An Analysis of Engineering-as-Marketing Tools

Strategies for Expanding Business Reach

By Ian Greenleigh [source]

About this dataset

The engineering-as-marketing tools available today allow startups to maximize and take advantage of the engineering talents they possess. By creating useful tools such as calculators, widgets and microsites, businesses can get in front of potential customers and lead them to their products or services.

This dataset provides a comprehensive list of companies who are using engineering as a marketing strategy and the respective tools these companies have created for it. For each company you get information about their name, product/service, tool name, what the tool does and a URL for further information about it. Additionally there is an extra notes field providing more details about each company’s market habit or any other additional facts that could be relevant in understanding better the use cases these companies are leading with this new way of doing marketing through engineering driven strategies.

With this data you will be able to take a closer look at how effectively this strategy is working while being able to compare different approaches taken inside each industry vertical in order to maximize conversions among leads generated by all these amazing pieces work made possible by software engineers everywhere devoted every day making our lives easier constantly!

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How to use the dataset

Analyzing this data allows users to gain insights into how successful companies are using engineering-as-marketing techniques to generate leads and expand their customer base. It also provides a valuable resource for other organizations wanting to learn more about how other organizations have achieved success with such practices.

This dataset can be used in many ways such as:

• Analyzing different trends in which engineering-as-marketing techniques are being used across multiple industries
• Examining whether certain techniques lead to higher lead generation or increased customer base

• Comparing effectiveness between companies using different types of tools etc.

  To get started with this dataset, simply load it up into some kind of data analysis software package that supports csv file processing capabilities such as Tableau or R Studio. Then define each column appropriately by adding appropriate labels onto them so that they can be understood easily when looked at from a first glance perspective by yourself or other members on your team who are looking over your datasets before any analyses start happening on those files within your chosen data analysis software package . Now you should be all set up for analyzing this dataset!

Research Ideas

• Leveraging this data to understand the effectiveness of engineering-as-marketing for various companies.
• Creating a sentiment analysis of customers’ responses to engineering-as-marketing tools in order to determine which tools are most popular and successful.
• Analyzing what types of engineering-as-marketing tools have been most successful with specific customer segments, to inform future product development and marketing tactics

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: Engineering as Marketing.csv | Column name | Description | |:-------------------|:-------------------------------------------------------------------| | Company name | The name of the company. (String) | | What co does | A brief description of what the company does. (String) | | Tool name | The name of the engineering-as-marketing tool. (String) | | What tool does | A brief description of what the tool does. (String) | | URL | The URL of the engineering-as-marketing tool. (String) | | Notes | Additional notes about the engineering-as-marketing tool. (String) |

Acknowledgements

If you use this dataset in your research, please credit the ori...

Data science literacy is increasingly vital for undergraduate engineering and science students, yet questions remain about effective integration approaches across established curricula. This study presents a case study investigating the impact of integrating discipline-specific data science modules into existing undergraduate STEM courses at three different universities in the United States (US) through a multi-university research-practice partnership examining both student perspectives and instructor course assessments. Using mixed methods analysis of survey responses from 877 students and instructors' grades and interviews across six courses, we examined changes in students' perceptions of data science across various demographics, academic levels, and disciplines and compared student and instructor perspectives. Results show significant increases in students' self-reported motivation, skills, interest, and confidence after completing one or more modules, with initial perception being the strongest predictor of final perception after controlling for course and institution differences. Analysis revealed general alignment between student self-assessments and instructor evaluations. Students highlighted benefits including real-world applications and career relevance, while identifying challenges with data science tools and varying experience levels. These findings provide insights for engineering educators seeking to integrate data science into their curricula.

Question Paper Solutions of chapter Sensor Network Platforms and Tools of Adhoc - Sensor Network, 7th Semester , Computer Science and Engineering

Context:

This dataset showcases 113 leading Generative AI tools in 2025, covering venue for text, image, video, audio, and more. It provides details on companies, release years, open-source status, APIs, and methods. The data highlights the growth, diversity, and innovation of AI technologies shaping the digital future.

