Explore the burgeoning Data Asset Map System market, projected for substantial growth driven by cloud adoption and intelligent analytics. Discover key trends, drivers, and leading companies shaping data governance and management.

Displays Anticipated Systems not mapped to a Published data asset. An Anticipated System can be described as a system expected to have at least one associated data asset. It excludes systems exclusively designated as Network, WAN, Web Server and has a Lifecycle Configuration Status as Canceled, Decommission, Deleted, Development, Discontinued, Disposal, or Renamed. This report can be used to help improve the Percentage of Data Assets to Anticipated Systems Mapped Score from Enterprise Data Management (EDM) Scorecard by identifying which anticipated system need to be mapped to a data asset.

Report of Data Asset Management Market is currently supplying a comprehensive analysis of many things which are liable for economy growth and factors which could play an important part in the increase of the marketplace in the prediction period. The record of Data Asset Management Industry is providing the thorough study on the grounds of market revenue discuss production and price happened. The report also provides the overview of the segmentation on the basis of area, contemplating the particulars of earnings and sales pertaining to marketplace.

An interactive dashboard that provides an inventory of open data assets and visually presents an overview of the various types of data assets classified as public that have been published to the City of Austin Open Data Portal (data.austintexas.gov) by departmental data owners. *City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj‐cccq

The information that is collected, used, disseminated, or maintained in the International Technology Services Admin Services system is used for user identification, authorization, and authentication purposes and can include the user’s name, organizational unit information, office telephone number, electronic mail address, and physical office address to adequately identify the individual for Help Desk support purposes.

All 311 Service Requests from 2010 to present. This information is automatically updated daily.

Click here to download data from 2011 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2011/fpz8-jqf4

Click here to download data from 2012 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2012/as38-8eb5

Click here to download data from 2013 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2013/hybb-af8n

Click here to download data from 2014 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2014/vtzg-7562

Click here to download data from 2015 - https://data.cityofnewyork.us/dataset/311-Service-Requests-From-2015/57g5-etyj

The approximate physical location of each individual Public Housing Building. If the building has more than one entrance or street address, the address of the entrance with the highest number of units and best possible geocode was chosen to represent the building location.

The Oklahoma Real Property Asset Report is published annually in compliance with the Oklahoma State Government Asset Reduction and Cost Savings Program found in Title 62 O.S. §908. The act requires the Office of Management and Enterprise Services (OMES) to compile and maintain a comprehensive inventory of all real property owned and leased by the state. All data contained in this report was self-reported by each state agency, board, commission, or public trust having the State of Oklahoma as a beneficiary.

This asset is a derived view based on the system dataset 'Site Analytics: Asset Inventory' which is automatically generated by the data management platform and provides a comprehensive inventory of all assets on this site. This asset has been filtered to present an overview of the various types of data that are classified as public and have been published on the City of Austin Open Data Portal (data.austintexas.gov) by departmental data owners.

The columns of the Asset Inventory dataset contain information about every asset. These include metadata fields (e.g., Name, Description, and Category), as well as statistics, such as the number of visits, row count, column count, and downloads. This asset is updated at least once per day to sync any changes, additional assets, or removed assets.

City of Austin Open Data Terms of Use – https://data.austintexas.gov/stories/s/ranj-cccq

North America Enterprise Asset Management Market size was valued at USD 3.96 Billion in 2023 and is projected to reach USD 7.78 Billion by 2031, growing at a CAGR of 8% from 2024 to 2031.

North America Enterprise Asset Management Market Dynamics

The key market dynamics that are shaping the North America Enterprise Asset Management market include:

Key Market Drivers

Industry Compliance Requirements: Stringent rules and compliance standards in industries like as manufacturing, utilities, and healthcare encourage the use of EAM solutions to assure safety, environmental, and operational compliance.

Aging Infrastructure: North America's aging infrastructure, particularly in sectors such as transportation and utilities, necessitates comprehensive asset management systems to optimize maintenance, extend asset lifespan, and reduce the risks associated with asset failures.

Emphasis on Asset Performance: Businesses are putting more focus on maximizing asset performance and uptime to deliver business results. EAM systems assist organizations in monitoring asset health, identifying maintenance requirements, and prioritizing resources to achieve maximum asset usage and reliability.

Integration with Business Systems: Integrating EAM systems with other business-critical systems like ERP (Enterprise Resource Planning) and CMMS (Computerized Maintenance Management Systems) allows for more seamless data exchange and decision-making, which improves overall organizational efficiency and effectiveness.

Key Challenges

Integration Complexity: Integrating EAM systems with existing enterprise resource planning (ERP) and other corporate systems can be difficult and time-consuming. Ensuring flawless compatibility across several software platforms is a big problem for firms using EAM systems.

Data Management and Accuracy: Maintaining correct and up-to-date asset data is critical for successful asset management. However, inconsistent data, insufficient records, and a lack of data standardization may hamper asset visibility and decision-making, resulting in operational inefficiencies.

Scalability and Flexibility: As firms expand and adapt, their asset management requirements may shift. EAM systems must be scalable and adaptable enough to handle changing business needs, new technologies, and regulatory changes without affecting operations.

