Description
Data Centre Database Atlas Tracker by Idem Est Research: Make faster, more confident data centre decisions
Data Centre Database Atlas is a practical dataset used by buyers and sellers of data centre services, investors, analysts, real estate professionals, construction companies, and public authorities. It brings the market into one place so you can quickly answer:
- Where are the data centres in my target markets?
- Who operates and owns them?
- Which sites are active now, and which are in the pipeline?
- Where is capacity growth likely to concentrate?
What teams use it for
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- DC Market intelligence and sourcing
- Network planning and target prioritisation
- DC Portfolio rollups and diligence
- DC Mapping clusters and pipeline activity
- Build a market map in minutes, not days
- Create a consistent target list for BD, procurement, or investment screening
- Track operators and portfolios across multiple sites
- Support internal briefs with clear maps and summaries
- Use the MW forecast and AI share view to inform infrastructure and planning discussions
What you get
- Data centre sites across Australia and New Zealand, organised so you can filter, sort, and map quickly
- Consistent site and company identifiers to help you track portfolios and avoid duplicates
- Clean locations with coordinates and standardised address fields
- Practical signals such as lifecycle stage and listing status to help separate live sites from planned projects
- Enrichment such as built-out power (MW), whitespace, PUE, tier design, year online, and building size
Country coverage
Starting with Australia and New Zealand today, with Southeast Asia expansion on the roadmap. Need another geography? Tell us what to prioritise next.
Available now
- Australia 280+ (180+ operational, 100+ future DCs)
- New Zealand
Planned next
- Malaysia
- Indonesia
- Thailand
- Vietnam
Target Audience
Built for decision makers who need data centre clarity, fast.
Past clients include
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Data Centre Real Estate Investment Trusts (REITs): market mapping, portfolio benchmarking, and diligence support
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Data Centre Construction Contractors: pipeline visibility, opportunity sizing, and bid prioritisation
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Data Centre Infrastructure Providers: network planning, coverage analysis, and target account selection
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New entrants: fast market orientation, competitor mapping, and site shortlisting
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Consultants, consultancies, and advisory firms: repeatable market research, client deliverables, and modeling inputs
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Corporate and government agencies: planning and procurement support, regional capacity monitoring, and infrastructure strategy
Pick the data you need
Build exports that match your workflow, from lightweight mapping files to enriched diligence datasets.
Core fields
- Site name, site ID
- Parent ID (when applicable)
- Company name and company ID
- Lifecycle stage, listing type, capacity type
- Latitude, longitude
- Address, address details, postal code
- City, market, state, country
- Built-out power (MW)
- Power ramp-up profiles
- Built-out whitespace
- Total building size
- Year online
- PUE
- Site code
- Tier design
- Ecosystem statistics
Need additional attributes? Share your requirements. Many fields can be added on request.
DC workload market sizing and MW forecast (Cloud, Video, AI)
Power is a strong proxy for how much compute is being deployed. This layer extends the DC Atlas with a workload-based MW forecast, so you can understand not only where data centres are, but what they are likely to be running, and how demand shifts over time across Cloud, Video, and AI.
What you receive
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Total data centre MW forecast by state, region, and key clusters
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Workload split (MW and % of total) for Cloud, Video, and AI
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Market sizing tables that show how each workload category grows over time
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Exportable outputs that can be delivered as simple columns and summary tables alongside the Atlas
Where it helps
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Size opportunity by market and cluster based on which workloads are driving demand
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Prioritise targets where AI load share is rising fastest, or where cloud and video are concentrating
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Support infrastructure planning by linking growth to realistic load composition, not just total MW
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Strengthen diligence and assumptions with consistent, comparable scenario outputs across regions
Australia geospatial intelligence add-on
See where capacity is, and what it means for energy, water, and planning.
We work with clients across APAC on an Australia-wide data centre database (270+ sites). This add-on extends that foundation with practical geospatial analysis at national and state level.
What we can deliver
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National Data Centre Atlas: zoning, energy infrastructure and Renewable Energy Zones, water sources and recycled schemes, plus flood, bushfire, and protected-area constraints.
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Energy demand scenarios: annual GWh and peak MW by site, state, region, and key clusters under business-as-usual, AI-aggressive, and efficiency-gains cases.
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Water implications by cooling pathway: site and regional estimates to highlight alignment with recycled water and risks in water-stressed catchments.
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Cross-sector “pressure map”: a simple regional index combining land, energy, and water pressures to identify strong and sensitive locations.
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State planning notes: concise briefs on AI-driven growth, infrastructure implications, and policy levers for better zoning, efficient cooling, and renewables co-location.
Power-to-bandwidth modelling (MW to Gbps)
Power is a strong proxy for compute density. This layer converts MW into estimated throughput in Gbps using transparent, configurable assumptions, so you can screen markets and prioritize targets faster.
How it works
- Start from built-out MW (apply PUE if you work with facility totals)
- Choose a scenario profile (conservative, baseline, high intensity)
- Receive estimated Gbps as exportable columns
Where it helps
- Rank sites by estimated connectivity demand
- Plan metro backhaul priorities
- Size opportunity by market and cluster
- Support diligence and assumption checks
Modeled bandwidth is an estimate for screening and prioritization, not a substitute for site specific engineering surveys.
Delivery formats
Choose the format that fits your workflow:
- CSV (Excel compatible)
- KML/KMZ (easy viewing and sharing in Google Earth)
- GeoJSON (web mapping and modern data stacks)
- SHP (Shapefile for GIS tools)
Request a sample
Tell us your geographies and preferred format. We will send a sample extract, the schema, and a short methodology note for the bandwidth modeling.
Send email to: landry@idemest.com
Data for market intelligence, sourcing, diligence, and network planning.
