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Jupyter

Data-driven business analytics. 3DM

 

Combination of skills, technologies, and practices needed to transform business data into insights to drive business planning and data-informed decision-makingverifiable.

  • Descriptive analytics.Interpretation of historical data, KPI's, OKR's. Detection of trends, seasonality, cyclicality and thresholds of key metrics.

  • Trend analysis:. Historical data and time series; simple and multiple correlation analysis, determination of influential elements (KI).

  • Predictive analytics. Statistical modeling, probabilistic simulation techniques and scenario generation.

 
 
 
 

platforms

 
Plataformas
python. This environment is flexible and multipurpose with a large community of analysts and data scientists.
2/3 of data scientists use Python as their main language since, among other advantages, it is free, open source and also has a large community and ecosystem of third-party packages that facilitate the treatment, analysis and interpretation of data and information.
 
 
Jupyter
JupyterIt is a platform that supports several execution environments in different programming languages.
Its Notebook version is like a document, with different input and output instructions, which can be codes, texts, mathematical functions, graphics and rich text, all combined in a single workbook, widely used in preparation, analysis, transformation and visualization procedures. of large volumes of data.
 
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Jupyter2
Pandas
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Data analysis with Pandas.  It is the quintessential Data Science software library; allows the treatment and analysis of data on Python.
It offers data structures and operations to manipulate number tables and time series.
It is a flexible, powerful, and high-performance tool for performing quantitative analysis of large amounts of data.
 
 
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