Cybersecurity Risks: As assets become more connected and rely on digital technology, cybersecurity risks pose significant risks to EAM systems. Protecting sensitive asset data from cyberattacks, data breaches, and unauthorized access necessitates strong cybersecurity safeguards and proactive risk mitigation methods.

Key Trends

Focus on Predictive Maintenance: North American firms are increasingly implementing predictive maintenance methods powered by EAM systems. Organizations can use data analytics, machine learning, and predictive modeling to forecast equipment problems, schedule maintenance in advance, and reduce unexpected downtime.

Cloud-Based Solution Adoption: In North America, there is an increasing trend toward cloud-based EAM solutions, owing to the benefits of scalability, flexibility, and accessibility. Organizations are increasingly relying on cloud solutions to centralize asset data, automate maintenance operations, and provide remote access to EAM systems.

Integration with Enterprise Resource Planning (ERP) Systems: In North America, EAM and ERP systems are increasingly being integrated, allowing for seamless data exchange and workflow automation between asset management and other business functions such as finance, procurement, and inventory management.

Mobile Workforce Enablement: EAM solutions are increasingly being used to enable North America's mobile workforce. Mobile applications and devices allow field technicians to access asset information, update maintenance records, and receive work orders in real time, increasing productivity and efficiency.

🇺🇸 미국

This dataset represents the total number of Open Data Portal assets and the frequency of how often the asset is accessed. This data is collected by using Socrata Analytics. This dataset supports measure GTW.G.4 of SD23. Data Source: Socrata. Calculations: (GTW.G.4) Percentage of datasets published in the Open Data portal that are being accessed frequently (such as through a website views, API interactions, embeds or mobile views). Measure Time Period: Fiscal Year Annually Automated: No Date of Last description update: 4/1/2020 For questions please contact CTMCollaborationServices@austintexas.gov

Data Center Asset Management Market is expected to reach USD 9,924.99 Million by 2034, expanding at a CAGR of 15.2% from 2025 to 2034

The Oklahoma Real Property Asset Report is published annually in compliance with the Oklahoma State Government Asset Reduction and Cost Savings Program found in Title 62 O.S. §908. The act requires the Office of Management and Enterprise Services (OMES) to compile and maintain a comprehensive inventory of all real property owned and leased by the state. All data contained in this report was self-reported by each state agency, board, commission, or public trust having the State of Oklahoma as a beneficiary.

The Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) provides a new level of detail in global topographic data. Previously, the best available global DEM was GTOPO30 with a horizontal grid spacing of 30 arc-seconds. The GMTED2010 product suite contains seven new raster elevation products for each of the 30-, 15-, and 7.5-arc-second spatial resolutions and incorporates the current best available global elevation data. The new elevation products have been produced using the following aggregation methods: minimum elevation, maximum elevation, mean elevation, median elevation, standard deviation of elevation, systematic subsample, and breakline emphasis. Metadata have also been produced to identify the source and attributes of all the input elevation data used to derive the output products. Many of these products will be suitable for various regional continental-scale land cover mapping, extraction of drainage features for hydrologic modeling, and geometric and radiometric correction of medium and coarse resolution satellite image data. The global aggregated vertical accuracy of GMTED2010 can be summarized in terms of the resolution and RMSE of the products with respect to a global set of control points (estimated global accuracy of 6 m RMSE) provided by the National Geospatial-Intelligence Agency (NGA). At 30 arc-seconds, the GMTED2010 RMSE range is between 25 and 42 meters; at 15 arc-seconds, the RMSE range is between 29 and 32 meters; and at 7.5 arc-seconds, the RMSE range is between 26 and 30 meters. GMTED2010 is a major improvement in consistency and vertical accuracy over GTOPO30, which has a 66 m RMSE globally compared to the same NGA control points. In areas where new sources of higher resolution data were available, the GMTED2010 products are substantially better than the aggregated global statistics; however, large areas still exist, particularly above 60 degrees North latitude, that lack good elevation data. As new data become available, especially in areas that have poor coverage in the current model, it is hoped that new versions of GMTED2010 might be generated and thus gradually improve the global model.

This table is the primary table for information about work orders, and contains general information - including a description of the work, assigned title, request date and completion date - about each work order. Each row represents a single work order. The primary key field is EVT_CODE. The EVT_OBJECT field can be joined to the Assets table on OBJ_CODE to know which asset the work order was for.

For the User Guide, please follow this link For the Data Dictionary, please follow this link

The general location of an entire Public Housing Development. A distinct address is chosen to represent the general location of an entire Public Housing Development, which may be comprised of several buildings scattered across a community. The building with the largest number of units is selected to represent the location of the development.

This dataset provides information on Social Housing Asset Data at Salford City Council. Details are provided to meet the required standards of the Local Government Transparency Code 2014.

US Data Center Asset Management market size valued at USD 0.82 billion in 2025 and expected to reach USD 1.36 billion by 2034, growing at 5.8% CAGR from 2026-2034.

Inventory of public assets including asset level metadata.