Adventure Works Cycles is a large and rapidly growing multinational manufacturer and seller of bicycles and accessories to commercial markets. In order to evaluate the company’s performance, their current marketing strategy’s effectiveness and to identify areas for marketing process improvement. The managements is interested in how revenue is generated over the years.
The query:
SELECT
ISNULL(A.[SalesTerritoryCountry],'TOTAL') AS Country
,FORMAT(SUM(B.[SalesAmount]),'$#,0.00') AS Revenue
FROM
[dbo].[DimSalesTerritory] A
LEFT JOIN [dbo].[FactInternetSales] B
ON A.SalesTerritoryKey=B.SalesTerritoryKey
WHERE
B.[SalesAmount] Is NOT NULL
GROUP BY
A.[SalesTerritoryCountry] WITH ROLLUP
ORDER BY /* Order by the country and have the group total at the bottom*/
CASE
WHEN SalesTerritoryCountry IS NULL THEN 1
ELSE 0
END
ASC, Country ASC;The Result Set:
| Country | Revenue |
|---|---|
| Australia | $9,061,000.58 |
| Canada | $1,977,844.86 |
| France | $2,644,017.71 |
| Germany | $2,894,312.34 |
| United Kingdom | $3,391,712.21 |
| United States | $9,389,789.51 |
| TOTAL | $29,358,677.22 |
The Visual:
The query:
SELECT
ISNULL(A.[SalesTerritoryCountry],'TOTAL') AS Country
,FORMAT(SUM(B.[SalesAmount]),'$#,0.00') AS Revenue
FROM
[dbo].[DimSalesTerritory] A
LEFT JOIN [dbo].[FactResellerSales] B
ON A.SalesTerritoryKey=B.SalesTerritoryKey
WHERE
B.[SalesAmount] Is NOT NULL
GROUP BY
A.[SalesTerritoryCountry] WITH ROLLUP
ORDER BY /* Order by the country and have the group total at the bottom*/
CASE
WHEN SalesTerritoryCountry IS NULL THEN 1
ELSE 0
END
ASC, Country ASC;The Result Set:
| Country | Revenue |
|---|---|
| Australia | $1,594,335.38 |
| Canada | $14,377,925.60 |
| France | $4,607,537.94 |
| Germany | $1,983,988.04 |
| United Kingdom | $4,279,008.83 |
| United States | $53,607,801.21 |
| TOTAL | $80,450,596.98 |
The Visual:
3. What is the Total Revenue by Location(Country and Continent) for Internet Sales and Reseller Sales?
The query:
SELECT
A.[SalesTerritoryCountry] AS Country
,A.[SalesTerritoryGroup] AS Continent
,FORMAT(SUM(B.[SalesAmount]),'$#,0.00') AS Revenue
FROM
[dbo].[DimSalesTerritory] A
LEFT JOIN [dbo].[FactInternetSales] B
ON A.SalesTerritoryKey=B.SalesTerritoryKey
LEFT JOIN [dbo].[FactResellerSales] C
ON B.SalesTerritoryKey=C.SalesTerritoryKey
WHERE
B.[SalesAmount] Is NOT NULL
GROUP BY
A.[SalesTerritoryCountry]
,A.[SalesTerritoryGroup]
ORDER BY
Revenue DESC;The Result Set:
| Country | Continent | Revenue |
|---|---|---|
| France | Europe | $9,333,382,531.48 |
| Germany | Europe | $5,322,640,389.95 |
| Canada | North America | $22,634,456,601.87 |
| Australia | Pacific | $15,521,494,001.08 |
| United Kingdom | Europe | $11,938,826,982.37 |
| United States | North America | $105,362,939,186.95 |
The Visual:
4. What is the Total Revenue by Location(Country and Continent) for Internet Sales and Reseller Sales (in separate columns)?
