Data collection

Data collection?or?data gathering?is the process of gathering and?measuring ?information ?on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes.?Data ?collection is a?research ?component in all study fields, including?physical ?and?social sciences ,?humanities ,[2] ?and?business . While methods vary by discipline, the emphasis on ensuring accurate and honest collection remains the same. The goal for all data collection is to capture quality evidence that allows analysis to lead to the formulation of convincing and credible answers to the questions that have been posed. Data collection and validation consists of four steps when it involves taking a census and seven steps when it involves sampling.[3]

Regardless of the field of or preference for defining data (quantitative ?or?qualitative ), accurate data collection is essential to maintain research integrity. The selection of appropriate data collection instruments (existing, modified, or newly developed) and delineated instructions for their correct use reduce the likelihood of?errors .

A formal data collection process is necessary as it ensures that the data gathered are both defined and accurate. This way, subsequent decisions based on arguments embodied in the findings are made using valid data.[4] ?The process provides both a baseline from which to measure and in certain cases an indication of what to improve.

Data management platform

Main article:?Data management platform

Data management platform ?(DMP) is a centralized storage and analytical system for data. Mainly used by marketers, DMPs exist to compile and transform large amounts of data into discernible information. Marketers may want to receive and utilize first, second and third-party data. DMPs enable this, because they are the aggregate system of?DSPs ?(demand side platform) and?SSPs ?(supply side platform). When it comes to advertising, DMPs are integral for optimizing and guiding marketers in future campaigns. This system and their effectiveness is proof that categorized, analyzed, and compiled data is far more useful than raw data.