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About this event
CDAO Chicago — Deep Research Buyer & Attendee Intelligence
Event Snapshot (What CDAO Chicago is)
CDAO Chicago is a focused leadership conference centered on the evolving role of data leadership—typically bringing together Chief Data Officer–level executives and adjacent data, analytics, governance, and information management stakeholders. The Chicago edition usually concentrates on practical themes such as data strategy execution, governance and compliance, operating models, data quality, master data management (MDM), data platforms, analytics acceleration, and how organizations can build sustainable, scalable data capabilities.
Because the event is named for “CDAO,” the strongest buyer density tends to be on senior data leadership and the organizations that support enterprise data operations—meaning buyers are often vendor teams selling data platforms, governance tooling, data integration, data quality, data security, data cataloging, or analytics enablement services. We can also see demand from internal data program sponsors inside enterprises who want to benchmark, validate roadmaps, and compare vendors.
1️⃣ Who attends (BUYERS / ATTENDEES)
CDAO Chicago is most commonly attended by enterprise data leaders and practitioners, along with solution providers that sell into enterprise data transformation programs. While many conferences include a broad spectrum, CDAO-type events generally skew toward leadership and transformation roles rather than purely technical individual contributors.
Primary attendee groups (Buyer / high-value attendee profile)
- Chief Data Officer / Head of Data (or equivalent titles such as VP Data, Director of Data Strategy)
- Data Governance leadership (Data Governance Officer, Director of Governance, Governance Program Manager)
- Data & analytics platform leadership (VP Analytics, Head of Data Platforms, Director of Analytics Engineering)
- Enterprise data architecture leadership (Data Architecture Lead, Enterprise Architect for Data)
- Data quality and MDM leadership (Director of Data Quality, MDM Program Owner)
- Privacy, risk, and compliance stakeholders aligned to data management (sometimes as supporting attendees)
- Transformation / operating model leaders focused on building repeatable data delivery (Program Managers, Transformation Leads)
Secondary attendee groups (Still valuable, but buyer intent varies)
- Data engineering leadership (Director/Manager, Data Engineering)
- Analytics leadership (Head of BI, Analytics Strategy)
- Information management stakeholders (Director of Information Governance, Records/Data Lifecycle)
- Consulting and systems integration leaders (Partners, Practice Leads)
For attendee list research, the most monetizable segment is usually not the most junior practitioner; it is the sponsor layer that influences vendor evaluation, roadmap funding, governance policy, and tool selection.
2️⃣ Where the show is happening + attendee geographic origin
Venue: Chicago, Illinois, USA (exact venue details can vary by year and run schedule; we recommend confirming the official event listing once provided).
Attendee geographic origin (typical pattern for Chicago editions)
- Local / regional: Chicago metro, Midwest enterprises (Illinois, Indiana, Wisconsin, Michigan, Ohio, Iowa)
- National: Large organizations with HQ or regional offices across the U.S. often send data leadership teams
- Infrequent international presence: Sometimes a small number of global enterprises attend, but the “center of gravity” is typically North America
How we should interpret geographic value
Chicago is a strong hub for finance, healthcare, retail, logistics, manufacturing, and insurance—sectors that frequently invest in data governance, regulated data handling, and scalable analytics. That means geographic targeting plus industry targeting together tends to outperform geographic targeting alone.
3️⃣ Audience reach (Local / National / Global)
Audience reach: primarily National (USA) with strong regional Midwest participation.
CDAO Chicago generally positions as a leadership venue rather than an ultra-global event. Most buyer attendance comes from companies with national data programs, meaning the “reach” is more U.S.-wide than purely local. Global brands are possible but less likely to dominate compared with domestic enterprise data teams.
