Skip to main content

Big Data: Datalogic predicts growth in advanced data collection

Datalogic, a global leader in automatic data capture and industrial automation markets, expects a surge in next generation advanced data collection devices, which will intelligently edit and communicate data and play a critical role in providing improved business analytics, termed ‘big data’. This vision for future market growth was delivered by Bill Parnell, President and CEO of Datalogic ADC, the division focused on the global automatic data capture market, speaking during ID World Rio de Janeiro, the
December 6, 2013 Read time: 2 mins
7546 Datalogic, a global leader in automatic data capture and industrial automation markets, expects a surge in next generation advanced data collection devices, which will intelligently edit and communicate data and play a critical role in providing improved business analytics, termed ‘big data’.
 
This vision for future market growth was delivered by Bill Parnell, President and CEO of Datalogic ADC, the division focused on the global automatic data capture market, speaking during ID World Rio de Janeiro, the third Americas summit on traceability, mobility and security.
 
“The objective in analyzing extremely large and diverse types of data is to uncover correlations and patterns, aiding fast decisions and improved business results. Business analytics focuses on why events are happening, what will happen next, and how to optimise the enterprise’s future actions,” said Parnell.
 
In terms of big data, the data volumes are huge.  Parnell stressed the need for new data collection solutions to intelligently collect the large volume and variety of data in these complex transactional environments.
 
The future of automatic data collection is going far beyond simply scanning barcodes. For instance, advanced high performance imaging technology reads barcodes but also provides images that are the basis for item recognition systems using visual pattern recognition software. He also stated that benefits from business analytics are being seen in many other industries such as government, healthcare, and logistics while also serving as a catalyst to the development of more complex and higher performing data collection systems.
 
The end goal is to manage ‘big data’ for better business and improved customer satisfaction. Next generation advanced data collection devices, such as those from Datalogic, are crucial in providing the fuel for these analytical decision-support systems.

For more information on companies in this article

Related Content

  • SPONSORED CONTENT: Using AI to achieve real traffic intelligence
    June 3, 2020
    The application of artificial intelligence has the potential to transform the performance of vision-based systems used for a wide and growing set of applications. These include vehicle presence detection and identification, count and classification, and enforcement, explains Roy Czinku of International Road Dynamics
  • ITS Australia Awards: finalists revealed
    November 29, 2022
    Cisco, Moovit and Q-Free are among the companies up for 13th ITS Australia Annual Awards
  • Fully autonomous vehicles ‘spur LiDAR sensors mass adoption’
    January 26, 2017
    Cost-effective, high-resolution light detection and ranging (LiDAR) sensors capable of long-range object detection will be necessary for high to fully-automated driving applications. Demand for 3D mapping and imaging, better overall performance, automated processing of graphic data gathering and self-sufficient sensor with best-in-class performance in low-visibility conditions are factors driving the development and adoption of LiDAR sensors within the advanced driver assistance systems (ADAS) sensor suite
  • SensTraffic stars for Sensys in San Jose
    June 13, 2016
    Today at ITS America 2016 San Jose is highlighting Sensys Networks announces SensTraffic, a traffic data and analytical Smart City software platform for managing corridors and intersections. According to the company, this new service improves upon the highly manual and inefficient methods to collect traffic data and incorporate it into actionable insights. Traffic engineers can generate a wide variety of detailed reports including congestion mapping, travel times, origin/destination, high-resolution perform