Two PivotTables and a SUMIFS check summarize four stores' sales by category and month in the IT153 Unit 9 example, finished and cross-verified. Searches like "it 153 unit 9 assignment example", "it153 unit 9 sample" and "it153 unit 9 example" land here.
What a finished IT153 Unit 9 summary table exercise looks like
The Transactions sheet holds 420 composite rows as an Excel table: date, store, category, units and sales, spanning one quarter. A Store by Category sheet carries the first PivotTable, stores down the rows, six categories across the columns, sum of sales in the values area formatted as currency, with grand totals on both edges and a slicer for month beside it. A second PivotTable on its own sheet groups dates by month and shows units sold per category, sorted descending so the best seller leads. A Check sheet rebuilds four of the pivot's cells with SUMIFS against the table, store and category as criteria, beside a difference column that reads zero in every row. A PivotChart of the first table sits next to it, and a short findings paragraph names the strongest store and category pairing.
How a IT153 Unit 9 example is structured
The file moves from raw data to summary to proof, each on its own sheet, and never edits the raw data to make a summary look better. Formatting the source as a table means the PivotTables read a range that grows when new transactions are added, after a refresh. Field placement follows the buyer's question: stores in rows and categories in columns, because the question compares categories within each store. Values are summed rather than counted, a setting that is easy to get wrong when a field arrives as text, and number formatting is set on the value field itself so it survives a refresh. The SUMIFS check exists because a PivotTable can be right about the wrong range; matching four cells independently gives confidence in the rest. A findings note of three sentences states what the summary shows.
Transactions as a table
Four hundred twenty composite rows with consistent category names and real dates. As an Excel table, the source expands with new rows, and the PivotTables pick them up on refresh without any range edits.
Store by Category pivot
Stores in rows, categories in columns, sum of sales in values, currency format on the field. Grand totals on both edges show each store's total and each category's total at once.
Monthly units pivot and slicer
Dates grouped into months, units by category, sorted so the leading category sits first. A slicer for month on the first pivot isolates any single month in one selection.
SUMIFS cross-check
Four pivot cells recomputed from the raw table with SUMIFS, each with a difference column. Every difference is zero, which confirms that the pivot reads the full range with the right aggregation.
PivotChart and findings
A clustered column PivotChart mirrors the first table, and three sentences name the strongest store and category pairing and the category that trails in every store, citing the summary cells.
Where marks go in IT153 Unit 9
Summary-table exercises lose points to PivotTables that summarize the wrong thing. A value field set to Count instead of Sum, often because one sales entry was stored as text, produces tidy numbers that have nothing to do with revenue. Source ranges fixed at the original row count miss transactions added later, and pivots never refreshed after a data change show stale figures that graders catch by adding a row. Category names spelled two ways in the raw data, Childrens and Children's, split one category into two columns. Summaries built by hand-typing totals from filtered views lose the PivotTable row entirely. Missing number formats, default field names such as Sum of Sales left unexplained and no written interpretation each cost smaller amounts. Files that score well prove their summary against the raw data at least once.
Get a IT153 Unit 9 example written to your instructions
Name the question the Unit 9 summary has to answer, such as a staffing or stocking decision, if your IT153 prompt poses one, and add the data export, instructions and rubric. PivotTables, a check sheet and a findings note follow in 24-48h, shaped to that material. Your first custom sample is free.
IT153 Unit 9 questions, answered
Is a PivotTable required, or can I use formulas?
Read the prompt closely, because some IT153 assignments specifically grade a PivotTable while others accept a formula-based summary with SUMIFS or COUNTIFS. When a PivotTable is named, a formula table will not earn that row, however accurate. When either is allowed, the PivotTable is usually faster and the formulas easier to audit, so the sample carries both.
Why does my PivotTable show counts instead of totals?
Excel defaults a value field to Count when any cell in that column is blank or holds text, which often happens with imported data. Changing the value field setting to Sum fixes the display, but the underlying text entries are worth cleaning too, since they are excluded from the total. A SUMIFS check against the raw data exposes the gap.
Do I need to refresh the PivotTable?
Yes, whenever the source data changes. PivotTables store a snapshot of their source and do not recalculate like ordinary formulas. After editing or adding rows, a refresh brings the summary up to date, and a source formatted as an Excel table ensures new rows are included. Some graders test this directly by changing a value.