4️⃣ Sample buyer company names (BUYERS ONLY) + Websites
Below is a buyer-oriented sample set we would typically target for attendee intelligence—focused on enterprise data platforms, governance tooling, analytics enablement, and data management services that align strongly with CDAO leadership interests.
| Priority | Company | Website | Best Title to Target | Why This is a Good Buyer Fit |
|---|---|---|---|---|
| 1 | Alteryx | https://www.alteryx.com | VP, Data & Analytics Transformation / Director, Analytics Enablement | Strong fit for analytics acceleration and self-service governance patterns; commonly evaluated by enterprise analytics leaders. |
| 2 | Databricks | https://www.databricks.com | Global Head of Data Platforms / Director, Data Engineering Strategy | High alignment with modern data platforms and the data/AI stack; frequently sits in CDAO platform roadmaps. |
| 3 | Snowflake | https://www.snowflake.com | Director, Data Platform Strategy / VP, Data & Analytics | Commonly evaluated for governed data sharing, analytics acceleration, and scalable enterprise warehousing. |
| 4 | Collibra | https://www.collibra.com | VP, Data Governance / Director, Data Governance Programs | Direct overlap with data cataloging, governance workflow, and accountability—high-intent audience match. |
| 5 | Informatica | https://www.informatica.com | Director, Data Quality & MDM / VP, Data Management | Strong alignment with MDM, data integration, and quality—frequently core governance requirements. |
| 6 | Stibo Systems | https://www.stibosystems.com | MDM Product Lead / Director, Master Data Management | MDM is a recurring governance + quality initiative; best fit for enterprises scaling product and customer master data. |
| 7 | Experian | https://www.experian.com | Director, Data Quality / Head of Data Solutions | Fits data quality, identity, and enrichment programs frequently sponsored by data governance offices. |
| 8 | OneTrust | https://www.onetrust.com | Director, Data Privacy & Governance / VP, Privacy Programs | Useful overlap where governance includes privacy and risk controls aligned to data leadership. |
| 9 | SAS | https://www.sas.com | Head of Analytics Strategy / Director, Data & AI Platforms | Enterprises use SAS for analytics, governance-adjacent capabilities, and regulated analytics programs. |
| 10 | Talend (Reltio brand ecosystem varies by market) | https://www.talend.com | Director, Data Integration / VP, Data Engineering & Governance | Direct alignment with integration and orchestration initiatives that CDAO stakeholders sponsor. |
| 11 | TIBCO Software | https://www.tibco.com | Director, Data Integration / VP, Data Platform Solutions | Strong match for enterprise integration patterns and governed data movement requirements. |
| 12 | Collibra (Data Lineage & governance ecosystem) | https://www.collibra.com | VP, Data Intelligence / Director, Data Catalog Strategy | For organizations building lineage, stewardship, and adoption—high relevance to CDAO agenda themes. |
| 13 | Workday (data governance adjacencies in HR analytics) | https://www.workday.com | Director, Data Strategy / Head of Analytics Governance | Many enterprises evaluate governed analytics for HR, workforce planning, and finance—data leadership common stakeholders. |
| 14 | Deloitte (data & analytics services) | https://www2.deloitte.com | Partner, Data Governance & Transformation / Managing Director, Data Strategy | Consulting buyers often attend/engage at CDAO events to align transformation roadmaps and governance programs. |
| 15 | Accenture (data platforms & governance) | https://www.accenture.com | Data Transformation Lead / VP, Data & Analytics Consulting | High fit for enterprises commissioning operating model + platform programs led by CDAO-like stakeholders. |
| 16 | IBM Consulting (data modernization) | https://www.ibm.com/consulting | Director, Data & AI Transformation / Partner, Data Platform Enablement | Enterprises use IBM consulting for governance and modernization, aligning strongly to data strategy execution. |
| 17 | Google Cloud | https://cloud.google.com | Director, Data Platform Solutions / Head of Data Governance Offerings | Cloud governance and analytics stack often intersects with data leadership tool evaluation cycles. |
| 18 | Microsoft | https://www.microsoft.com | Director, Data Platform & Governance / VP, Enterprise Data Strategy | Microsoft’s enterprise ecosystem frequently supports governance, compliance alignment, and scalable analytics operations. |
| 19 | Amazon Web Services (AWS) | https://aws.amazon.com | Director, Data Platform GTM / VP, Enterprise Analytics Solutions | Enterprises evaluate governed data pipelines and platform choices aligned with CDAO modernization agendas. |
| 20 | Capgemini (data governance & integration) | https://www.capgemini.com | Director, Data Strategy & Governance / Practice Lead, Data & Analytics | Strong fit for end-to-end programs—operating model, governance, and platform modernization—sponsored by data leadership. |
Top buyer samples to send first (highest “intent overlap” with CDAO themes): Collibra, Informatica, Databricks, Snowflake, Experian, OneTrust, Stibo Systems, Databricks/Snowflake cloud stack vendors, and major data transformation consultancies.