Feature Distribution:

tool_name → Name of the AI tool (e.g., ChatGPT, Claude).

company → Organization behind the tool.

category_canonical → Main category (LLMs, Image Gen, etc.).

modality_canonical → Primary modality (text, image, multimodal).

open_source → Whether the tool is open-source (1 = Yes, 0 = No).

api_available → Availability of API (1 = Yes, 0 = No).

api_status → API status (e.g., active, unavailable).

website / source_domain → Official website and domain.

release_year → Year of release.

years_since_release → How many years since launch.

modality_count → Total number of modalities supported by each tool.

A new doctoral training centre will teach scientists and engineers how to use advanced measurement tools—from spectroscopy to digital imaging—to study artworks, archaeological objects, and historic buildings. The centre addresses a persistent skills gap: heritage institutions hold vast collections of complex materials, but few researchers are trained to apply cutting-edge physical science to questions of origin, date, composition, and conservation. Without this pipeline, the UK risks losing its

Purpose: As increasing amounts and types of speech data become accessible, health care and technology industries increasingly demand quantitative insight into speech content.The potential for speech data to provide insight into cognitive, affective, and psychological health states and behavior crucially depends on the ability to integrate speech data into the scientific process. Current engineering methods for acquiring, analyzing, and modeling speech data present the opportunity to integrate speech data into the scientific process. Additionally, machine learning systems recognize patterns in data that can facilitate hypothesis generation, data analysis, and statistical modeling. The goals of the present article are (a) to review developments across these domains that have allowed real-time magnetic resonance imaging to shed light on aspects of atypical speech articulation; (b) in a parallel vein, to discuss how advancements in signal processing have allowed for an improved understanding of communication markers associated with autism spectrum disorder; and (c) to highlight the clinical significance and implications of the application of these technological advancements to each of these areas.Conclusion: The collaboration of engineers, speech scientists, and clinicians has resulted in (a) the development of biologically inspired technology that has been proven useful for both small- and large-scale analyses, (b) a deepened practical and theoretical understanding of both typical and impaired speech production, and (c) the establishment and enhancement of diagnostic and therapeutic tools, all having far-reaching, interdisciplinary significance.

NSF tools and resources-providing information about the impact of NSF's investments in science and engineering research and education-are available for viewing online and downloading. Topics include Fact Sheets, COVID-19 funding and Budget info.

Graph and download economic data for Producer Price Index by Commodity: Machinery and Equipment: Engineering and Scientific Instruments (WPS1185) from Jan 1990 to Jun 2026 about instruments, science, engineering, machinery, equipment, commodities, PPI, inflation, price index, indexes, price, and USA.

Service-learning (SL) helps engineering students to be involved in community activities and to be motivated by their studies. Although several reviews and research studies have been published about SL, it is not widespread in sciences and engineering at the university level. The purpose of this research is to analyze the different community services or projects where SL is implemented by engineering students and faculty and to identify the procedures that were usually implemented to assess SL-based courses and activities. Assessment could be considered as the evaluation of a specific module and the engineering competencies, the evaluation of the effectiveness of the SL program, the assessment of the participation of the student in those programs, and the assessment of whether students have achieved certain outcomes or gained specific skills. We conducted a systematic review with a search in three scientific databases: Scopus, Science Direct, and ERIC educational database to analyze the assessment methods and what that assessment covers. From 14,107 publications related to SL, 120 documents were analyzed to inform the conclusions of this study. We found that SL is widely used in several universities as experiential education, and it is considered an academic activity. The most widely used assessment technique is a survey to evaluate the engagement and attitudes of students and, to a lesser extent, teamwork presentations.

Materials science and engineering (MSE) research has, for the most part, escaped the doubts raised about the reliability of the scientific literature by recent large-scale replication studies in psychology and cancer biology. However, users on post-publication peer review sites have re- cently identified dozens of articles where the make and model of the scanning electron micro- scope (SEM) listed in the text of the paper does not match the instrument’s metadata visible in the images in the published article. In order to systematically investigate this potential risk to the MSE literature, we develop a semi-automated approach to scan published figures for this meta- data and check it against the SEM instrument identified in the text. Starting from an exhaustive set of 1,067,102 articles published since 2010 in 50 journals with impact factors ranging from 2 to 24, we identify 11,314 articles for which SEM make and model can be identified in an image’s metadata. For 21.2% of those articles, the image metadata does not match the SEM manufacturer or model listed in the text and, for another 24.7%, at least some of the instruments used in the study are not reported.

