Industrial Real Estate Insights

Industrial Real Estate Insights
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At Nomad Data we help you find the right dataset to address these types of needs and more. Sign up today and describe your business use case and you'll be connected with data vendors from our nearly 3000 partners who can address your exact need.


Understanding the dynamics of the industrial real estate market in the USA, encompassing self-storage, warehouses, data centers, and flex R&D spaces, has historically been a complex task. Before the digital age, insights into this sector were primarily derived from anecdotal evidence, manual surveys, and limited public records. These methods were not only time-consuming but often resulted in outdated or incomplete data by the time analyses were completed. The reliance on such antiquated methods meant that businesses and investors were frequently making decisions in the dark, with a significant lag in understanding market changes.

The advent of sensors, the internet, and connected devices, alongside the proliferation of software and databases, has revolutionized data collection and analysis. This technological evolution has made it possible to gather and analyze vast amounts of data in real-time, providing immediate insights into the industrial real estate market. The importance of data in understanding market dynamics cannot be overstated. It has transformed the way professionals approach market analysis, investment decisions, and strategic planning.

Today, various types of data are available to those interested in the industrial real estate sector. From sales comps and leases to purchases and loans, the depth and breadth of data accessible have never been greater. This article will explore how specific categories of datasets can be leveraged to gain better insights into the industrial real estate market in the USA, highlighting the roles and industries that have historically used this data and the technology advances that have facilitated its collection and analysis.

Technology Data in Industrial Real Estate

The role of technology data, particularly concerning data centers, has become increasingly significant in the industrial real estate market. This category of data covers market capacity information, facility capacity, and trends, providing invaluable insights for investors, developers, and operators. The emergence of cloud computing and the exponential growth of data consumption have propelled the demand for data centers, making technology data a critical component in understanding market dynamics.

Historically, the availability of detailed information on data centers was limited. Advances in data collection and analytics have now made it possible to track market trends, capacity expansions, and investment opportunities in real-time. This acceleration in data availability has opened new avenues for strategic planning and investment in the industrial real estate sector.

Examples of Technology Data Usage:

  • Market Capacity Analysis: Understanding the current and future capacity of data centers in specific markets.
  • Investment Opportunities: Identifying underserved markets or facilities ripe for expansion or acquisition.
  • Trend Analysis: Tracking the evolution of data center demand and technology adoption.

Real Estate Data in Industrial Markets

Real estate data providers offer comprehensive datasets that include sales comps, leases, purchases, loans, and even parcel data. This information is crucial for a wide range of professionals within the industrial real estate sector, including investors, developers, and market researchers. The ability to access live market trends, demographics, and detailed property information has transformed the landscape of market analysis and decision-making.

The evolution of real estate data has been driven by advances in data collection, storage, and analytics technologies. The integration of geographic information systems (GIS), artificial intelligence (AI), and machine learning (ML) has enabled the analysis of complex datasets, providing deeper insights into market trends, property valuations, and investment risks.

Examples of Real Estate Data Usage:

  • Market Analysis: Comprehensive analysis of market trends, demographics, and property valuations.
  • Risk Assessment: Evaluating investment risks based on detailed property and market data.
  • Strategic Planning: Informing development and investment strategies with granular data on market demand and supply.


The importance of data in understanding and making informed decisions in the industrial real estate market cannot be overstated. The availability of technology and real estate data has revolutionized the way professionals approach market analysis, investment, and strategic planning. As the volume and variety of data continue to grow, the ability to analyze and leverage this information will be a key differentiator for businesses and investors.

Organizations that embrace a data-driven approach will be better positioned to identify opportunities, mitigate risks, and achieve competitive advantages in the dynamic industrial real estate market. The future of industrial real estate analysis and decision-making will increasingly rely on the discovery and monetization of new data types, further enhancing the depth and accuracy of market insights.


Industries and roles that benefit from industrial real estate data include investors, consultants, insurance companies, and market researchers. The transformation brought about by data has enabled these professionals to make more informed decisions, reduce risks, and identify new opportunities. The future of the industrial real estate sector will likely see further advancements in AI and ML, unlocking the value hidden in decades-old documents and modernizing the analysis of government filings and market trends.

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