5️⃣ Job profiles, industries & event type
Best job profiles to target
- Chief Data Officer (CDAO) / Chief Data Officer
- Head of Data / VP Data / Director of Data Strategy
- Director, Data Governance / Data Governance Officer / Data Stewardship Lead
- Director, Data Quality
- Head of Data Platforms / Director, Data Platforms
- Enterprise Data Architect / Data Architecture Lead
- Manager/Director, MDM (Master Data Management)
- VP/Director, Analytics Strategy / Analytics Engineering
- Program Director / Transformation Lead (Data & Analytics Transformation)
- Privacy & Risk alignment roles (as governance partners): Privacy Program Director, Compliance Data Lead
Industries & why they match CDAO Chicago (using the provided industry categories)
CDAO-type conferences tend to pull from enterprises investing in governance, analytics modernization, data quality, and regulated data handling. The best matching industry filters to use (from the provided list) are:
- Computer Software (data platforms, governance products, analytics enablement)
- Computer & Network Security (data security alignment, governance tooling)
- Information Technology & Services (data transformation services)
- Information Services (data services, data cataloging, enrichment)
- Market Research and Management Consulting (data insights + transformation advisory)
- Financial Services and Insurance (regulated governance + data quality)
- Health, Wellness & Fitness (health data governance and analytics, where applicable)
- Hospital & Health Care (often present due to data stewardship needs)
- Logistics & Supply Chain (operational analytics, master data, quality)
- Retail (customer/product master data + analytics)
- Telecommunications (customer data governance, identity, quality)
Event type
Primary event type: Data Strategy / Data Governance / Enterprise Analytics Leadership (enterprise transformation, operating models, and platform modernization).
6️⃣ Estimated attendance (expected total footfall)
Estimated attendance: ~400–900 total attendees.
CDAO leadership conferences are typically smaller than mass trade shows, but the buyer density per attendee can be high because the audience is curated toward enterprise data leadership and solution decision-makers. We recommend we validate the exact cap/registration numbers once the official CDAO Chicago listing is shared for the target year.
7️⃣ Key focus areas & buyer engagement
Typical CDAO Chicago agendas (and therefore likely buyer “hooks”) usually revolve around:
Key focus areas
- Enterprise Data Strategy Execution (turning strategy into operational plans)
- Data Governance Operating Model (stewardship, accountability, workflows)
- Data Quality & Trust (quality metrics, profiling, remediation)
- Master Data Management (customer/product master consistency)
- Data Platforms Modernization (cloud, lakehouse patterns, scalable pipelines)
- Metadata, Catalog, Lineage & Discovery (visibility and adoption)
- Compliance / Privacy alignment where data governance intersects regulatory requirements
- Analytics acceleration & responsible use (bridging governance with AI/BI enablement)
Buyer engagement approach that works for this event
Since CDAO Chicago attendees are leadership-focused, the most effective engagement angle typically emphasizes outcomes rather than technical features. Buyers respond well to:
- “How to operationalize governance at scale” positioning
- “Data quality ownership and remediation workflow” frameworks
- “Governed data enablement” for analytics and AI readiness
- “Reducing time-to-discovery and improving adoption” through catalog/lineage
- “MDM and trust for customer/product data” business impact messaging
8️⃣ Client-product fit note (we need your client website)
We can absolutely refine the “best buyers” for CDAO Chicago based on your client requirements and product. To do that accurately, we need:
- Your client website URL (the exact homepage or product page we should review)
- Client product category (e.g., data governance software, data quality, integration services, privacy tooling, analytics platform, MDM, consulting)
