Operations, Transformation, Strategy | Reach both technical buyers and budget owners |
| Seniority | Manager, Director, VP, C-Level, Partner | Prioritize decision-makers and high-influence stakeholders |
| Job titles | Chief Data Officer, VP Data & Analytics, Director of Analytics, Director of Data Governance, Head of BI, CIO, CTO, Enterprise Architect, Procurement Director, Strategic Sourcing Manager, Program Manager | Focus on roles most likely to evaluate, approve, or influence buying |
| Geography | United States; Florida; Southeast U.S.; major metro hubs such as New York, Atlanta, Dallas, Chicago, Washington DC, Boston, Charlotte | Capture local, regional, and national attendees |
| Employee size | 500–10,000+; prioritize 1,000+ | Best fit for enterprise data and analytics programs |
| Keywords | data governance, analytics, BI, reporting, data quality, master data, cloud data, lakehouse, AI, enterprise architecture, digital transformation | Improve query precision for attendee and account discovery |
| Company type | Enterprise, public sector, higher education, consulting partners, regulated industry organizations | Match the summit’s executive and solution-buying audience |
| Revenue range | Mid-market to enterprise; prioritize higher-revenue firms | Ensures sufficient budget and active transformation programs |
Suggested Apollo Search Logic: (“Chief Data Officer” OR “VP Data” OR “Director of Analytics” OR “Director of Data Governance” OR CIO OR CTO OR “Enterprise Architect”) AND (analytics OR “data governance” OR “business intelligence” OR “data quality” OR “cloud data” OR AI) AND (enterprise OR healthcare OR financial services OR retail OR government OR higher education). Prioritize companies in the United States, especially Florida and Southeast corridor markets.
Please share the client website or product/service details. I will review the client offering and identify the highest-fit buyer companies, Apollo industries, seniority levels, departments, and job titles from this event.
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| Gartner Data & Analytics Summit official event page | Official organizer source | Event identity, category, and summit branding | High |
| Gaylord Palms official website | Venue source | Venue identity and location context | High |
| Gartner corporate website | Organizer website | Organizer ownership and market positioning | High |
| Gartner Newsroom | Organizer press resource | General Gartner event and corporate context | High |
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