Приклади вживання Data quality Англійська мовою та їх переклад на Українською
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Enforce Data Quality.
In particular, we use them to improve data quality.
Statistics: increase the data quality of the statistics functions.
Bosch uses them to improve data quality.
Ensured data quality and analysis of gaps in information security;
Люди також перекладають
Rigid and principled approach to data quality control;
Monitor and maintain data quality within those marketing databases.
Controls the observance of aerial surveillance techniques, data quality.
Monitor and maintain data quality of the marketing database.
Data quality should be integrated any place where data is entered, loaded, processed, or updated.
In particular, Bosch eBike can improve data quality as a result.
To ensure data quality, all researchers included in bibliometric studies should be able to check that their outputs have been correctly identified.
List-cross Statistics: increase the data quality of the statistics functions.
In terms of data quality, the researchers believe that their journalists were high-quality reporters, as evidenced by the consistency within journals and across journals.
Many ETL vendors now have data profiling, data quality, and metadata capabilities.
Using open standards and documented APIs one can integrate(mash up) different data sources, if the projection system,map scale and data quality match.
For ideas about how to measure data quality from respondents, see Schober et al.(2015).
The Austrian administrators, their local representatives, and the imperial statisticians continued to learn from each census,progressing their methods and the data quality over time.
A survey conducted by theBusiness Application Research Center stated the data quality management as the most important trend in 2020.
The range of data values or data quality in an operational system may exceed the expectations of designers at the time validation and transformation rules are specified.
However, eBird, and related projects,indicate that challenges related to sampling and data quality are concerns for distributed data collection projects.
EBird researchers have two main solutions to these data quality issues- solutions that might be helpful in other distributed data collection projects as well.
The design of PhotoCity also elegantly solves the sampling and data quality challenges of eBird and other distributed data collection projects.
Overall, the PhotoCity project shows that sampling and data quality are not insurmountable problems in distribution data collection.
Our customers are provided with daily prompt notifications about the data quality, change dynamics, and can monitor the complex indicator of data quality. .
The combination of UrtheDaily's resolution, revisit, and data quality opens the door to machine learning and AI opportunities never before seen in agriculture.