# data[].attributes.headline
How does a sensemaking framework compare to other frameworks for understanding DBDM?

# data[].attributes.subject
How does a sensemaking framework compare to other frameworks for understanding DBDM?

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This one specifically focuses on the individual interpretation of the data which varies from person to person because of backgrounds, demographics, and personal belief systems

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Sense-making involves diving deeper into understanding one's own thought-process around data as well as understanding the influence of others on one's thought process about data.

# data[].attributes.subject
Sense-making involves diving deeper into understanding one's own thought-process around data as well as understanding the influence of others on one's thought process about data.

# data[].attributes.body
When it comes to understanding Data-Based Decision Making (DBDM), the sensemaking framework offers a unique perspective. Unlike other frameworks, it focuses on how stakeholders make sense of the data and information involved in the decision-making process. This framework emphasizes the importance of context, interpretation, and sensemaking in DBDM. It helps stakeholders navigate the complexities and uncertainties of data analysis and use it to inform decision-making effectively.

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Sense making is something that has already happened and we can provide personal experience to define. Other ideas are the beginning of the process.

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I think sense-making framework compares with other frameworks because it allows one to use their own experience and background to make understanding of an event or data. With that, they can adapt to the data and reevalute how an outcome or situation can adjust to the input.

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Sense-making can be subjective in nature and requires a deliberate recognition of confirmation bias.

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Sense making allows the human touch to be added to the data

# data[].attributes.subject
Sense making allows the human touch to be added to the data

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Sensemaking focuses on understanding the complexity and interpreting data in context, subjective to bias.