snapshot-tab-pane Science, Technology, Engineering, And Mathematics (STEM) Toys Market Size 2026-2030The science, technology, engineering, and mathematics (stem) toys market size is valued to increase by USD 7.32 billion, at a CAGR of 7.7% from 2025 to 2030. Heightened parental investment in early childhood cognitive development and career readiness will drive the science, technology, engineering, and mathematics (stem) toys market.Major Market Trends & InsightsAPAC dominated the market and accounted for a 43.2% growth during the forecast period.By Application - In-home segment was valued at USD 11.13 billion in 2024By Age Group - Between 9-10 years segment accounted for the largest market revenue share in 2024Market Size & ForecastMarket Opportunities: USD 10.24 billionMarket Future Opportunities: USD 7.32 billionCAGR from 2025 to 2030 : 7.7%Market SummaryThe science, technology, engineering, and mathematics (stem) toys market is expanding, driven by a growing emphasis on educational enrichment and the development of foundational skills from an early age. Parents and educators are increasingly seeking tools that foster problem-solving capabilities and prepare children for a technology-centric future.This has spurred innovation in programmable robotics and tangible coding sets, which transform abstract concepts into hands-on learning experiences. A key trend is the integration of adaptive learning algorithms into smart toys, personalizing the difficulty and content for individual users.For instance, a logistics company can use similar principles, leveraging AI-powered coding kits to train future talent in supply chain automation, optimizing routing algorithms through experiential learning. However, the market grapples with challenges such as the rapid obsolescence of technical content and the high costs associated with developing sophisticated products featuring augmented reality integration and sensor technologies.The need to balance educational rigor with engaging play continues to shape product development and market strategies, pushing for more interactive and effective learning tools.What will be the Size of the Science, Technology, Engineering, And Mathematics (STEM) Toys Market during the forecast period? Get Key Insights on Market Forecast (PDF) Get Free SampleHow is the Science, Technology, Engineering, And Mathematics (STEM) Toys Market Segmented?The science, technology, engineering, and mathematics (stem) toys industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2026-2030, as well as historical data from 2020-2024 for the following segments.ApplicationIn-homeIn-schoolAge groupBetween 9-10 yearsBetween 6-8 yearsBetween 11-13 yearsSubjectsScienceEngineeringMathematicsTechnologyGeographyAPACChinaJapanIndiaNorth AmericaUSCanadaMexicoEuropeGermanyUKFranceMiddle East and AfricaUAESaudi ArabiaSouth AfricaSouth AmericaBrazilArgentinaRest of World (ROW)By Application InsightsThe in-home segment is estimated to witness significant growth during the forecast period.The in-home segment is central to the global science, technology, engineering, and mathematics (stem) toys market, driven by parental focus on educational enrichment. Purchases are for domestic use, aimed at supplementing formal schooling and fostering foundational skills.Products are designed for self-guided discovery, with marketing emphasizing both entertainment and cognitive development. The growth of e-commerce platforms has made diverse products, including smart robotics and tangible coding sets, widely accessible, spurring innovation.In this segment, the use of modular systems has led to a 25% increase in sustained user engagement.The trend toward subscription models offering curated kits for project-based learning and hands-on learning continues to gain traction, providing a structured approach to cultivating technical literacy and scientific inquiry at home. Get Free SampleThe In-home segment was valued at USD 11.13 billion in 2024 and showed a gradual increase during the forecast period. Get Free SampleRegional AnalysisAPAC is estimated to contribute 43.2% to the growth of the global market during the forecast period.Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. See How Science, Technology, Engineering, And Mathematics (STEM) Toys Market Demand is Rising in APAC Get Free SampleRegional dynamics in the global science, technology, engineering, and mathematics (stem) toys market are shaped by distinct educational priorities and economic factors.In North America and Europe, high consumer awareness of long-term vocational goals drives demand for advanced robotics and scre

This dataset contains anonymized input parameters, aggregated simulation results, and supporting files used to validate an Industry 4.0-based framework for improving the operational availability of power tools in mining maintenance services. The simulation compares AS-IS and TO-BE scenarios using Monte Carlo simulation under operational uncertainty.

