🎯 Selling to this event's audience? Get a free tailored buyer list
Tell us your work email and our AI instantly builds a buyer list matched to Big Data LDN — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.
🔒 Get my buyer details Free · ~20 seconds
About this event
Big Data LDN (London) — Deep Research Buyer & Attendee Analysis
Show basics (from official event information)
- Event title: Big Data LDN
- Dates: Wednesday 23 September 2026 & Thursday 24 September 2026 (23–24 September 2026)
- Venue: Olympia London (Olympia Grand entrance and Olympia National Entrance)
- City / Country: London, United Kingdom
- Official daily opening hours:
- Wednesday 23 September 2026: 09:00–18:00
- Thursday 24 September 2026: 09:00–17:30
- Event positioning (official): The UK’s leading data, analytics and AI conference & exhibition; a hub for the data community to learn/share best practice, build relationships, and find tools to maximise the power of data, AI & analytics within business.
- Conference size (official): Over 400 seminars covering every aspect of data, AI & analytics.
- Senior track (official): A brand-new conference track called Data Driven LDN focused on senior professionals, including AI Agents, AI Governance & Data Products, with specialist speakers and high-quality networking.
- Featured example exhibitors mentioned (official): Snowflake, Databricks, Google Cloud, AWS, TikTok, Spotify (as part of conference insights / speakers mentions), and others including start-ups and data innovators.
1) Who attends (BUYERS / ATTENDEES)
Big Data LDN is designed primarily for data and AI business decision-makers who need pragmatic guidance, vendor solutions, and peer validation on how to adopt, govern, and operationalise data, analytics and AI. It also draws technology buyers and practitioner audiences who influence purchase decisions, evaluate platforms, and shape architecture standards.
Primary attendee groups (high-probability “buyer” layer)
- Senior data & AI leaders: People responsible for enterprise data strategy, analytics strategy, and AI adoption.
- Data/AI governance and risk professionals: Stakeholders aligned with governance, compliance, and controls (especially relevant to the “Data Driven LDN” senior track).
- Data product & platform owners: Teams building “data products” or internal platforms, including those accountable for enablement, adoption, and measurable value.
- Cloud and data platform buyers: Teams evaluating data warehouses/lakes, streaming, ETL/ELT, orchestration, and modern analytics stacks.
- Analytics leaders and engineering managers: Those who translate business needs into technical requirements for data and AI pipelines.
- Commercial stakeholders in data transformation: Demand-gen, digital transformation, and innovation leadership where data/AI is a strategic initiative.
Additional attendee groups (influencers & revenue accelerators)
- Solution architects & data architects: Evaluate feasibility, reference architectures, and integration patterns.
- ML engineers / data scientists: Validate tooling for experimentation and deployment readiness.
- Consulting and systems integrators: Attend to build pipelines, partner with platforms, and identify implementation opportunities.
- Start-ups and innovators: Participate as exhibitors and are often backed by strong technical and commercial teams that can identify pilot-fit enterprises.
Buyer fit note: Even though conferences often attract practitioners, Big Data LDN explicitly emphasises senior, governance, and product-oriented topics through “Data Driven LDN.” That increases the probability of capturing decision-influencing roles rather than only early-stage technical audiences.
2) Where the show is happening + attendee geographic origin
The event takes place at Olympia London in London, United Kingdom. Because it is positioned as the UK’s leading data, analytics & AI conference and exhibition, the base audience is highly likely to be concentrated across the UK while drawing meaningful interest from European and global technology communities.
Likely geographic origin of attendees (practical expectations)
- Primary: United Kingdom (London-centric + nationwide UK data/AI communities)
- Secondary: Europe (especially organisations with English-speaking teams, cross-border governance requirements, and pan-European cloud/data programmes)
- Selective global: International exhibitors and speakers (example large vendors are referenced on the official site), which typically brings additional international attendance and travelling teams.
Best targeting emphasis: UK-based enterprise buyers and UK/EU teams within multinational organisations that have UK analytics, governance, or cloud data platforms.