The query:
SELECT
A.[SalesTerritoryCountry] AS Country
,A.[SalesTerritoryGroup] AS Continent
,FORMAT(SUM(B.[SalesAmount]),'$#,0.00') AS internetRevenue
,FORMAT(SUM(C.[SalesAmount]),'$#,0.00') AS resellerRevenue
FROM
[dbo].[DimSalesTerritory] A
LEFT JOIN [dbo].[FactInternetSales] B
ON A.SalesTerritoryKey=B.SalesTerritoryKey
LEFT JOIN [dbo].[FactResellerSales] C
ON B.SalesTerritoryKey=C.SalesTerritoryKey
WHERE
B.[SalesAmount] Is NOT NULL
GROUP BY
A.[SalesTerritoryCountry]
,A.[SalesTerritoryGroup]
ORDER BY
internetRevenue DESC
,resellerRevenue DESC;The Result Set:
| Country | Continent | internetRevenue | resellerRevenue |
|---|---|---|---|
| France | Europe | $9,333,382,531.48 | $25,608,695,842.73 |
| Germany | Europe | $5,322,640,389.95 | $11,159,932,709.81 |
| Canada | North America | $22,634,456,601.87 | $109,559,793,045.33 |
| Australia | Pacific | $15,521,494,001.08 | $21,276,405,602.06 |
| United Kingdom | Europe | $11,938,826,982.37 | $29,550,834,956.50 |
| United States | North America | $105,362,939,186.95 | $338,971,891,689.64 |
The Visual:
5. What is the Total Revenue by Product Category for Internet Sales and Reseller Sales (in separate columns)?
The query:
SELECT
E.EnglishProductCategoryName AS CategoryName
,FORMAT(SUM(B.[SalesAmount]),'$#,0.00') AS Revenue
FROM
[dbo].[DimProduct] A
LEFT JOIN [dbo].[FactInternetSales] B
ON A.ProductKey=B.ProductKey
LEFT JOIN [dbo].[FactResellerSales] C
ON B.ProductKey=C.ProductKey
LEFT JOIN [dbo].[DimProductSubcategory] D
ON A.ProductSubcategoryKey=D.ProductSubcategoryKey
LEFT JOIN [dbo].[DimProductCategory] E
ON D.ProductCategoryKey=E.ProductCategoryKey
WHERE
B.[SalesAmount] Is NOT NULL
GROUP BY
E.EnglishProductCategoryName
ORDER BY
Revenue DESC;The Result Set:
| CategoryName | Revenue |
|---|---|
| Bikes | $5,514,174,492.66 |
| Accessories | $128,262,539.07 |
| Clothing | $101,053,213.75 |
The Visual:
The query:
SELECT TOP 10
A.EnglishProductName AS Product
,SUM(B.[SalesAmount]) AS Revenue
FROM
[dbo].[DimProduct] A
LEFT JOIN [dbo].[FactInternetSales] B
ON A.ProductKey=B.ProductKey
LEFT JOIN [dbo].[FactResellerSales] C
ON B.ProductKey=C.ProductKey
WHERE
B.[SalesAmount] Is NOT NULL
GROUP BY
A.EnglishProductName
ORDER BY
Revenue DESC;The Result Set:
| Product | Revenue |
|---|---|
| Mountain-200 Black, 38 | $428,863,632.9916 |
| Mountain-200 Black, 42 | $361,345,273.0446 |
| Mountain-200 Silver, 38 | $314,967,971.7216 |
| Mountain-200 Black, 46 | $298,453,039.435 |
| Mountain-200 Silver, 46 | $286,538,979.9384 |
| Mountain-200 Silver, 42 | $283,256,857.0944 |
| Road-150 Red, 56 | $190,006,137.00 |
| Road-150 Red, 62 | $161,108,028.48 |
| Road-250 Black, 48 | $142,851,679.425 |
| Road-350-W Yellow, 40 | $136,831,037.58 |
