Buyer’s Guide: Industrial Data Management Solutions (2024)
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Executive Summary
This report provides decision-makers at industrial facilities who are responsible for the selection, implementation and management of software for industrial data management with an up-to-date analysis of 18 prominent industrial data management vendors, as well as a broader overview of 29 industrial data management solution providers on the market. The report leverages questionnaires completed by 18 industrial data management solutions providers over the last four months, vendor software demonstrations, and analysis of emerging tools such as vector databases, knowledge graphs and generative AI. To supplement this, Verdantix has built a picture of the industrial data management market and buyer requirements using a range of publicly available data, as well as insights generated from our annual global survey of 304 executives in operations, maintenance, engineering and process safety roles. Prospective buyers should use this report to support them in their search for industrial data management software applications that support well-informed industrial operations and the acceleration of AI initiatives.
Table of contents
Industrial data management solutions Buyer’s Guide 2024Industrial data management software offers buyers a platform on which to action their analytics and AI strategies
Industrial data management vendors utilize sophisticated data models to deliver relevant information efficiently
Buyers should assess their digital maturity and analytics needs before selecting industrial data management software
Inclusion criteria for the 2024 industrial data management solutions Buyer’s Guide
AspenTech combines process modelling expertise with industrial DataOps
AVEVA provides deep asset management capabilities in combination with time series heritage
Braincube offers data digital twin and low code solutions for complex manufacturing processes
C3 AI provides an ecosystem of DataOps-enabled AI for a wide variety of industries
Cognite orchestrates industrial data with knowledge graphs and GenAI
Databricks’s platform provides comprehensive DataOps tools to engineers
GE Vernova has built a strong data management foundation for its APM solution
HighByte’s edge-native DataOps solution delivers ready-to-use industrial data to consuming applications at enterprise scale
Hitachi Vantara delivers strong DataOps capabilities to a broad range of industrial firms
Honeywell provides flexible and scalable data collection with self-service analytics
IBM offers a comprehensive and industry-agnostic data management platform
MachineMetrics delivers automated and actionable insights, driving enhanced decision-making at the machine, plant and enterprise level for discrete manufacturers
Palantir’s government intelligence track record offers multinational industrial firms planet-scale DataOps
Rockwell Automation offers manufacturing firms a data management platform built through acquisitions and partnerships
Seeq transforms time series data into insights for industrial enterprises
SymphonyAI Industrial provides a strong analytics track record in combination with knowledge graphs and AI
TrendMiner provides a robust industrial data management platform for fast and actionable insights to process firms
Viewport.ai delivers a richly integrated DataOps solution for technical documentation management and discovery
Table of figures
Figure 1. The modern industrial data management stackFigure 2. Comparison of industrial data modelling strategies
Figure 3. Comparison of industrial data types and associated modelling strategies
Figure 4. Products and top industries for industrial data management solutions providers
Figure 5. Regional presence of industrial data management solutions providers
Figure 6. AspenTech industrial data management solutions overview
Figure 7. AVEVA industrial data management solutions overview
Figure 8. Braincube industrial data management solutions overview
Figure 9. C3 AI industrial data management solutions overview
Figure 10. Cognite industrial data management solutions overview
Figure 11. Databricks industrial data management solutions overview
Figure 12. GE Vernova industrial data management solutions overview
Figure 13. HighByte industrial data management solutions overview
Figure 14. Hitachi Vantara industrial data management solutions overview
Figure 15. Honeywell industrial data management solutions overview
Figure 16. IBM industrial data management solutions overview
Figure 17. MachineMetrics industrial data management solutions overview
Figure 18. Palantir industrial data management solutions overview
Figure 19. Rockwell Automation industrial data management solutions overview
Figure 20. Seeq industrial data management solutions overview
Figure 21. SymphonyAI Industrial industrial data management solutions overview
Figure 22. TrendMiner industrial data management solutions overview
Figure 23. Viewport.ai industrial data management solutions overview
Organisations mentioned
3M, ABB, Accel, Accenture, Accruent, Air Products, Airbus, Aker ASA, Aker Solutions, AkerBP, Alcon, Altair, Amazon Web Services (AWS), Anglo American, Apache Spark, APERIO, Arcion, AspenTech, Assai, AssetWorks, AstraZeneca, ATS Euromaster, Avalign Technologies, Avanade, AVATA, AVEVA, Baker Hughes, Bangkok Industrial Gas, BASF, Bayer, Bell Canada, Bengalla, BHP, Boston Consulting Group, BP, Bpifrance, Braincube, C3 AI, Canvass Analytics, Capgemini, Cargill, Celanese Corporation, Centrica, Chevron Corporation, Cogent DataHub, Cognite, Cognizant, Con Edison, COSMO ENERGY HOLDINGS, Covestro, Dassault Systèmes, Databricks, DataProphet, DataSentics, Deloitte, Dianomic, Element Analytics, Emerson, ENGIE, EOT, Equinox Software and Services, eschbach, Espoon Vesi, EY, Factry, FANUC, FAST Technologies, Ferrari, Fiix, Fivetran, Fluke, Full Sail Brewing, GE Vernova, General Electric, Georgia-Pacific, Google, Grafana, Greenbird, Haas Automation, HCLTech, Heidenhain, Helin, Hexagon, HighByte, Hitachi Solutions, Hitachi Vantara, HiveMQ, Honeywell, HP, Hurco, IBM, IFP Energies Nouvelles, IFS Ultimo, InfluxData, inmation, Intel, International Organization for Standardization (ISO), Jupyter, KBR, Kellogg's, Keras, Kinder Morgan, King's Hawaiian, Klipfolio, Kobai, Koch Industries, Lanxess, Lincoln Electric, Litmus Automation, Lityx, LTIMindtree, Lufthansa, MachineMetrics, MACS, MaestroHub, McKinsey & Company, Mercedes-Benz, Meta, Michelin, Microsoft, Mitsubishi, MongoBD, MQTT, MTConnect, NASDAQ, Neo4j, Nukon, Nutrien, OData, OPC Foundation, Open AI Energy Initiative, Open Design Alliance, Open Text Corporation, OpenAI, Oracle, OSDU, OSIsoft, Palantir, Paragon Medical, Petronas, Pfizer, Pinnacle, Plex, Plotly, PowerRunner, PrestoDB, PTC, PwC, QbD Group, Qlik, Radial Software Group, Radix, Raytheon Systems, Regal Rexnord, Roche, Rockwell Automation, Royal IHC, RWE, Saint-Gobain, Salesforce, SAP, Sappi, Saudi Aramco, SCADAfence, Schneider Electric, Scottish Equity Partners, Seagate, SECO, Seeq, Sensia, Shell, Siemens, SIG, Sight Machine, Sitech, SKF, Skkynet, SLB, Snowflake, Software AG, Suncor, SymphonyAI Industrial, Tableau, Tampa Electric, Tata Consultancy Services, TCV, Tech Mahindra, TensorFlow, Tiama, Timeseer.ai, TotalEnergies, Trendence, Trendminer, Tulip, TwinThread, UK National Health Service (NHS), Umicore, Uptake, US Air Force, US Department of Defense, US Federal Risk and Authorization Management Program (FedRAMP), US National Nuclear Security Administration, Vertix Technologies, Verve Industrial Protection, Viewport.ai, Visionaize, WBL, werusys, Wild Turkey, Wipro, Wood, Yokogawa, YuzeDataAbout the authors
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