3) Audience reach (Local / National / Global)
Big Data LDN is positioned as the UK’s leading data/AI conference & exhibition, which strongly implies a national reach within the United Kingdom. The event’s vendor mix and the presence of globally recognised technology companies indicates it also achieves a global (or international) presence at the exhibitor and speaker level, and likely among attendee travel.
- Local: London (dense enterprise tech ecosystem, frequent attendee travel from Greater London)
- National: UK-wide (data leaders, governance teams, analytics teams from across the country)
- Global / International: Supported by international technology brands, start-ups, and cross-border data/AI initiatives
Operational implication for buyer lists: We typically see the highest relevance when targeting UK decision-makers first, then layering EU multinational roles (especially those tied to governance, platforms, or AI operationalisation).
4) Sample buyer company names (BUYERS ONLY) + websites
Below are sample buyer-fit company targets aligned with the event theme (data, analytics, AI governance, cloud data platforms, and data products). These are chosen as buyer archetypes rather than “random exhibitors” and represent organisations that frequently purchase data/AI platforms or related services. (In practice, we refine the final list after confirming your product fit.)
| Priority | Company | Website | Best Title to Target | Why This is a Good Buyer Fit |
|---|---|---|---|---|
| 1 | HSBC | hsbc.com | Head of Data Strategy / Chief Data Officer (CDO) / VP Data Governance | Large-scale governance-heavy data programmes where AI and analytics require strong controls and reusable data products. |
| 2 | Barclays | barclays.com | Director of Data & Analytics / Head of AI Governance / Data Platform Owner | Financial services organisations commonly evaluate modern data platforms and governance frameworks for responsible AI. |
| 3 | Vodafone | vodafone.com | Senior Manager, Data & AI / Director of Analytics Platform / AI Governance Lead | Telecoms rely on data-driven customer and operational analytics; AI governance and data product management are recurring needs. |
| 4 | BT Group | bt.com | Head of Data Platform / Director of Data Governance / Analytics Engineering Lead | Large enterprise data platforms plus governance programs; strong fit for buyers focused on operational analytics and platform modernization. |
| 5 | Sky | sky.com | Head of Data Science / Director of Data Products / Lead, AI & Analytics Governance | Media and services organisations increasingly invest in data products and AI for personalization and content intelligence. |
| 6 | Deliveroo | deliveroo.co.uk | Head of Data / Director of Machine Learning Operations / Analytics Platform Manager | High-volume event and marketplace data; strong need for streaming/analytics, ML ops, and responsible AI practices. |
| 7 | Just Eat Takeaway.com | takeaway.com | VP Data Engineering / Director of Data Products / Head of AI Governance | Marketplace analytics and ML adoption typically require scalable data products and clear governance for deployment. |
| 8 | Sainsbury’s | sainsburys.co.uk | Director of Customer Analytics / Data Governance Manager / Head of Data Products | Retailers invest heavily in customer data platforms and analytics; governance and compliant AI are critical. |
| 9 | Tesco | tesco.com | Head of Data & Analytics / Senior Manager, Data Governance / AI Product Lead | Enterprise analytics platforms with strong internal governance needs; frequently evaluates data and AI tooling. |
| 10 | Unilever | unilever.com | Global Head of Data Platforms / Director of Analytics / Data Product Owner | Global organisations invest in platform standardization, analytics enablement, and cross-business data products. |
| 11 | GSK | gsk.com | Director, Data & Analytics / Head of AI Governance / Data Platform Lead | Life sciences governance and data quality requirements make governance and AI oversight a major buying priority. |
| 12 | Roche | roche.com | Head of Data Strategy / Director Data Governance / AI Programme Lead | Strong fit for AI governance and data product initiatives in regulated environments. |
| 13 | Reckitt | reckitt.com | Head of Data Science / Analytics Platform Manager / Data Governance Lead | Consumer health and analytics-driven innovation typically involves modern data stacks and responsible AI governance. |
| 14 | Barclays Investment Bank (Barclays) | barclays.com | Quant Data Lead / AI Governance & Controls Manager / Head of Data Platform | High value data pipelines and governance-driven AI adoption for complex decision workflows. |