- Target buyer type (enterprise buyers vs. SMB; industry preference; deal size range, if relevant)
Reply with your client website and we will respond with:
- Best buyer company list (ranked) mapped to the CDAO attendee intent
- Job titles to target for maximum conversion likelihood
- Recommended industries (using the provided Apollo industry list categories) that match your client’s offer
- Buyer fit score per segment
9️⃣ Industry suggestions (from the provided Apollo industry list)
If we need to start without your client website yet, the best initial industry selections for CDAO Chicago attendee research are:
- Computer Software
- Computer Hardware (only if your client sells data infrastructure components)
- Information Technology & Services
- Information Services
- Computer & Network Security (if governance/security/privacy is a product pillar)
- Management Consulting
- Market Research (for analytics/insights-focused offerings)
- Financial Services and Insurance (for governed data and compliance drivers)
- Logistics & Supply Chain (operational master data + quality)
- Retail (customer/product data trust initiatives)
- Telecommunications (large-scale customer data governance)
- Health, Wellness & Fitness and Hospital & Health Care (when relevant to data stewardship and compliance)
Final Recommendation (How we should position the research)
CDAO Chicago is a strong event for buyer-focused attendee intelligence because the audience is anchored in enterprise data strategy, governance, and platform decisions—areas where organizations are willing to invest and where sponsorship/vendor engagement is common.
The best results come from combining: job-title targeting (CDAO/Head of Data/Governance/MDM/Data Quality/Platform leadership) + industry targeting (software/services/financial/insurance/telecom/retail/logistics) + agenda-aligned keywords (data governance, data quality, MDM, catalog, lineage, operating model, analytics enablement).
Next step: Please share your client website URL so we can review your product and return a ranked “best buyers” list tailored to your exact client fit for CDAO Chicago.
Data sheet
| Event Name | CDAO Chicago |
| Event Date | 13–14 August 2025 |
| Event Status | Completed |
| Venue | DoubleTree by Hilton Hotel Chicago - Magnificent Mile |
| City | Chicago |
| State / Region | Illinois |
| Country | United States |
| Organizer | Corinium Global Intelligence (official event series organizer) |
| Official Event Website | Official event page / event series website |
| Event Type | Conference / summit focused on data, analytics, AI, and governance leadership |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Business Services, Science & Research, Banking & Finance, Medical & Pharma, Logistics & Transportation |
| Audience Reach | National, with selective North American reach |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Medium. Venue and event details are confirmed; public attendance totals were not confirmed in available official materials. |
| Main Purpose of Event | To connect senior data, analytics, AI, governance, and digital leaders for benchmarking, vendor evaluation, peer learning, and solution sourcing. |
CDAO Chicago is a senior leadership conference within the CDAO event series, bringing together chief data and analytics officers, AI and machine learning leaders, data governance executives, and digital transformation stakeholders. The program is designed around executive briefings, peer exchange, and solution evaluation across data strategy, modernization, governance, privacy, and responsible AI.
The event matters because data leadership has become a board-level priority across enterprise, public sector, and regulated industries. It is especially relevant for vendors serving analytics, data management, cloud, AI, governance, cybersecurity, and enterprise transformation use cases, making it a strong event for B2B lead generation and executive-level outreach.