The Visual:
The query:
SELECT TOP 10
A.EnglishProductName AS Product
,SUM(B.[SalesAmount]) AS Revenue
FROM
[dbo].[DimProduct] A
LEFT JOIN [dbo].[FactInternetSales] B
ON A.ProductKey=B.ProductKey
LEFT JOIN [dbo].[FactResellerSales] C
ON B.ProductKey=C.ProductKey
WHERE
B.[SalesAmount] Is NOT NULL
GROUP BY
A.EnglishProductName
ORDER BY
Revenue ASC;The Result Set:
| Product | Revenue |
|---|---|
| Touring Tire Tube | $7,425.12 |
| Road Tire Tube | $9,480.24 |
| Road Bottle Cage | $15,390.88 |
| Mountain Tire Tube | $15,444.05 |
| Mountain Bottle Cage | $20,229.75 |
| Long-Sleeve Logo Jersey, S | $21,445.71 |
| LL Mountain Tire | $21,541.38 |
| Short-Sleeve Classic Jersey, M | $21,973.93 |
| LL Road Tire | $22,435.56 |
| ML Road Tire | $23,140.74 |
The Visual:
The query:
SELECT
CONCAT(A.FirstName,' ',A.LastName) AS FullName
,A.EmailAddress
,C.SalesTerritoryCountry
,SUM(B.SalesAmount) AS Revenue
FROM
[dbo].[DimEmployee] A
LEFT JOIN [dbo].[FactResellerSales] B
ON A.EmployeeKey=B.EmployeeKey
LEFT JOIN [dbo].[DimSalesTerritory] C
ON B.SalesTerritoryKey=C.SalesTerritoryKey
WHERE
Title LIKE 'Sales Representative'
GROUP BY
CONCAT(A.FirstName,' ',A.LastName)
,A.EmailAddress
,C.SalesTerritoryCountry
ORDER BY
Revenue DESC
,FullNameThe Result Set:
| FullName | EmailAddress | Country | Revenue |
|---|---|---|---|
| Linda Mitchell | linda3@adventure-works.com | United States | $10,367,007.4286 |
| Jillian Carson | jillian0@adventure-works.com | United States | $10,065,803.5429 |
| Michael Blythe | michael9@adventure-works.com | United States | $9,293,903.0055 |
| Jae Pak | jae0@adventure-works.com | Canada | $8,503,338.6472 |
| Tsvi Reiter | tsvi0@adventure-works.com | United States | $7,171,012.7514 |
| Shu Ito | shu0@adventure-works.com | United States | $6,427,005.5556 |
| Ranjit Varkey Chudukatil | ranjit0@adventure-works.com | France | $4,509,888.933 |
| José Saraiva | josé1@adventure-works.com | United Kingdom | $3,837,927.1902 |
| David Campbell | david8@adventure-works.com | United States | $3,729,945.3501 |
| Garrett Vargas | garrett1@adventure-works.com | Canada | $3,609,447.2163 |
| Pamela Ansman-Wolfe | pamela0@adventure-works.com | United States | $3,325,102.5952 |
| Tete Mensa-Annan | tete0@adventure-works.com | United States | $2,312,545.6905 |
| José Saraiva | josé1@adventure-works.com | Canada | $2,088,491.1672 |
| Rachel Valdez | rachel0@adventure-works.com | Germany | $1,790,640.2311 |
| Lynn Tsoflias | lynn0@adventure-works.com | Australia | $1,421,810.9252 |
The query:
SELECT
[MonthNumberOfYear] AS MonthNo
,[CalendarYear] AS Year_
,[EnglishMonthName] AS Month_
,FORMAT(SUM([SalesAmount]),'$#,0.00') AS Revenue
FROM
[dbo].[FactInternetSales] A
LEFT JOIN [dbo].[DimDate] B