| 15 | NHS England (NHS) | england.nhs.uk | Data Platform Programme Lead / Head of Analytics / AI Governance Officer | Public sector data and analytics governance, plus AI oversight and operational use-cases where appropriate governance is essential. |
| 16 | Capgemini (Buyer + transformation teams) | capgemini.com | Data & AI Sales Director / Head of Data Platforms / Partner Alliance Lead | Consulting/transformation firms have strong relevance for enterprise platform evaluations and implementation partnerships. |
| 17 | Accenture | accenture.com | Data & AI Strategy Lead / Enterprise Data Transformation Lead / AI Governance Consultant | Frequent buyers of data/AI tooling and partners for governance, data product programs, and platform modernisation. |
| 18 | ITV | itv.com | Head of Data & Analytics / Director of Data Products / AI Adoption Lead | Media and streaming platforms depend on data products and analytics; AI adoption benefits from governance and engineering leadership. |
| 19 | Experian | experian.com | Director, Data Governance / Head of AI & Analytics / Data Product Leader | Data-first organisation with governance and data product workflows that align closely with the event’s themes. |
| 20 | Commerzbank (UK presence / EU) | commerzbank.com | Head of Data Governance / Director, Data Platforms / AI Oversight Lead | Banks typically treat AI governance and platform modernisation as strategic priorities with measurable risk controls. |
Top buyer-fit starting set (to prioritise first): HSBC, Barclays, Vodafone, BT Group, Tesco. These represent common “budget owners” and decision-makers across governance, platforms, and analytics transformation.
5) Job profiles, industries & event type
Event type
- Conference & exhibition focused on data, analytics & AI
- Seminar-heavy agenda: 400+ seminars
- Senior track: “Data Driven LDN” (AI Agents, AI Governance, Data Products)
Job profiles to target (highest buyer relevance)
- Chief Data Officer (CDO) / Head of Data Strategy
- Head of Data Governance / Data Governance Lead
- Director, AI Governance / AI Risk & Controls Lead
- Head of Data Platforms / Director of Data Engineering
- Analytics Platform Owner / Enterprise Analytics Lead
- Data Product Owner / Director of Data Products
- AI Programme Lead / Head of AI Transformation
- ML Engineering Manager / MLOps Lead
- Solution Architecture Lead (Data & AI) / Enterprise Data Architect
- Digital Transformation Lead (Data & AI)
- Security & Privacy for data/AI (where governance intersects)
Industries that typically align strongly
- Financial Services (governance, risk, responsible AI)
- Telecommunications
- Retail & Consumer (customer analytics and data products)
- Healthcare & Life Sciences (regulated data governance)
- Media & Entertainment (recommendation/data products)
- Consulting & Systems Integration (enterprise transformation)
- Public Sector / Health (analytics programmes and governance)
6) Estimated attendance (expected total footfall)
The official website content provided includes programme scale (400+ seminars) and venue details, but it does not provide a specific attendance number. Because we must not invent figures, we cannot reliably state an official attendance estimate from the text provided.
What we can do reliably for planning: We position Big Data LDN as a major UK data/AI congregation with a multi-track conference format. For list strategy, we typically model demand assuming a high volume of data/AI practitioners alongside a meaningful layer of senior governance and platform decision-makers due to the “Data Driven LDN” senior content.
If you share whether your target is senior buyers (governance/product/platform owners) or technical evaluators (architects/ML engineers), we will tailor the outreach density accordingly without over-indexing on roles that are unlikely to purchase your specific offering.
7) Key focus areas & buyer engagement
Key focus areas (officially aligned themes)
- Data-driven transformation and best practice sharing
- AI & analytics adoption across business functions
- AI Agents (capability and implementation approaches)
- AI Governance (controls, oversight, responsible deployment)
- Data Products (ownership models, operationalisation, reuse)
- End-to-end analytics and modern data platform topics (supported by 400+ seminars)
How buyers are likely to engage
- Seminar attendance and networking: Buyers attend sessions to validate vendor claims against real governance and implementation realities.
- Vendor evaluation behaviour: Given the conference scope and named major platforms, many attendees will compare capabilities, reference architectures, and governance approaches.
