Sentence examples for data practitioners from inspiring English sources
The phrase "data practitioners" is correct and usable in written English
It can be used to refer to individuals who work with data in various capacities, such as data analysis, data science, or data management. Example: "Data practitioners play a crucial role in interpreting complex datasets to drive business decisions."
Crowdsourcing platforms are usually publicly available and are widely used by big crisis data practitioners.
Looking more broadly, business analysts — a growing base of big data practitioners — avoid both of these frameworks, which are low-level toolkits meant for programmers.
"As companies look to their data to deliver value – data practitioners are finding that configuring and managing their own data infrastructure is a time-consuming job that is expensive and fraught with errors," said Murthy.
Late in 2017 HESA organized the Data Matters conference to disseminate Data Futures updates to HE data practitioners, and as a forum for presentations and discussion around issues of big data, learning analytics, personalization services, data visualization, as well as data protection, privacy and data quality assurance (Guy, 2017).
[Planner, North West] Besides using formally-collected quantitative data, practitioners drew on personal local knowledge.
If a choice is made to fit a beta regression model to observed data practitioners must strive to ensure correct specification of both the mean and dispersion sub-models in order to generate proper inferences.
As a long-time big data practitioner, an early advocate for investment in Hadoop by Yahoo! and now CEO of a company that provides big data as a service for the enterprise, I'd like to bring some perspective and clarity to this conversation.
Yet, using these efficacy data, many practitioners changed their practice and started using oral dexamethasone in the management of bronchiolitis.
Issues faced by data warehouse practitioners are explained, including topics such as big data, changing business requirements, performance issues, complexity, auditability, restart checkpoints, and fluctuation of team members.
Hence, the generator for X can be given by the algorithm: The ℳ O E W distributions can be very useful in modeling lifetime data and practitioners may be interested in fitting one of these models.
Our data suggests practitioners should try to manage a landscape containing both young and mature pine stands and use prescribed fire to create understory conditions selected by turkeys across all reproductive phases.