ON A.OrderDateKey=B.DateKey
GROUP BY
[MonthNumberOfYear]
,[CalendarYear]
,[EnglishMonthName]
ORDER BY
[CalendarYear] DESC
,[MonthNumberOfYear] DESC;The Result Set:
| MonthNo | Year | MonthName | Revenue |
|---|---|---|---|
| 1 | 2014 | January | $45,694.72 |
| 12 | 2013 | December | $1,874,360.29 |
| 11 | 2013 | November | $1,780,920.06 |
| 10 | 2013 | October | $1,673,293.41 |
| 9 | 2013 | September | $1,447,495.69 |
| 8 | 2013 | August | $1,551,065.56 |
| 7 | 2013 | July | $1,371,675.81 |
| 6 | 2013 | June | $1,643,177.78 |
| 5 | 2013 | May | $1,284,592.93 |
| 4 | 2013 | April | $1,046,022.77 |
| 3 | 2013 | March | $1,049,907.39 |
| 2 | 2013 | February | $771,348.74 |
| 1 | 2013 | January | $857,689.91 |
| 12 | 2012 | December | $624,502.17 |
| 11 | 2012 | November | $537,955.52 |
| 10 | 2012 | October | $535,159.48 |
| 9 | 2012 | September | $486,177.45 |
| 8 | 2012 | August | $523,917.38 |
| 7 | 2012 | July | $444,558.23 |
| 6 | 2012 | June | $555,160.14 |
| 5 | 2012 | May | $358,877.89 |
| 4 | 2012 | April | $400,335.61 |
| 3 | 2012 | March | $373,483.01 |
| 2 | 2012 | February | $506,994.19 |
| 1 | 2012 | January | $495,364.13 |
| 12 | 2011 | December | $669,431.50 |
| 11 | 2011 | November | $660,545.81 |
| 10 | 2011 | October | $708,208.00 |
| 9 | 2011 | September | $603,083.50 |
| 8 | 2011 | August | $614,557.94 |
| 7 | 2011 | July | $596,746.56 |
| 6 | 2011 | June | $737,839.82 |
| 5 | 2011 | May | $561,681.48 |
| 4 | 2011 | April | $502,073.85 |
| 3 | 2011 | March | $485,198.66 |
| 2 | 2011 | February | $466,334.90 |
| 1 | 2011 | January | $469,823.91 |
| 12 | 2010 | December | $43,421.04 |
The query:
SELECT
[MonthNumberOfYear] AS MonthNo
,[CalendarYear] AS Year_
,[EnglishMonthName] AS Month_
,FORMAT(SUM([SalesAmount]),'$#,0.00') AS Revenue
FROM
[dbo].[FactResellerSales] A
LEFT JOIN [dbo].[DimDate] B
ON A.OrderDateKey=B.DateKey
GROUP BY
[MonthNumberOfYear]
,[CalendarYear]
,[EnglishMonthName]
ORDER BY
[CalendarYear] DESC
,[MonthNumberOfYear] DESC;The Result Set:
| MonthNo | Year | MonthName | Revenue |
|---|---|---|---|
| 11 | 2013 | November | $3,416,234.85 |
| 10 | 2013 | October | $3,314,600.78 |
| 9 | 2013 | September | $2,206,725.22 |
| 8 | 2013 | August | $2,738,653.62 |
| 7 | 2013 | July | $2,699,300.79 |
| 6 | 2013 | June | $1,662,547.32 |
| 5 | 2013 | May | $3,510,948.73 |
| 4 | 2013 | April | $3,483,161.40 |
| 3 | 2013 | March | $2,282,115.88 |
| 2 | 2013 | Febraury | $4,047,574.04 |
| 1 | 2013 | January | $4,212,971.51 |
| 12 | 2012 | December | $2,665,650.54 |
| 11 | 2012 | November | $1,987,872.71 |
| 10 | 2012 | October | $2,880,752.68 |
| 9 | 2012 | September | $1,865,278.43 |
| 8 | 2012 | August | $1,563,955.08 |
| 7 | 2012 | July | $2,384,846.59 |