- Partnership and ecosystem discussions: Engagement commonly happens around how vendors integrate with existing data ecosystems and cloud environments.
What We recommend as messaging angle (based on attendee intent)
- If your product touches governance: lead with control frameworks, auditability, and policy-driven oversight.
- If your product touches data products: lead with reusability, ownership models, and lifecycle management.
- If your product touches AI Agents: lead with safety, orchestration, and operational deployment patterns.
- If your product touches analytics platforms: lead with performance, data quality workflows, and integration strategy.
8) Client-product fit validation (We need your website to refine “best buyers”)
We can generate the best buyer-attendee list recommendations only after we confirm your exact product requirements. The event is broad (data/analytics/AI) and “buyer fit” changes substantially based on whether your solution is governance, platform, tooling, consulting services, data products, AI enablement, or agent orchestration.
Please share the client website URL (or product name and 2–3 key use-cases). After we review it, We will:
- Identify the closest buyer segments for Big Data LDN (e.g., CDO/data governance leads vs. platform owners vs. AI governance and control owners).
- Prioritise roles whose day-to-day responsibilities most directly align to your value proposition.
- Select the most relevant industries within the event’s typical audience mix.
- Provide an expanded buyer table (beyond the sample above) mapped to target titles and fit rationales for your product.
Interim best-fit assumptions (until we see your website): We recommend focusing first on titles aligned with AI Governance, Data Product ownership, Enterprise Data Platforms, and analytics platform ownership, because those align directly with the event’s “Data Driven LDN” senior track themes.
9) Industry suggestions (aligned to the event theme)
Below are the most relevant industry options to use when building targeted buyer lists for Big Data LDN. These are selected to match the event’s focus on data, analytics and AI governance/product adoption.
- Information Technology & Services
- Computer Software
- Computer & Network Security (especially if your product includes governance, controls, risk or compliance)
- Internet (if your offering supports large-scale data/analytics in web platforms)
- Financial Services (AI governance and analytics are deeply regulated here)
- Telecommunications
- Health, Wellness & Fitness (only if relevant to healthcare analytics use-cases; for stricter healthcare governance we may also use Hospital/Health Care outside this list depending on your filters)
- Hospitality (if your solution applies to customer analytics and operational data products)
- Logistics & Supply Chain (if your data product improves forecasting, planning, or operations)
- Retail
- Media Production / Entertainment (for recommendation, personalization, and analytics pipelines)
- Market Research (if your offering supports analytics, measurement, and data products for insights)
- Professional Training & Coaching (if your solution includes enablement training for responsible AI/data literacy)
- Management Consulting (if you sell advisory or implementation accelerators for data/AI transformation)
Best starting set (most consistent fit): Information Technology & Services, Computer Software, Financial Services, Retail, Telecommunications, and Management Consulting.
Next step: We refine “best buyers” with your product
To produce the most accurate buyer shortlist for Big Data LDN, We need your client website. Please send your client website URL and we will respond with:
- A refined buyer target list (company + target title mapping)
- Role-level prioritisation aligned to Big Data LDN’s “Data Driven LDN” themes (AI Agents, AI Governance, Data Products)
- Industry filter recommendations tailored to your offering
- An outreach angle that matches the most likely buyer motivations at this specific event
Data sheet
Big Data LDN – Event Attendee & Buyer Profile Analysis
Event Date: 23–24 September 2026
Location: Olympia, London, United Kingdom
Event Status: Upcoming
Research Date: 30 June 2026
Event Overview
| Event Name | Big Data LDN |
| Event Date | 23–24 September 2026 |
| Event Status | Upcoming |
| Venue | Olympia London (Olympia Grand entrance and Olympia National Entrance) |
| City | London |
| State / Region | Greater London |
| Country | United Kingdom |
| Organizer | Reed Exhibitions Limited (RX) |
| Official Event Website | Big Data LDN |
| Event Type | Conference & Exhibition |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Business Services; Science & Research; Education & Training |
| Audience Reach | National with strong international participation likely |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for attendance volume; high for date, venue, organizer, and agenda positioning. |
| Main Purpose of Event | To connect the data, analytics, and AI community for learning, networking, solution discovery, and business development. |
About the Event
Big Data LDN is the UK’s leading data, analytics, and AI conference and exhibition. The official website positions the event as a central meeting point for the data community to learn best practices, build relationships, and identify tools that improve how businesses use data, AI, and analytics.
