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令和7年度 ITパスポート試験 問22

This question's explanation and your answers so far.

問22
頻出度★★☆

営業部のA さんは, 営業担当者10人の営業成績が一目で分かるように, 各営業担当者が提出する営業見込みと実績を毎月集約してグラフ化したいと考えている。この問題を解決するために適用する技術やツールとして, 最も適切なものはどれか。

出典 令和7年度 ITパスポート試験 問22
解説

問 22

  • Incorrectア

    AI (that learns from and analyzes data) is a technology for advanced analysis such as pattern learning and prediction. This question only aggregates known figures and turns them into a graph, requiring no learning or inference, so AI is excessive and does not fit the purpose.

  • Incorrectイ

    IoT (that automatically collects data and accumulates it in a database) is a mechanism that automatically obtains data from devices such as sensors. The data in this question is submitted and entered manually by each salesperson, so it is not a target for automatic collection by IoT.

  • ウ

    正解 The correct answer is ウ. The sales forecasts and actual results of 10 salespeople are numerical data that each person already enters; aggregating them every month, computing totals and comparisons, processing them into graphs (tables or charts), and presenting them in a form that can be understood 'at a glance' is exactly the strength of office tools, typified by spreadsheet software. They can easily handle data entry, aggregation, and graphing, and fit best with the scale of this question, which requires neither large-scale data nor advanced analytical methods. Therefore, 'office tools that process and present the entered data' is the most appropriate.

  • Incorrectエ

    Data science (that analyzes big data with various methods) is a specialized analytical method for drawing insights from large and diverse data. For aggregating and graphing the small-scale, routine data of 10 people's forecasts and actual results, it is overkill and not appropriate.

ここがポイント
  • Match the purpose (visualization by aggregating and graphing known data) with the scale of the means: for small-scale, routine data visualization, office tools such as spreadsheet software are sufficient.
  • AI / IoT / data science are technologies aimed at advanced, automated, and large-scale scenarios. This question tests the perspective of not choosing means beyond what is needed (avoiding excessive technology).
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