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Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1] Data is collected and analyzed to answer questions, test hypotheses, or disprove theories. [11] Statistician John Tukey, defined data analysis in 1961, as:
The difficulty in ensuring data quality is integrating and reconciling data across different systems, and then deciding what subsets of data to make available. [ 3 ] Previously, analytics was considered a type of after-the-fact method of forecasting consumer behavior by examining the number of units sold in the last quarter or the last year.
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.
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A business analyst should have knowledge in IT and/or business, but the combination of both of these fields is what makes a business analyst such a valuable asset to the business environment. As a minimum standard, a business analyst should have a "general understanding of how systems, products and tools work" in the business environment. [2]
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Business analysis is a professional discipline [1] focused on identifying business needs and determining solutions to business problems. [2] Solutions may include a software-systems development component, process improvements, or organizational changes, and may involve extensive analysis, strategic planning and policy development.
A scope statement should be written before the statement of work and it should capture, in very broad terms, the product of the project (e.g., "developing a software-based system to capture and track orders for software"). A scope statement should also include the list of users using the product, as well as the features in the resulting product.