The event matters because it brings together senior decision-makers, technical practitioners, solution providers, and innovation-led organizations around enterprise data transformation. Its relevance is strongest for buyers and influencers involved in analytics platforms, AI governance, cloud data infrastructure, data products, and modern data operations.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| Data & Analytics Leaders | Enterprise and mid-market organizations adopting analytics, BI, and AI | Owns data strategy, platform selection, and roadmap priorities | Primary audience for data platforms, analytics tools, and AI solutions |
| CIO / CTO / IT Leadership | Large enterprises, digital-native firms, public sector IT teams | Approves architecture, cloud, security, and transformation budgets | High-value decision-makers for enterprise software and services |
| Data Engineering & Platform Teams | Organizations running modern data stacks | Influences technical evaluation and implementation | Important for tools covering pipelines, storage, governance, and orchestration |
| AI / Machine Learning Leaders | Companies operationalizing AI agents, ML models, and governance | Evaluates AI tools, model management, and responsible AI programs | Relevant for AI infrastructure, MLOps, and governance vendors |
| Procurement & Vendor Management | Enterprises buying software, cloud, and consulting services | Negotiates contracts, renewals, and supplier selection | Relevant for suppliers selling platform licenses and services |
| Business Intelligence / Reporting Leaders | Finance, operations, sales, and commercial teams | Influences dashboarding, reporting, and self-service analytics | Strong fit for visualization, governance, and analytics enablement vendors |
| Data Governance / Risk / Compliance | Regulated industries, public sector, and large enterprises | Shapes controls for data privacy, lineage, and AI governance | Useful for governance, cataloging, compliance, and security suppliers |
| Consultants / Systems Integrators | Advisory firms, SI partners, implementation specialists | Influences vendor shortlists and implementation recommendations | Good channel and referral audience for software suppliers |
| Product & Innovation Leaders | Digital products, platforms, and data-driven businesses | Uses data and AI to improve product strategy and user experience | Relevant for embedded analytics, AI features, and data products |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Host City: London | Very high | High | Major concentration of enterprise technology buyers and data teams |
| Host Region: Greater London / South East England | Very high | High | Nearby headquarters, digital businesses, consultancies, and public sector buyers |
| UK National Reach | High | High | Expected from finance, retail, healthcare, public sector, and tech hubs across the UK |
| European Business Hubs | Moderate to high | Medium | Likely participation from data and cloud buyers across Western Europe |
| Global / International | Moderate | Medium | International vendors, speakers, and enterprise teams may travel for the event |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| National | Primary classification | The event is anchored in London but clearly serves the UK’s broader data, analytics, and AI market. |
4. Sample Buyer Companies and Websites
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Snowflake | Data platform / enterprise technology | Named by organizer as an exhibitor example and aligns with data cloud buying audiences. | snowflake.com | VP Data, Head of Analytics, Data Platform Director | Confirmed Speaker Organization |
| Databricks | Data and AI platform | Named by organizer as an exhibitor example; strong fit for data engineering and AI budgets. | databricks.com | CIO, CTO, Head of Data Engineering | Confirmed Speaker Organization |
| Google Cloud | Cloud / data infrastructure | Mentioned in official website content as a speaker company and relevant to cloud data transformation. | cloud.google.com | Cloud Architect, IT Director, Platform Engineering Lead | Confirmed Speaker Organization |
| Technology / digital platform | Named by organizer as a speaker company; strong relevance for AI, data, and cloud decision-makers. | google.com | VP Engineering, CIO, Data Science Lead | Confirmed Speaker Organization | |
| Amazon Web Services (AWS) | Cloud infrastructure | Named by organizer as a speaker company and often a priority buyer for data, governance, and analytics partnerships. | aws.amazon.com | Cloud Program Manager, Data Platform Lead, Procurement Manager | Confirmed Speaker Organization |
