Data Analytics. Tower Software versions 2.4 or later may collect and transmit usability data (including information identifying the source of that data) to Red Hat. Red Hat intends to use the data to enhance future releases of the Tower Software and help streamline customer experience and success. Usability data includes information such as dashboard items clicked in the Tower Software, amount of time spent on individual pages and paths taken throughout the Tower Software. Usability data is collected and transmitted to Red Hat via a javascript file that is downloaded to a customer’s web-browser. The collection and transmission of such usability data is optional and you may (a) completely opt-out by editing the Tower Software configuration and restarting the Tower Software, or (b) choose between two opt-in scenarios: (i) “anonymous mode” that will provide usability data to Red Hat without any information identifying the source of that data, or
Data Analytics. Licensee is aware that as part of Licensor’s Program(s)improvement process Licensor may obtain feedback from the Program(s) regarding the hardware profile and operating system of Licensee’s users, internal errors that are arising with respect to the Program(s) and the regions of functionality of the Program(s) that Licensee is using.
Data Analytics. Appliance for improving network management by more effectively factoring in issues related to congestion, such as utilization, service consumption and routing. Provides real-time insights into network traffic to determine the value of different portions of that traffic.
Data Analytics. Customer is aware that as part of ANSYS’ Services and Applications improvement process ANSYS may obtain feedback from the Services and Applications regarding the hardware profile and operating system of Customer’s users, amount of time Services and/or Applications are used, file sizes created in connection with the Services, internal errors that are arising with respect to the Services and/or Applications and the regions of functionality of the Applications that Customer is using.
Data Analytics. 10.1. We may use the Customer Data, Usage Data and other data to run statistical reports within the Services for our own use; for example, showing which features are the most popular with Users, which features cause issues, for benchmarking in aggregate form and/or to gain insights. We may use Customer Data internally for product research, development and innovation; for example to improve the Services, add new features and functionality, such as receipt recognition and cashflow forecasting, and provide you with insights. You (as a business Customer) consent to and authorise our access to and use of the Customer Data for those purposes and agree that our use of the Customer Data is legitimate, proportionate and, in the case of support, network and information security, may be necessary, given the negligible impact on you and the benefit you and your Users will receive in terms of technical support and from product improvements and enhancements. For further information, including our legitimate interests for conducting analytics, please see our website privacy notice.
Data Analytics. Access to the Touchpoint Solution database for the Customer App which provides insight tools on number of Users entered for Giveaways, Experiences and commerce via the Operator’s Customer Resource Management (CRM) tool.
Data Analytics. The roadmap to a new digital architecture is well framed and accepted (Module Based Systems Engineering & Open System Architecture)
Data Analytics toolbox Data Analytics toolbox will be the final end-users service to be provided by PLATOON. PLATOON will develop a data analytics toolbox containing both generic big data tools and energy specific analytical tools for different applications. The toolbox has to provide the possibility to process data in batch and real time manner. PLATOON Data Analytics Toolbox should allow distributed implementation of the different parts of the data analytics tools at different levels of the architecture (i.e. at the edge and on cloud/premise) so that the developed tools make an efficient use of the available storage and processing capability. The PLATOON Data Analytics Toolbox should be compatible with the main widespread open-source and free to use big data batch and real time processing frameworks (e.g. Hadoop V2.0, Spark, Xxxxx, etc.) and storage solutions (RDBMS, HDFS, HBase, NoSQL databases. Cache, time series) so that it will be possible to use already existing and validated libraries (e.g. Spark MLib, Spark ML, etc.) without having to write all the code from scratch. Also, by using these open source solutions the project will benefit from a global software development community.
Data Analytics. 9.1. We may use the Relevant Data and other data to run statistical reports within the Services for our own use; for example, showing which features are the most popular with Users, which features cause issues, for benchmarking in aggregate form and/or to gain insights. We may use this to improve the Services, add new features and functionality, and provide you with insights. You consent to and authorise our access to and use of the Relevant Data for those purposes, and agree that our use of the Relevant Data is legitimate, necessary and proportionate given the negligible impact on you and the benefit you and your Users will receive from product improvements and enhancements. For further information, including our legitimate interests for conducting analytics, please see our privacy notice at xxx.xxxx.xxx.
Data Analytics. The Contractor will work with the State and its applicable Contractors to provide the network analysis data to be merged with other existing clinical and claims data sets, which includes preparation and provisions of a data file using the specifications agreed upon by the State. During and following the merger of the data, the Contractor will meet with the State and its data analytics contractors to determine best-practice methods for merging the data and subsequent data analysis techniques that will be applied to the merged data set. The work will include: Working with data analytics contractors of the State to link network data to other datasets Researching best practice methods for correlating network data with health outcomes measures Working with data analytics contractors to correlate data as prescribed by best practices Reporting Deliverables