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Chief Data & Analytics Leadership | Enterprise, healthcare, financial services, retail, manufacturing, public sector | Budget ownership, platform selection, strategy approval | Primary audience for analytics, AI, and data platform vendors |
| Data Governance / Data Management Teams | Regulated and data-intensive enterprises | Tool evaluation, policy enforcement, vendor shortlisting | Strong fit for MDM, data quality, catalog, lineage, and compliance solutions |
| AI / Machine Learning Leaders | Large enterprises, digital-native firms, innovation labs | Technical evaluation and use-case prioritization | Relevant for AI platforms, model governance, MLOps, and GenAI vendors |
| CIO / CTO / Digital Transformation Leaders | Enterprise IT, shared services, public sector, healthcare systems | Technology roadmap and enterprise architecture decisions | High-value targets for cloud, integration, security, and modernization suppliers |
| Privacy / Risk / Compliance Stakeholders | Financial services, healthcare, insurance, government | Controls, governance, and approval influence | Relevant for governance, security, data protection, and audit solutions |
| Operations / Business Process Leaders | Large operational enterprises and process-heavy organizations | Process improvement and productivity buying influence | Useful for automation, analytics, workflow, and reporting tools |
| Vendors, Consultancies, and System Integrators | Implementation firms, advisory firms, technology partners | Partnership building, channel influence, co-sell potential | Important for services, alliances, and enterprise solution ecosystems |
| Media / Analysts / Associations | Industry media, analyst firms, trade groups | Influence, education, market visibility | Useful for thought leadership and ecosystem engagement |
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Host city: Chicago | High local attendance from enterprise and consulting communities | High | Major U.S. business hub with strong data, finance, healthcare, and manufacturing presence |
| Host state / region: Illinois / Midwest | Strong regional attendance from Illinois, Indiana, Wisconsin, Michigan, Ohio, Minnesota | High | Midwest enterprise corridor is a major source of data and analytics decision-makers |
| Nearby business hubs | Executives from New York, Dallas, Atlanta, San Francisco Bay Area, Washington DC | Medium | Relevant where national enterprise teams travel for executive networking and vendor evaluation |
| National reach | Strong U.S. national buyer reach | High | CDAO-branded events typically attract senior leaders from multiple sectors across the country |
| International reach | Limited but possible from Canada and global enterprises with U.S. operations | Low to Medium | Primarily U.S.-focused; international participation is likely selective |
| Reach Level | Assessment | Explanation |
|---|---|---|
| National | Primary classification | The event is best viewed as a U.S. national executive conference with strong Midwest gravity and selective participation from other major business hubs. |
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| United Airlines | Enterprise operator | Large data, operations, and customer analytics environment | united.com | CDAO, VP Data, Analytics Director, AI Director | Strong Market Fit, Attendance Not Confirmed |
| AbbVie | Pharmaceutical enterprise | Regulated data and analytics use cases in life sciences | abbvie.com | Head of Data, Analytics VP, Governance Lead | Strong Market Fit, Attendance Not Confirmed |
| McDonald’s | Retail / restaurant enterprise | Large-scale customer and operational analytics need | mcdonalds.com | Chief Data Officer, Insights Director, Digital Analytics Lead | Strong Market Fit, Attendance Not Confirmed |
| Allstate | Insurance enterprise | Data governance, risk, and AI use-case priorities | allstate.com | Data Strategy VP, Risk Analytics Director, CTO Office | Strong Market Fit, Attendance Not Confirmed |
| JPMorganChase | Financial services | Large-scale analytics, compliance, and AI governance requirements | jpmorganchase.com | Chief Data Officer, AI Governance Lead, Data Platform VP | Strong Market Fit, Attendance Not Confirmed |
| Kroger | Retail / grocery enterprise | Customer analytics, supply chain data, and retail AI use cases | kroger.com | VP Analytics, Data Science Director, Digital Transformation Lead | Strong Market Fit, Attendance Not Confirmed |
| Caterpillar | Industrial manufacturing | Manufacturing analytics, digital operations, and industrial AI | cat.com | IT Director, Data Platform Leader, Analytics VP | Strong Market Fit, Attendance Not Confirmed |
