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Many data workers are complaining about the fierce competition in the data area. Fortunately, the situation seems to be improving. Data analysts had to manually analyze distribution charts for deep insights, but now they can use smart machine learning models to automate this process. Traditional data analysis and modeling skills have been gradually becoming easy. For instance, Power BI or Tableau allow users to use a drag-and-drop low-code fashion to generate visual charts and models, whilst the old way is to import Python libraries such as pandas, matplotlib and sklearn to do the same in Jupyter Notebook. Open-source projects Apache Superset and Metabase allow users to easily analyze data on the web pages. This is quite similar to the development of digital cameras, from the film cameras to digital cameras and to smartphone cameras used by everyone. With lower and lower technical barriers, the whole industry can be developing fast. "Everyone can be data analyst" will no longer be a fantasy.
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Many data workers are complaining about the fierce competition in the data area. Fortunately, the situation seems to be improving. Data analysts had to manually analyze distribution charts for deep insights, but now they can use smart machine learning models to automate this process. Traditional data analysis and modeling skills have been gradually becoming easy. For instance, Power BI or Tableau allow users to use a drag-and-drop low-code fashion to generate visual charts and models, whilst the old way is to import Python libraries such as pandas, matplotlib and sklearn to do the same in Jupyter Notebook. Open-source projects Apache Superset and Metabase allow users to easily analyze data on the web pages. This is quite similar to the development of digital cameras, from the film cameras to digital cameras and to smartphone cameras used by everyone. With lower and lower technical barriers, the whole industry can be developing fast. "Everyone can be data analyst" will no longer be a fantasy.
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Onboard AI
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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Many data workers are complaining about the fierce competition in the data area. Fortunately, the situation seems to be improving. Data analysts had to manually analyze distribution charts for deep insights, but now they can use smart machine learning models to automate this process. Traditional data analysis and modeling skills have been gradually becoming easy. For instance, Power BI or Tableau allow users to use a drag-and-drop low-code fashion to generate visual charts and models, whilst the old way is to import Python libraries such as pandas, matplotlib and sklearn to do the same in Jupyter Notebook. Open-source projects Apache Superset and Metabase allow users to easily analyze data on the web pages. This is quite similar to the development of digital cameras, from the film cameras to digital cameras and to smartphone cameras used by everyone. With lower and lower technical barriers, the whole industry can be developing fast. "Everyone can be data analyst" will no longer be a fantasy.
-
Many data workers are complaining about the fierce competition in the data area. Fortunately, the situation seems to be improving. Data analysts had to manually analyze distribution charts for deep insights, but now they can use smart machine learning models to automate this process. Traditional data analysis and modeling skills have been gradually becoming easy. For instance, Power BI or Tableau allow users to use a drag-and-drop low-code fashion to generate visual charts and models, whilst the old way is to import Python libraries such as pandas, matplotlib and sklearn to do the same in Jupyter Notebook. Open-source projects Apache Superset and Metabase allow users to easily analyze data on the web pages. This is quite similar to the development of digital cameras, from the film cameras to digital cameras and to smartphone cameras used by everyone. With lower and lower technical barriers, the whole industry can be developing fast. "Everyone can be data analyst" will no longer be a fantasy.
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