Some organizations struggle with analysis due to a lack of talent. This is especially true in those without formal risk departments. Employees may not have the knowledge or capability to run in-depth data analysis. This challenge is mitigated in two ways: by addressing analytical competency in th...
Companies can also upskill, identifying employees with strong analytical or technical backgrounds who might be interested in transitioning to data roles and offering paid training programs, online courses, or data bootcamps to equip them with the necessary skills. ...
AB Baggeroer,WA Kuperman - 《Oceanic Engineering IEEE Journal of》 被引量: 982发表: 1993年 Channel Modeling and Threshold Signal Processing in Underwater Acoustics: An Analytical Overview An overview of underwater acoustic channel modeling and threshold signal processing is presented, which emphasizes ...
Journal of Interactive MarketingAnalytical challenges in customer acquisition - Hansotia, Wang - 1997 () Citation Context ...such as data processing, data maintenance, billing and collection, customer service; future ‘defection’ or ‘lapse’ rates (customers going elsewhere); future interest rates ...
when and how RC learns a general dynamical process are important mathematical questions whose answers are expected to provide guidelines for the practical design and implementation of RC systems. These lines of queries have led to a number of important analytical results which we classify into four ...
Ochratoxin A, fumonisins, and paralytic shellfish poisoning toxins are examples of naturally occurring toxins whereas sulfites, peanuts, and milk exemplify common allergenic food additives/ingredients. To deal with the increasing number of sample matrices and analytes of interest, two analytical ...
The resulting complex landscape of analytical methods has naturally fostered the growth of an omics benchmarking industry. Benchmarking refers to the process of objectively comparing and evaluating the performance of different computational or analytical techniques when processing and analysing large-scale ...
GenAI has the power to simplify data integration across ISVs and cloud platforms to create a powerful holistic view of activity. Integrating data in this way can radically change an organisation’s analytical capabilities. With a few prompts, generative AI can: ...
If an analytical procedure is not robust and its output is not reproducible or replicable, the public would call into questions the scientific rigor of the work and doubt the conclusion from a RWD-based study [113,114,115]. Result validation, reproducibility, and replicability can be challenging...
resulting research data managed by these infrastructures collected by individual researchers, groups, or projects are not only voluminous but also extremely heterogeneous, which reflects the multidisciplinarity as well as the large range of methods and technologies used in data acquisition and processing....