| Boeing | Aerospace / defense enterprise | Complex data governance, engineering, and supply chain analytics | boeing.com | Chief Data Officer, Engineering Analytics Director, CIO | Strong Market Fit, Attendance Not Confirmed |
| Northwestern Memorial HealthCare | Healthcare system | Clinical, operational, and compliance-heavy data environments | nm.org | CDAO, Analytics Director, Data Governance Manager | Strong Market Fit, Attendance Not Confirmed |
| U.S. Department of Health and Human Services | Government / procurement | Public-sector data governance, modernization, and AI oversight | hhs.gov | Data Officer, IT Director, Program Manager, Procurement Lead | Strong Market Fit, Attendance Not Confirmed |
| Accenture | Consulting / systems integrator | Common buyer and partner in enterprise data transformation | accenture.com | Managing Director, Data Practice Lead, Partner, Sales Director | Strong Market Fit, Attendance Not Confirmed |
| Deloitte | Consulting / advisory | Advises on data, AI, governance, and operating model change | deloitte.com | Principal, Partner, Analytics Leader, AI Strategy Director | Strong Market Fit, Attendance Not Confirmed |
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Chief Data Officer | Data / Analytics | C-level | Primary strategic buyer for data platforms, governance, and AI readiness |
| 2 | Chief Analytics Officer | Analytics | C-level | Owns analytics strategy and vendor selection for decision intelligence |
| 3 | VP Data & Analytics | Data / Analytics | VP / SVP | Influences platform, services, and transformation budgets |
| 4 | Director of Data Governance | Governance / Compliance | Director | Evaluates governance, catalog, quality, and policy solutions |
| 5 | Head of AI / ML | AI / Innovation | Director / VP | Relevant for AI tooling, model governance, and deployment platforms |
| 6 | CIO | Information Technology | C-level | Enterprise buyer for core technology and modernization initiatives |
| 7 | CTO / VP Engineering | Technology / Engineering | C-level / VP | Influences architecture, data platform, and integration decisions |
| 8 | Director, Business Intelligence | Analytics / BI | Director | End-user champion for dashboards, reporting, and data visualization |
| 9 | Data Platform Manager | IT / Data Engineering | Manager | Operational buyer for cloud, pipeline, warehouse, and tooling decisions |
| 10 | Data Science Manager | Data Science | Manager | Evaluates modeling, experimentation, and AI tool stacks |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Information Technology & Services | Core technology audience for data platforms and transformation | Enterprise software, services, integration |
| 2 | Computer Software | Strong fit for analytics, AI, governance, and data tooling | Platform vendors and SaaS providers |
| 3 | Financial Services | Highly regulated data environment with strong governance demand | Compliance, risk, analytics, AI governance |
| 4 | Hospital & Health Care | Healthcare data governance and analytics modernization | Clinical analytics, compliance, reporting |
| 5 | Pharmaceuticals | Data-heavy, regulated, and research-centric buying environment | Research data, governance, AI, compliance |
| 6 | Retail | Customer, supply chain, and personalization analytics demand | Merchandising, forecasting, loyalty analytics |
| 7 | Airlines/Aviation | Operational optimization and customer analytics use cases | Operations intelligence, forecasting, AI |
| 8 | Automotive | Manufacturing and supply chain data transformation | Industrial analytics, planning, data ops |
| 9 | Insurance | Risk and governance intensive; strong AI and analytics demand | Claims analytics, fraud, compliance |
| 10 | Government Administration | Public-sector modernization and responsible AI adoption | Data governance, procurement, digital services |
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Not publicly confirmed | Confirmed unavailable | Organizer materials reviewed; no public total attendance found | Use with caution for list-sizing forecasts |
| Exhibitor count | Not publicly confirmed | Confirmed unavailable | No confirmed exhibitor count located in accessible official materials | Potentially limited expo footprint versus keynote-led programming |
| Buyer count | Not publicly confirmed | Confirmed unavailable | No official buyer list published for the 2025 edition | Use attendee persona targeting rather than company-count assumptions |
| Speaker count | Not publicly confirmed in this report | Unavailable here | Official agenda may contain the final speaker roster | Speaker organizations can be used for prospecting if verified from agenda pages |
| Historical attendance | Not publicly confirmed by the organizer | Historical / prior-year evidence only | Event series branding indicates a recurring executive conference format | No numeric historical estimate included without official confirmation |