| TikTok | Digital platform / media technology | Named by organizer as a speaker company; large-scale data, AI, and platform operations relevance. | tiktok.com | Head of Data, ML Engineering Manager, Analytics Director | Confirmed Speaker Organization |
| Spotify | Digital media / consumer technology | Named by organizer as a speaker company; strong data-driven product and personalization use case. | spotify.com | Product Analytics Lead, Data Scientist, VP Product | Confirmed Speaker Organization |
| RX Global | Event organizer / B2B services | Organizer and commercial stakeholder; relevant for event-tech, data, and marketing solutions buyers. | rxglobal.com | Commercial Director, Marketing Director, CRM Lead | Confirmed Organizer |
| London-based enterprise retailers and financial services firms | End-user buyers | High concentration in London for analytics, reporting, AI governance, and cloud modernization. | varies by organization | CIO, Head of Data, Procurement Director | Strong Market Fit, Attendance Not Confirmed |
| UK public sector digital teams | Government / public sector buyers | Data governance, AI policy, and analytics modernization are common priorities. | gov.uk | Digital Director, Data Lead, Commercial Manager | Strong Market Fit, Attendance Not Confirmed |
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Chief Data Officer / Head of Data | Data | C-Level / VP | Owns enterprise data strategy and platform decisions |
| 2 | CIO / CTO | IT | C-Level | Approves technology roadmap, cloud, and transformation investments |
| 3 | Director of Analytics / BI Director | Analytics / BI | Director | Drives tooling for reporting, insights, and self-service analytics |
| 4 | Data Engineering Manager | Data Engineering | Manager / Director | Influences architecture, pipelines, and implementation choices |
| 5 | AI / Machine Learning Lead | AI / Data Science | Lead / Manager | Evaluates AI platforms, model operations, and governance |
| 6 | Director of Procurement / Strategic Sourcing Manager | Procurement | Director / Manager | Supports supplier selection, renewals, and commercial negotiation |
| 7 | Data Governance Manager | Governance / Compliance | Manager / Director | Focuses on data quality, privacy, and policy control |
| 8 | Product Analytics Lead / Product Manager | Product | Manager / Director | Uses data to optimize product strategy and customer experience |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Information Technology & Services | Core market for data, cloud, analytics, and AI solutions | Enterprise software, data platforms, consulting |
| 2 | Computer Software | Major attendee and buyer segment for analytics and AI tooling | SaaS, data products, AI enablement |
| 3 | Banking | Data governance, analytics, risk, and AI use cases are highly relevant | Financial data platforms, compliance, reporting |
| 4 | Financial Services | Large analytics and AI spend profile | Data governance, cloud modernization |
| 5 | Retail | Customer analytics, demand forecasting, personalization | Commercial intelligence, AI recommendations |
| 6 | Hospital & Health Care | Data governance and operational analytics needs | Reporting, compliance, patient data platforms |
| 7 | Government Administration | Public sector digital transformation and data governance | Public sector analytics, AI policy, secure platforms |
| 8 | Management Consulting | Influences enterprise technology selection and implementation | Advisory, transformation, SI partnerships |
| 9 | Internet | Digital-native firms often attend for data scale and AI experimentation | Cloud data, ML ops, product analytics |
| 10 | Telecommunications | Large operational data volumes and AI use cases | Network analytics, customer intelligence |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Not publicly confirmed | Confirmed unavailable | Organizer website content reviewed | No official attendance number published on the reviewed page |
| Exhibitor count | Not publicly confirmed | Confirmed unavailable | Official website mentions exhibitor directory, but no count in reviewed text | Use exhibitor directory for list-building if accessible |
| Conference seminars | Over 400 seminars | Confirmed | Official website content | Supports strong speaker and content depth |
| Buyer count | Not publicly confirmed | Confirmed unavailable | No official buyer count published in reviewed text | Likely broad enterprise and technical audience |
| Speaker count | Not publicly confirmed in the reviewed text | Confirmed unavailable | Official agenda and speakers pages exist | Use agenda for contact discovery |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Data Platforms | Modernize storage, integration, and analytics foundations | Meet platform evaluators and enterprise buyers | Cloud data warehouse, lakehouse, integration services |
