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[citation needed] However, there is no harmonized terminology in different languages, including in French and Spanish. Patent analytics encompasses the analysis of patent data, analysis of the scientific literature, data cleaning, text mining, machine learning, geographic mapping, and data visualisation. [1]
Data cleaning is the process of preventing and correcting these errors. Common tasks include record matching, identifying inaccuracy of data, overall quality of existing data, deduplication, and column segmentation. [23] Such data problems can also be identified through a variety of analytical techniques.
Data analysis focuses on the process of examining past data through business understanding, data understanding, data preparation, modeling and evaluation, and deployment. [8] It is a subset of data analytics, which takes multiple data analysis processes to focus on why an event happened and what may happen in the future based on the previous data.
For example, a data analyst might analyze sales data to identify trends in customer behavior and make recommendations for marketing strategies. [ 37 ] Data science, on the other hand, is a more complex and iterative process that involves working with larger, more complex datasets that often require advanced computational and statistical methods ...
Its core platforms, Gotham and Foundry, integrate data sets and machine learning models into an ontology, a framework that connects digital information to real-world objects. Users can query the ...
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." [3]
Social data scientists use both digitized data [22] (e.g. old books that have been digitized) and natively digital data (e.g. social media posts). [23] Since such data often take the form of found data that were originally produced for other purposes (commercial, governance, etc.) than research, data scraping, cleaning and other forms of preprocessing and data mining occupy a substantial part ...
Applied in varying degrees of detail, open coding can be linked to a line, sentence, paragraph or complete text (e.g., protocol, scenario). Alternatives are selected according to the research question, relevant data, personal style of the analyst and the stage of research.