je pointe ici parce que, pour une fois, au milieu des généralités habituelles sur « la data », il est mentionné, parmi les compétences,
• la production de données
• et le nettoyage
Data literacy, the ability to read, understand, analyze and communicate information, helps companies make better decisions, improve performance and visualization, and better manage risks and opportunities.
[…]
What are the important data literacy skills?
Data types and structures
Understanding data as it evolves through different stages and data structures is a basic data skill. This involves not only recognizing numeric data from text data or categorical data, but also identifying raw data from data fit for business or data that is poorly formatted, incorrect or outdated.
How data is structured and stored and knowing where it came from are vital to building comprehensive data inventories and data flow charts, which will serve as the foundation for most data operations.
Data cleansing
A business intelligence dashboard that executives and leaders use to make decisions can be a liability if the data used to build it is incorrect. This means selecting raw data that is useful and making sure it is properly formatted and is not incorrect in any way.
Data generation
Data generation involves all the processes and endpoints used by a business to collect or create new data. Usually, the first stages of data generation are ripe with raw data. However, when collecting or generating new data, compliance, security and reliability of the data as well as a proper inventory are vital.
Data analysis
Data analytics involves recognizing which data is useful for a business goal and selecting that data as a “feature.” There are many automated technologies today that excel in data analytics, including automatic feature engineering.
However, humans are still vital for data and analytics to work well. Not only must the right data be identified, but it must be correlated with other data; patterns need to be found; and comparisons, conclusions and projections need to be made.
Data stories
Using data to tell data stories is a vital data literacy tool. No one wants to see endless Excel sheets during a presentation or read through them in an email. A person may be the most talented analytic expert on a team, but if they cannot use data to tell a story or communicate, connect and engage with others, the value of the data is lost.
Instead of using tables, data stories use high-impact graphs, visualizations, videos, animations, maps and other elements that make data more engaging and easier to understand.