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  2. Data preparation - Wikipedia

    en.wikipedia.org/wiki/Data_preparation

    Data preparation is the first step in data analytics projects and can include many discrete tasks such as loading data or data ingestion, data fusion, data cleaning, data augmentation, and data delivery. [2] The issues to be dealt with fall into two main categories:

  3. Data preprocessing - Wikipedia

    en.wikipedia.org/wiki/Data_Preprocessing

    The data-frame is then used to manipulate data that can be challenging otherwise to do in Excel. Pandas (software) which is a powerful tool that allows for data analysis and manipulation; which makes data visualizations, statistical operations and much more, a lot easier.

  4. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  5. Data wrangling - Wikipedia

    en.wikipedia.org/wiki/Data_wrangling

    Depending on the amount and format of the incoming data, data wrangling has traditionally been performed manually (e.g. via spreadsheets such as Excel), tools like KNIME or via scripts in languages such as Python or SQL. R, a language often used in data mining and statistical data analysis, is now also sometimes used for data wrangling. [6]

  6. Power Query - Wikipedia

    en.wikipedia.org/wiki/Power_Query

    Power Query is built on what was then [when?] a new query language called M.It is a mashup language (hence the letter M) designed to create queries that mix together data. It is similar to the F Sharp programming language, and according to Microsoft it is a "mostly pure, higher-order, dynamically typed, partially lazy, functional language."

  7. Data analysis for fraud detection - Wikipedia

    en.wikipedia.org/wiki/Data_analysis_for_fraud...

    Some forensic accountants specialize in forensic analytics which is the procurement and analysis of electronic data to reconstruct, detect, or otherwise support a claim of financial fraud. The main steps in forensic analytics are data collection, data preparation, data analysis, and reporting.

  8. Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Excel

    Excel can accept data in real-time through several programming interfaces, which allow it to communicate with many data sources such as Bloomberg and Reuters (through addins such as Power Plus Pro). DDE: "Dynamic Data Exchange" uses the message passing mechanism in Windows to allow data to flow between Excel and other applications.

  9. Data Analysis Expressions - Wikipedia

    en.wikipedia.org/wiki/Data_Analysis_eXpressions

    Data Analysis Expressions (DAX) is the native formula and query language for Microsoft PowerPivot, Power BI Desktop and SQL Server Analysis Services (SSAS) Tabular models. DAX includes some of the functions that are used in Excel formulas with additional functions that are designed to work with relational data and perform dynamic aggregation .

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