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Data Governance | Policy, stewardship, lineage, and control | Executive discussions on risk reduction and operating model | Catalog, lineage, governance workflow tools |
| Analytics Modernization | Faster reporting and better decision support | Benchmarks and roadmap sessions | BI, semantic layer, lakehouse, visualization |
| AI Strategy | Responsible GenAI and machine learning deployment | AI governance and use-case discovery | AI platforms, MLOps, model risk tools |
| Cloud Data Infrastructure | Scalable and secure storage/compute | Technical evaluation of deployment models | Cloud platforms, data warehousing, integration |
| Privacy and Compliance | Control frameworks and audit readiness | Solution demos for regulated workflows | Policy, consent, compliance, DLP |
| Data Quality / MDM | Trusted data for reporting and automation | Problem-solution fit conversations | Master data, validation, enrichment |
| Data Security | Protection of sensitive enterprise data | Executive risk framing and security alignment | Data security posture, masking, access control |
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Very High | The audience is tightly aligned to enterprise data, analytics, AI, and governance buying decisions. |
| Decision-maker availability | High | C-level and director-level data leaders are likely core attendees. |
| Data collection potential | High | Strong for executive target lists, speaker-driven outreach, and account-based prospecting. |
| Apollo targeting potential | Very High | Clear job-title, industry, and seniority filters map well to the attendee profile. |
| Geographic targeting potential | High | Best targeted nationally, with emphasis on Chicago, Midwest, and major enterprise hubs. |
| Best outreach approach | Executive ABM + solution-based messaging | Lead with business outcomes, compliance, modernization, and ROI. |
| Overall lead quality | Very High | Strong event for executive-level lead generation, list building, and event-follow-up campaigns. |
| Best use case | B2B attendee list building and account targeting | Ideal for sellers of data, analytics, AI, compliance, cloud, and transformation solutions. |
| Limitations / risks | Moderate | No publicly confirmed attendance total in the reviewed materials; buyer list is not officially published here. |
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Information Technology & Services, Computer Software, Financial Services, Hospital & Health Care, Pharmaceuticals, Retail, Government Administration, Consulting, Automotive, Airlines/Aviation | Match the highest-probability attendee verticals |
| Departments | Data, Analytics, IT, Digital Transformation, Operations, Compliance, Risk, Innovation | Identify functional buyers |
| Seniority | C-level, VP, Director, Head of, Senior Director, Manager | Prioritize decision-makers and strong influencers |
| Job titles | Chief Data Officer, Chief Analytics Officer, CDAO, VP Data, Director of Analytics, Data Governance Director, Head of AI, CIO, CTO, BI Director, Data Science Director | Direct attendee-title matching |
| Geography | Chicago, Illinois, Midwest, United States | Focus on host-market proximity while keeping national scope |
| Employee size | 500–10,000+, with emphasis on enterprise accounts | Align with executive data programs and budget ownership |
| Keywords | data governance, analytics, AI, machine learning, GenAI, data quality, data platform, data strategy, cloud modernization, business intelligence | Broaden capture beyond title-only matching |
| Company type | Enterprise, public sector, regulated industries, consultancies, system integrators | Focus on organizations with active data transformation budgets |
| Technologies | Cloud data platforms, BI, MDM, data catalog, governance, security, AI tooling | Find buyers already investing in adjacent stack categories |
| Revenue range | $100M+; prioritize $500M+ for enterprise sales motions | Increase likelihood of executive sponsorship and funded initiatives |
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| Corinium Global Intelligence – CDAO event series | Official organizer / event series | Organizer identity, event branding, conference positioning | High |
| DoubleTree by Hilton Hotel Chicago - Magnificent Mile | Venue website | Venue confirmation and location context | High |
| CDAO Chicago official event page | Official event page | Event dates, city, general event positioning | High |
| CDAO Chicago agenda page | Official agenda / program | Program themes, likely attendee functions, speaker categories | Medium to High |
| CDAO Chicago speakers page | Official speaker directory | Speaker profile types and executive audience inference | Medium to High |
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