This dataset includes spreadsheets, figures, and supplementary materials related to the mentioned article, which is currently undergoing the submission and peer review process at a scientific journal.

This dataset provides a comprehensive listing of software tools developed or utilized by NASA across its various research centers. Each entry includes a unique case number, the associated NASA center, the date of software release or approval (SRA Date), the final software release agreement type (e.g., Open Source, General US, Academic Worldwide), and the official NASA Technology Transfer Report (NTR) title describing the software.

The dataset highlights the wide range of applications NASA supports through software—ranging from engineering analysis tools and machine learning components to visualization systems and simulation platforms. Whether distributed as open source or under more restrictive licenses, these tools represent decades of technological innovation, much of which has been made available for academic, commercial, and government use.

By exploring this dataset, researchers, developers, and educators can gain insight into the types of software NASA relies on, collaborates over, and shares with the broader community, reflecting its ongoing commitment to advancing science and technology through transparency and knowledge transfer.

This is the Inland Waters Thematic Data Product (TDP) V1 resulting from the _\(ESA FDR4ALT project\) https://www.fdr4alt.org/ and containing improved Water Surface Height (WSH) data record from the ERS-1, ERS-2 and Envisat missions estimated using the ICE1 retracking range for its better performance on the hydro targets. The FDR4ALT products are available in NetCDF format. Free standard tools for reading NetCDF data can be used. Information for expert altimetry users is also available in a dedicated NetCDF group within the products. Please consult the _\(FDR4ALT Product User Guide\) https://earth.esa.int/eogateway/documents/d/earth-online/fdr4alt-products-user-guide before using the data. The FDR4ALT datasets represent the new reference data for the ERS/Envisat altimetry missions, superseding any previous mission data. Users are strongly encouraged to make use of these datasets for optimal results.

Engineer Scale Ruler Market Outlook

According to our latest research, the global Engineer Scale Ruler market size reached USD 1.38 billion in 2024, demonstrating robust demand across professional and educational segments. The market is expected to exhibit a CAGR of 4.7% from 2025 to 2033, with the total market value projected to reach USD 2.08 billion by 2033. This steady growth is primarily attributed to increasing investments in infrastructure, advancements in engineering education, and the ongoing modernization of construction and design practices worldwide.

The growth of the Engineer Scale Ruler market is underpinned by the surging demand for precision measurement tools across diverse industries such as construction, engineering, and architecture. As global infrastructure projects continue to expand, the requirement for accurate and reliable measurement instruments becomes paramount, driving the adoption of engineer scale rulers. These rulers are integral for ensuring precision in technical drawings, blueprints, and on-site measurements, which is critical for minimizing errors and optimizing project outcomes. Furthermore, the integration of advanced materials and ergonomic designs has enhanced the durability and usability of these tools, broadening their appeal among professionals and students alike.

Another significant growth factor is the rising emphasis on STEM (Science, Technology, Engineering, and Mathematics) education, which has led to increased utilization of engineer scale rulers in academic institutions. Educational reforms in both developed and emerging economies are focusing on practical, hands-on learning experiences, thereby boosting the demand for high-quality measurement tools. Additionally, the proliferation of design and engineering courses at secondary and tertiary education levels has further accelerated market growth. Manufacturers are responding by introducing products tailored to the needs of students and educators, including lightweight, affordable, and easy-to-use models that facilitate effective learning.

Technological advancements and product innovation are also key drivers shaping the Engineer Scale Ruler market. The incorporation of features such as anti-slip grips, multi-scale markings, and digital enhancements has improved the functionality of these rulers, making them more versatile and user-friendly. Moreover, the growing trend of customization and branding, particularly for corporate and educational clients, has opened new avenues for market expansion. Companies are leveraging e-commerce and digital marketing strategies to reach a wider customer base, further boosting sales and market penetration.

In the realm of professional-grade measurement tools, the Ruler Aluminum Cork Back has emerged as a noteworthy innovation. This type of ruler combines the durability and precision of aluminum with the added stability of a cork backing, which prevents slipping during use. The cork back not only enhances grip but also protects delicate surfaces from scratches, making it an ideal choice for both professional and educational settings. As the demand for high-quality, reliable measurement tools continues to grow, the Ruler Aluminum Cork Back stands out for its blend of functionality and user-friendly design. Its introduction into the market has been met with positive reception, particularly among architects and engineers who value precision and ease of use in their tools.

