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Related Concept Videos

Data Reporting and Recording01:24

Data Reporting and Recording

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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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Data Collection I01:30

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Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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Data Collection II01:29

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The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and...
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Data Collection by Observations01:08

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Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
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Data Collection III01:05

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The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
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Data Collection by Experiments01:13

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Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
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Related Experiment Video

Updated: Mar 26, 2026

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Collaborative Data Analytics with DataHub.

Anant Bhardwaj1, David Karger1, Harihar Subramanyam1

  • 1MIT.

Proceedings of the VLDB Endowment. International Conference on Very Large Data Bases
|February 5, 2016
PubMed
Summary
This summary is machine-generated.

DataHub offers a unified platform for collaborative data analytics, enabling simultaneous data analysis, modification, and sharing across diverse tools and languages. It provides flexible data storage, an app ecosystem, and multi-language support for efficient data management and analysis.

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Area of Science:

  • Computer Science
  • Data Science

Background:

  • Existing data storage and analysis solutions lack robust support for collaborative data analytics.
  • Multiple individuals and teams often work simultaneously on datasets using heterogeneous tools and languages.

Purpose of the Study:

  • To introduce DataHub, a unified platform designed to overcome limitations in collaborative data analytics.
  • To demonstrate DataHub's capabilities in data storage, analysis, visualization, and sharing.

Main Methods:

  • DataHub provides flexible data storage with native versioning for concurrent updates and conflict inspection.
  • An integrated app ecosystem facilitates data ingestion, querying, and visualization.
  • Thrift-based data serialization enables multi-language data analysis (20+ languages) with DataHub as the central data store.

Main Results:

  • DataHub supports concurrent data modification and version browsing, allowing users to inspect conflicts.
  • Users can effortlessly ingest, query, and visualize data using DataHub's app ecosystem.
  • Data analysis in languages like R, Python, and Matlab is streamlined, with inputs and results managed within DataHub.

Conclusions:

  • DataHub enhances collaborative data analytics by providing a unified platform for data management and analysis.
  • The platform's flexible storage, app ecosystem, and multi-language support facilitate efficient and collaborative data workflows.