| AI Governance | Control risk, compliance, and responsible AI usage | Engage senior leaders focused on policy and controls | Governance software, policy tooling, audit support |
| Analytics & BI | Better reporting and self-service insights | Target business and technical users with immediate needs | Visualization, dashboards, semantic layer |
| Cloud Transformation | Scale infrastructure and reduce legacy constraints | Capture migration and modernization discussions | Cloud consulting, managed services, migration tooling |
| Data Products | Monetize and operationalize data assets | Attract product leaders and innovation teams | Data product platforms, governance, APIs |
| AI Agents | Evaluate emerging automation and decision support use cases | Use conference content to identify innovation-minded buyers | Agent frameworks, orchestration, LLM tooling |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Very High | The event is centered on data, analytics, and AI decision-makers and influencers. |
| Decision-maker availability | High | Conference-and-exhibition format typically attracts senior technical and commercial leaders. |
| Data collection potential | High | Official agenda, exhibitor directory, speaker pages, and registration tools support list-building. |
| Apollo targeting potential | Very High | Strong overlap with technology, data, cloud, consulting, and enterprise buyer profiles. |
| Geographic targeting potential | High | London and UK-wide targeting is highly relevant; international tech hubs also matter. |
| Best outreach approach | Account-based outreach | Focus on data leaders, AI governance stakeholders, and procurement decision-makers before the event. |
| Overall lead quality | Very High | Excellent event for B2B attendee list building, solution targeting, and enterprise pipeline generation. |
| Best use case | B2B lead generation and buyer profiling | Ideal for targeting data, analytics, AI, cloud, governance, and transformation buyers. |
| Limitations / risks | Attendance figures not published in reviewed content | Use official directories and registration intelligence rather than assumed footfall volumes. |
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Information Technology & Services; Computer Software; Financial Services; Banking; Government Administration; Management Consulting; Retail; Internet; Telecommunications; Hospital & Health Care | Match the core data and analytics buyer universe |
| Departments | IT; Engineering; Data; Analytics; Procurement; Operations; Product; Transformation; Innovation; Compliance | Reach both technical evaluators and commercial approvers |
| Seniority | Manager; Director; VP; CXO | Prioritize decision-makers and budget holders |
| Job titles | CIO OR CTO OR "Chief Data Officer" OR "Head of Data" OR "Director of Analytics" OR "Data Engineering Manager" OR "AI Lead" OR "Procurement Director" OR "Strategic Sourcing Manager" OR "Platform Engineering Lead" | Target the most commercially relevant job functions |
| Geography | United Kingdom; Greater London; South East England; Europe | Align with event location and likely travel radius |
| Employee size | 201–500; 501–1,000; 1,001–5,000; 5,001+ | Best fit for budgeted data and AI buying cycles |
| Keywords | data, analytics, AI, machine learning, governance, cloud, lakehouse, dashboard, BI, MLOps, data product | Refine to active solution buyers and practitioners |
| Company type | Enterprise; Mid-market; Public sector; Consulting / SI; Technology vendor | Covers both end-user buyers and implementation influencers |
Suggested Apollo Search Logic: ("data" OR analytics OR AI OR "machine learning" OR governance OR cloud OR "data platform" OR lakehouse) AND (CIO OR CTO OR "Head of Data" OR "Director of Analytics" OR "Procurement Director" OR "Data Engineering Manager") AND geography = United Kingdom.
Client Fit Review Required
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.
Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| Big Data LDN official website | Official organizer source | Dates, venue, city, organizer, event format, audience positioning, seminar volume, and official content themes | Very High |
| Olympia London | Venue website | Venue identification and location context | High |
| RX Global | Organizer corporate website | Organizer identity and corporate ownership context | High |
🎯 Selling to this event's audience? Get a free tailored buyer list
Tell us your work email and our AI instantly builds a buyer list matched to Big Data LDN — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.
🔒 Get my buyer details Free · ~20 seconds