The statistic shows the number of internal and external data sources used for decision-making in organizations worldwide as of 2018. Around ** percent of respondents stated that their organization used less that **** external data sources in its decision-making process as of 2018.

In 2020, according to respondents surveyed, data masters typically leverage a variety of external data sources to enhance their insights. The most popular external data sources for data masters being publicly available competitor data, open data, and proprietary datasets from data aggregators, with **, **, and ** percent, respectively.

Dataset

This dataset was created by Tarik Karakas

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Dataset

This dataset was created by README

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Dataset content available to registered users only

SP ENW - External Data - National Parks

An extract from Natural England's 'National Parks' dataset, identifying those National Park polygons which are shown to intersect with the SP ENW Control Boundary.

While we use reasonable endeavours to ensure that the data contained within this dataset is accurate, we do not accept any responsibility or liability for the accuracy or the completeness of the content held, or for any loss which may arise from reliance on this dataset and/or its related information.

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Guided by common values, Covid Act Now is a multidisciplinary team of technologists, epidemiologists, health experts, and public policy leaders working to provide disease intelligence and data analysis on COVID in the U.S.

APIs, Visualizations and csv files of data are available for public use.

Dataset

This dataset was created by Alex Shonenkov

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Soil Structural Degradation (Vulnerability).Sourced from the Manaaki Whenua Landcare Research via the LRISPortal.To download or access this layer, please go to the source : LRISPortal

Nigeria NG: External Health Expenditure Per Capita: Current PPP data was reported at 0.000 Intl $ mn in 2015. This records a decrease from the previous number of 0.000 Intl $ mn for 2014. Nigeria NG: External Health Expenditure Per Capita: Current PPP data is updated yearly, averaging 0.000 Intl $ mn from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 0.000 Intl $ mn in 2014 and a record low of 0.000 Intl $ mn in 2002. Nigeria NG: External Health Expenditure Per Capita: Current PPP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Health Statistics. Current external expenditures on health per capita expressed in international dollars at purchasing power parity (PPP). External sources are composed of direct foreign transfers and foreign transfers distributed by government encompassing all financial inflows into the national health system from outside the country.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted average;

Validation data for the Astro scientific publication clustering benchmark dataset

This is the dataset used in the publication Donner, P. "Validation of the Astro dataset clustering solutions with external data", Scientometrics, DOI 10.1007/s11192-020-03780-3

Certain data included herein are derived from Clarivate Web of Science. © Copyright Clarivate 2020. All rights reserved.

Published with permission from Clarivate.

The original Astro dataset is not contained in this data. It can be obtained from http://topic-challenge.info/ and requires permission from Clarivate Analytics for use.

This dataset collection consists of four files. Each file contains an independent dataset that relates to the Astro dataset via Web of Science (WoS) record identifiers. These identifiers are called UTs. All files are tabular data in CSV format. In each, at least one column contains UT data. This should be used to link to the Astro dataset or other WoS data. The datasets are discussed in detail in the journal publication.

Dataset content available to registered users only

SP ENW - External Data - Flood Risk

Extract of the Environment Agency's 'Flood Risk Areas' dataset, identifying those flood Risk polygons which are shown to intersect with the SP ENW Control Boundary.

While we use reasonable endeavours to ensure that the data contained within this dataset is accurate, we do not accept any responsibility or liability for the accuracy or the completeness of the content held, or for any loss which may arise from reliance on this dataset and/or its related information.

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Mithilss/nasdaq-external-data-processed dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset

This dataset was created by huytrần

Contents

To assess use of external evidence for overall survival (OS) estimation in oncology single-technology appraisals (STAs) by the National Institute for Health and Care Excellence (NICE). STAs for oncology drugs appraised by NICE between January 2021 and March 2023 were identified. For each eligible STA, OS extrapolation methods used, the rationale for using external data, the source and type of data, and information on acceptance by the evidence review group (ERG) and the appraisal committee were extracted. Initially, 215 STAs were identified, of which 82 were eligible for the study. Of these, 32 STAs used external data for OS extrapolation, including trial data (44%), real-world data (47%), clinical opinion (25%), meta-analysis (1%) and previous STA (1%). External data were used more frequently in state-transition models for post-event transitions and cure assumptions, and in partitioned-survival models to replace pivotal trial OS, inform long-term survival estimates or to estimate OS based on surrogacy analysis. Sensitivity analyses on use of external data was explored in 16 (50%) of the STAs. The committee accepted use of external data in half of the analysed STAs, acknowledging uncertainty in OS extrapolation. The analysis was limited to the STAs published between 2021 and 2023 and publicly available materials on the NICE website. This study provides an overview of external data used to estimate OS in oncology STAs conducted by NICE in recent years. External data, including trial data, real-world data and clinical opinions, were incorporated into recent oncology STAs at various modelling stages. ERGs and appraisal committees were generally accepting of the use of external data. However, it is crucial to conduct a sensitivity analysis and provide a justification for the methods and data source selection.

Land Use Capability, includes a measure for 'Slope'.Sourced from the Manaaki Whenua Landcare Research via the LRISPortal.To download or access this layer, please go to the source : LRISPortal

Mithilss/nasdaq-external-data-2018-onwards-dedup dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset

This dataset was created by Chien-Hsiang Hung

Contents

Dataset content available to registered users only

SP ENW - External Data - Sites of Special Scientific Interest (SSSI)

An extract from Natural England's 'Sites of Special Scientific Interest' dataset, identifying those SSSI polygons which are shown to intersect with the SP ENW Control Boundary.

While we use reasonable endeavours to ensure that the data contained within this dataset is accurate, we do not accept any responsibility or liability for the accuracy or the completeness of the content held, or for any loss which may arise from reliance on this dataset and/or its related information.

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SP ENW - External Data - Lower Level Super Output Areas (LSOA) Data

The Office of National Statistics (ONS) make available the Lower layer Super Output Areas (LSOA) dataset. The individual areas are described as comprising between 400 and 1,200 households and have a usually resident population between 1,000 and 3,000 persons.

This dataset contains the LSOA Polygons (sourced from ONS) which have been cropped to only reflect the polygons - or sections thereof, which fall within the Electricity North West Control BoundaryAdditional Columns have been added, detailing the KM2 area of each LSOA polygon, alongside the area of the same polygon which falls within the SP ENW boundary (also shown as a percentage value)

While we use reasonable endeavours to ensure that the data contained within this dataset is accurate, we do not accept any responsibility or liability for the accuracy or the completeness of the content held, or for any loss which may arise from reliance on this dataset and/or its related information.

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