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Data wrangling, sometimes referred to as data munging, is the process of transforming and mapping data from one "raw" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics. The goal of data wrangling is to assure quality and useful data.
The purpose of this step is to measure the specification of problem/goal. This is a data collection step, the purpose of which is to establish process performance baselines. The performance metric baseline(s) from the Measure phase will be compared to the performance metric at the conclusion of the project to determine objectively whether ...
A screen fragment and a screen-scraping interface (blue box with red arrow) to customize data capture process. Although the use of physical "dumb terminal" IBM 3270s is slowly diminishing, as more and more mainframe applications acquire Web interfaces, some Web applications merely continue to use the technique of screen scraping to capture old screens and transfer the data to modern front-ends.
Project cycle management (PCM) is the process of planning, organizing, coordinating, and controlling a project effectively and efficiently throughout its phases, from planning through execution then completion and review to achieve pre-defined objectives or satisfying the project stakeholder by producing the right deliverable at the right time, cost and quality.
Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. The data can be collected from one or more sources and it can also be output to one or more destinations.
Web scraping is the process of using automated software, like bots, to extract structured data from websites.
The term process management usually refers to the management of engineering processes and project management processes where a process is a collection of related, structured tasks that produce a specific service or product to address a certain goal for a particular organization, actor or set of actors.
This process often, but not always, involves using A.I. itself to create a large dataset of synthetic data from a smaller set of real-world data, with the resulting synthetic data mirroring the ...
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