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  • 1
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (24 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Which companies have adopted technologies such as Hadoop and Spark, as well as data science in general? And which industries are lagging behind? This O’Reilly report provides the results of a unique, data-driven analysis of the market for big data products and technologies. Using eye-catching charts and visualizations, Spiderbook cofounder Aman Naimat highlights some surprising results from the analysis, such as: The relatively small number of companies using big data in production Industries that have embraced big data the most—and the least The amount of money spent on various big data use cases How many companies actually use “fast data” The results also reveal the geographical locations where companies have been quick to adopt big data, as well as the types of teams that use big data technology. In addition, Naimat takes you through the analysis process with Spiderbook’s graph-based machine-learning model. The company analyzed billions of publicly available documents, canvassed more than 500,000 companies, and searched the entire business internet to compile the most comprehensive results possible.
    Note: Online resource; Title from title page (viewed July 19, 2016)
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  • 2
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Internet of things ; Web site development industry ; Electronic books ; local
    Abstract: After years of speculation, the Internet of Things appears ready for genuine action in 2017. That's the conclusion of a unique data-driven analysis-conducted by Aman Naimat, SVP for Technology at Demandbase-that shows precisely which industries and companies are actively adopting IoT technologies. This report reveals the study's findings, including IoT use cases not anticipated by previous models and surveys. Naimat gathered live data across the entire business world, including websites, meetups, hiring patterns, business relationships, blogs, press, forums, and SEC filings, using data crawlers and proprietary natural-language parsing technology. The results show that IoT spending is currently focused on relatively simple use cases such as security, retail, and inventory, while more complex healthcare and traffic control initiatives remain in their infancy. This report reflects the most accurate snapshot of what IoT will look like in 2017. You'll learn about: Factors driving IoT growth, from platform support and availability of professional talent to real-time data/analytics support The top 50 companies in the IoT space, starting with Deloitte, Verizon, Amazon, Intel, and Microsoft IoT investment by industry, including capital spent on various use cases The size and location of companies involved in IoT adoption The methodology used in the data-driven analysis The author conducted similar surveys in 2016 on the adoption of big data and artificial intelligence technologies.
    Note: Description based on online resource; title from title page (viewed February 12, 2019)
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  • 3
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Computer industry ; Employees ; Salaries, etc ; Electronic books ; local
    Abstract: As with other technologies introduced in the past decade, artificial intelligence is the subject of many market predictions. But what exactly is current commercial adoption of AI beyond academic labs? In this ten-page report, Spiderbook cofounder Aman Naimat provides the results of a data-driven analysis into the U.S. industries and companies using or building AI products right now. Although some so-called AI applications aren't actually cognitive, there are technologies capable of achieving human- or superhuman-level intelligence on given tasks. Naimat and his team canvassed nearly 500,000 companies and used Spiderbook's graph-based machine-learning model to read the business Internet and classify businesses into different levels of AI maturity. With eye-catching charts and visualizations, this report presents findings that include: AI investment by industry, such as automotive, financial services, and telecommunications Companies within each industry actively investing in AI The top 20 companies investing in AI, including the usual suspects and relative unknowns AI use cases that receive budget resources The number of companies building AI applications and investing in AI as a strategic direction The number of companies investing in AI technology subcategories, such as deep learning and autonomous vehicles Physical locations of AI-oriented companies in the United States by state
    Note: Description based on online resource; title from title page (viewed February 12, 2019)
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