Row 51346

Row ID: 51346 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 51346 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

This is only true if you define data analytics as very basic analytics pipelines and not the other billion things you need to do to get data analytics right, like actually having SME knowledge of how the analysis you're doing fits into the business (and the biz problems you're solving), being able to communicate the data to non-data people in a way that drives meaningful decision making and not just smoke and mirrors bullshit, and how to critically think (and question) outputs from machine-driven processes that look/sound right but feel somehow off (usually indicative of some faulty logic somewhere in the pipeline or flow).

As always, the baseline expectations will increase: Nonsense work that can be automated will be automated, and data analysts will be expected to leverage that automation rather than do that job day in and day out.

FieldValue
text This is only true if you define data analytics as very basic analytics pipelines and not the other billion things you need to do to get data analytics right, like actually having SME knowledge of how the analysis you're doing fits into the business (and the biz problems you're solving), being able to communicate the data to non-data people in a way that drives meaningful decision making and not just smoke and mirrors bullshit, and how to critically think (and question) outputs from machine-drive…
label r/technology
dataType comment
communityName r/technology
datetime 2024-05-22
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Raw Record

{
  "text": "This is only true if you define data analytics as very basic analytics pipelines and not the other billion things you need to do to get data analytics right, like actually having SME knowledge of how the analysis you're doing fits into the business (and the biz problems you're solving), being able to communicate the data to non-data people in a way that drives meaningful decision making and not just smoke and mirrors bullshit, and how to critically think (and question) outputs from machine-driven processes that look/sound right but feel somehow off (usually indicative of some faulty logic somewhere in the pipeline or flow).\n\nAs always, the baseline expectations will increase: Nonsense work that can be automated will be automated, and data analysts will be expected to leverage that automation rather than do that job day in and day out.",
  "label": "r/technology",
  "dataType": "comment",
  "communityName": "r/technology",
  "datetime": "2024-05-22",
  "username_encoded": "Z0FBQUFBQm5Lak1UQzJ5UjBpcHlRVWV4RnZBUG1WejRuNUFqWmlzS29sSk12RXFNUTItaENNUFZBcEJFTDlUWEJoektQMzJyLVZSTTdPclpMdThYRGQ1TWFtMFBDcUk2Z3BMZ0Iwc3ZfNVFKeVlmaUJfYkU5enc9",
  "url_encoded": "Z0FBQUFBQm5Lak9pSGVaTExnTV9BRUZLZWdpbVA3cGFXczlPRXJJUUxIVGpoVzdjS21jdHRnQURNRWs1VHlrWmo5dk92TEczT0kyaDhlT3RTXzExT2xTZ2FQUzFVY3JaVlVHMjBKWXVzcjlxT2VHTTFmNWdTa3Z5SzBNbklXRHI4eERvUjFOTHRmdnR5Sy1JSHNkYjdRWFBuY2RTUnh4ZXFURUJDUW1oSjktNkdWcG10bmE3WVVSWUZmM3MtVkpoNmpZZ0Zkd0o0c29PMEV5N1BhM0dENDBLSEhSckN0SDRHdz09"
}
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