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EnglishThree Steps to Complete the Full Data Analysis Process
When conducting data analysis, the most challenging issues typically boil down to three things: data scattered across different files, inconsistent values for the same metric across tables, and a time-consuming, labor-intensive data-cleaning process.
This issue will show you how to use Qwen Office to streamline the entire data-analysis workflow in just three steps—from importing multi-source data and intelligent cleaning to structured analysis—ultimately producing interactive reports, underlying data tables, and standardized glossary documents.
01 Import Basic Data from Multiple Sources
The data required for operational analysis is often spread across various locations: sales details are stored in Excel files, payment records are saved as CSVs, and user growth and inventory status each exist in separate, differently formatted tables.
First, simply drag all relevant files into the chat window. Whether it’s sales details, payment records, or inventory lists—even if formats vary significantly—Qwen Office automatically parses the content and standardizes it according to your business context.
In addition to local files, data exported from DingTalk Docs or internal enterprise systems can also be directly imported—the location of the data isn’t a limitation; as long as it’s readable, it can be used.
Prompt template (copyable):
I’ve uploaded [the attachment]. Please first parse the [attachment], then conduct a data-quality check, examining each item: ① Consistency of definitions (are sales and payments comparable?), ② Time granularity (do monthly/weekly/daily/timestamps align?), ③ Units and formats, ④ Duplicate records, ⑤ Other items needing confirmation. For each issue, indicate where it occurs, which metrics are affected, and suggest how to handle it. First, list everything for my review; after I approve each item, proceed with corrections—don’t modify the data on your own. Once cleaning is complete, generate a “Data Glossary Document” (defining metrics, calculation methods, data sources, and timestamps), then create a Q3 operational analysis report based on the cleaned data: total sales, product-mix breakdown, channel distribution, and trend insights, with data sources cited for each conclusion.
02 Organize Data and Standardize Definitions
Before formally cleaning the data, let AI thoroughly review its condition to avoid incorrect adjustments due to misinterpretation. After integrating multiple data sources, common problems often emerge:
For example, sales amounts may include tax while payments reflect net receipts—these two measures differ in nature and shouldn’t be compared directly; inventory represents stock at a specific point in time (e.g., September 30), whereas sales data covers the entire third quarter, making the timeframes incompatible; additionally, duplicate entries and mixed units/formatting may appear in the details.
In this stage, Qwen Office performs a comprehensive data-quality audit, covering definition discrepancies, time units, format consistency, and duplicate data. Each anomaly is clearly marked with its location and impact range, and corrections are made only after user approval, ensuring transparency and control.
Upon completion of cleaning, the system generates a “Data Glossary Document,” detailing the definitions, calculation methods, data sources, and timestamps for each metric, creating a traceable, standardized document. In the future, if colleagues ask, “How was this number calculated?” simply refer them to this document for a quick answer.
03 Generate Interactive Analysis Reports
With data definitions unified and content clean, analytical efficiency soars.
The “Q3 Operational Analysis Report” generated by Qwen Office covers key areas such as total sales, product-mix proportions, sales-channel distribution, and trend observations, with data sources cited for every conclusion—clicking any figure takes you back to the original table, enabling full traceability.
If the initial report doesn’t fully meet expectations, further questions can be posed, and the system will delve deeper into the dataset to uncover additional insights.
Finally, the report can be published as a web link with one click, making it easy to share with team members. No need to send attachments or worry about version control—just open the link to see the latest content.
04 Two Advanced Application Tips
Tip 1: Long-Term Memory Feature—Turn Analysis Workflows into Team Assets
The entire analysis process—including uploaded files, defined rules, and report structure—is automatically saved by Qwen Office. Next quarter, simply replace the new data, and the entire workflow can be reused without reconfiguration. Over time, these accumulated analytical logics become valuable data assets for your department and even the entire company.
Tip 2: Scheduled Auto-Updates for Dashboards—Transform One-Time Analysis into Continuous Monitoring
Operational analysis can be set as a recurring task: every week, the system automatically pulls the latest data, reruns the analysis, and updates the online dashboard. If abnormal fluctuations are detected, alerts are immediately sent. You don’t have to manually run the process weekly—just focus on interpreting the reasons behind the changes.
This concludes Lesson 2 of the Essential AI Office Course. The next installment will explore Qwen Office’s efficient applications in various scenarios.
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