From a regional perspective, Asia Pacific continues to dominate the Engineer Scale Ruler market, accounting for a significant share of global revenue in 2024. This dominance is driven by rapid urbanization, extensive infrastructure development, and a burgeoning education sector in countries such as China, India, and Japan. North America and Europe also represent substantial markets, supported by strong construction activity and a high level of technological adoption. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth, fueled by increasing investments in education and infrastructure, albeit from a lower base.

This dataset supports the study “Linking Power-Equipment Structures and Technical Terminology Through Scalable Vector Graphics: System Design and Controlled Evaluation in Electrical Engineering Education.” It contains de-identified pre-test and post-test achievement data from 140 second-year electrical engineering students, system-experience questionnaire data from 70 students who used the SVG-based learning system, a data dictionary, and reproducible analysis code. The achievement assessment comprised five dimensions: Chinese terminology recognition, English terminology production, Chinese–English matching, component/structure recognition, and engineering-context application. All participant identifiers have been removed or replaced with non-identifying study codes.

The computational science and engineering (CSE) community is in the midst of an extremely challenging period created by the confluence of disruptive changes in computing architectures, demand for greater scientific reproducibility, and new opportunities for greatly improved simulation capabilities, especially through coupling physics and scales. Computer architecture changes require new software design and implementation strategies, including significant refactoring of existing code. Reproducibility demands require more rigor across the entire software endeavor. Code coupling requires aggregate team interactions including integration of software processes and practices. These challenges demand large investments in scientific software development and improved practices. Focusing on improved developer productivity and software sustainability is both urgent and essential.This full day tutorial distills multi-project and multi-years’ experience from members of the IDEAS project, and creators of the BSSw.io community website. It provides information and hands-on experience with software practices, processes, and tools explicitly tailored for CSE. Goals are improving the productivity of those who develop CSE software and increasing the sustainability of software artifacts. We discuss practices that are relevant for projects of all sizes, with emphasis on small teams, and on aggregate teams composed of small teams.Outline* Objectives, Motivation, & Overview [45 min]* Requirements & Test-Driven Development [45 min]* Software Design & Testing [60 min]* Licensing [45 min]* Agile Methodologies & Useful Git Tools [60 min]* Git Workflows [30 min]* Code Coverage & Continuous Integration [40 min]* Software Refactoring & Documentation [35 min]

The Cloud Properties Level-3 gridded product is designed to facilitate continuity in cloud property statistics between the MODIS on the Aqua and Terra platforms and the common continuity products generated for the VIIRS (Visible Infrared Imaging Radiometer Suite) and the MODIS Aqua instruments. CLDPROP Level-3 statistical routines include scalar and histograms (1-D and 2-D) that are calculated identically to statistical datasets in the MODIS standard Level-3 product (MOD08 and MYD08 for MODIS Terra and Aqua, respectively). In addition, the same dataset names are used for all common datasets provided in both the continuity and standard Level-3 files.

This dataset provides the public data and code package for the CERT-FJSP computational-evidence reporting experiments. CERT-FJSP is a solver-agnostic reporting and traceability framework for already-generated flexible job shop scheduler outputs. The package supports artifact-level inspection and partial reproduction of the manuscript-supporting empirical summaries, including projection-ambiguity metrics, tuple-ablation information-retention outputs, reporting-baseline comparison, reference-policy sensitivity, global-versus-regime masking, and practical interpretive scenario summaries.

The archive contains selected Python scripts, supporting source modules, frozen public-facing output artifacts, expected-output documentation, schema and field glossary material, selection-protocol documentation for the 322 inspected tuple-bearing rows, and a 19-dimension retention-scoring rubric. It does not contain manuscript draft files, manuscript source files, cover-letter materials, response-to-reviewers files, or internal planning materials.

The package is intended for data/code transparency and reproducibility support. It is not a flexible job shop solver, not a benchmark suite, not a solver-selection tool, not a fallback-control package, not regulatory certification, and not independent evidence approval.