The phrase "attention on data" is correct and usable in written English.
It can be used when discussing the focus or emphasis placed on data in a particular context, such as research, analysis, or decision-making.
Example: "In our meeting, we need to ensure that our attention on data drives our strategic decisions moving forward."
Alternatives: "focus on data" or "emphasis on data".
In this work we focus our attention on data sets of events involving rival gangs on a social network.
In this manuscript, we focus our attention on data with nuclear families.
For this paper, we focused our attention on data coded into the second theme about the transition from research practices into clinical care.
In addition, compared with LncRNA2Target, LncReg pays more attention on data obtained from laboratory methods that contain precise mechanisms and accurate information of regulatory relationships and contain more entries collected from laboratory methods (1081 vs. 396) that have been validated through various experimental methods, such as qRT-PCR, western blot, RNA-IP, ELISA, activity assay, etc.
The special attention of data transmission on railroad leads to significant problems in terms of performance simulation and measurement in particular environment.
If users put more attention on recent data, a heavier weight can be assigned to the recent data.
Because of the internal structure that exists inside the text documents CNN has been gaining attention on text data as well.
The company is using Earth Day to focus attention on its data center in Maiden, N.C., which is powered by a sun trap of solar panels that generate 167 million kilowatt-hours of renewable energy per year.
The consultant leads the conversation, not by focusing the team's attention on the data but on the conversation itself.
This modular approach allows chart abstractors to focus their attention on specific data elements (eg, dates of bone metastasis) and to collect these elements uniformly.
By focusing attention on thorough data analysis, design issues can be understood and their impact or bias can be estimated, on average, and then ideally accounted for in the interpretation of data.