| 6 | 2012 | June | $1,317,541.83 |
| 5 | 2012 | May | $2,185,213.21 |
| 4 | 2012 | April | $3,053,816.33 |
| 3 | 2012 | March | $1,802,154.21 |
| 2 | 2012 | February | $2,885,359.20 |
| 1 | 2012 | January | $3,601,190.71 |
| 12 | 2011 | December | $1,001,803.77 |
| 11 | 2011 | November | $2,269,116.71 |
| 10 | 2011 | October | $882,899.94 |
| 9 | 2011 | September | $3,356,069.34 |
| 8 | 2011 | August | $713,116.69 |
| 7 | 2011 | July | $4,027,080.34 |
| 5 | 2011 | May | $2,010,618.07 |
| 4 | 2011 | April | $1,538,408.31 |
| 3 | 2011 | March | $489,328.58 |
The query:
SELECT [CalendarYear] AS [Year]
,[MonthNumberOfYear] AS [Month]
,FORMAT(SUM([SalesAmount]), '$#,0.00') AS Revenue
,CONCAT(
100*(SUM([SalesAmount])-LAG(SUM([SalesAmount]), 1, 0) OVER(ORDER BY [CalendarYear],[MonthNumberOfYear] ASC))/LAG(SUM([SalesAmount]), 1) OVER(ORDER BY [CalendarYear],[MonthNumberOfYear] ASC)
,'%'
) AS [MoM Growth]
FROM [dbo].[FactInternetSales] A
LEFT JOIN [dbo].[DimDate] B ON A.OrderDateKey=B.DateKey
GROUP BY [CalendarYear] ,
[MonthNumberOfYear]
ORDER BY [Year] DESC,
[Month] DESC;The Result Set:
| Year | Month | Revenue | MoM Growth |
|---|---|---|---|
| 2014 | 1 | $45,694.72 | -97.56% |
| 2013 | 12 | $1,874,360.29 | 5.25% |
| 2013 | 11 | $1,780,920.06 | 6.43% |
| 2013 | 10 | $1,673,293.41 | 15.60% |
| 2013 | 9 | $1,447,495.69 | -6.68% |
| 2013 | 8 | $1,551,065.56 | 13.08% |
| 2013 | 7 | $1,371,675.81 | -16.52% |
| 2013 | 6 | $1,643,177.78 | 27.91% |
| 2013 | 5 | $1,284,592.93 | 22.81% |
| 2013 | 4 | $1,046,022.77 | -0.37% |
| 2013 | 3 | $1,049,907.39 | 36.11% |
| 2013 | 2 | $771,348.74 | -10.07% |
| 2013 | 1 | $857,689.91 | 37.34% |
| 2012 | 12 | $624,502.17 | 16.09% |
| 2012 | 11 | $537,955.52 | 0.52% |
| 2012 | 10 | $535,159.48 | 10.07% |
| 2012 | 9 | $486,177.45 | -7.20% |
| 2012 | 8 | $523,917.38 | 17.85% |
| 2012 | 7 | $444,558.23 | -19.92% |
| 2012 | 6 | $555,160.14 | 54.69% |
| 2012 | 5 | $358,877.89 | -10.36% |
| 2012 | 4 | $400,335.61 | 7.19% |
| 2012 | 3 | $373,483.01 | -26.33% |
| 2012 | 2 | $506,994.19 | 2.35% |
| 2012 | 1 | $495,364.13 | -26.00% |
| 2011 | 12 | $669,431.50 | 1.35% |
| 2011 | 11 | $660,545.81 | -6.73% |
| 2011 | 10 | $708,208.00 | 17.43% |
| 2011 | 9 | $603,083.50 | -1.87% |
| 2011 | 8 | $614,557.94 | 2.98% |
| 2011 | 7 | $596,746.56 | -19.12% |
| 2011 | 6 | $737,839.82 | 31.36% |
| 2011 | 5 | $561,681.48 | 11.87% |
| 2011 | 4 | $502,073.85 | 3.48% |
| 2011 | 3 | $485,198.66 | 4.05% |
| 2011 | 2 | $466,334.90 | -0.74% |
| 2011 | 1 | $469,823.91 | 982.02% |
| 2010 | 12 | $43,421.04 |
The query:
SELECT [CalendarYear] AS [Year]
,[MonthNumberOfYear] AS [Month]
,FORMAT(SUM([SalesAmount]), '$#,0.00') AS Revenue
,CONCAT(
100*(SUM([SalesAmount])-LAG(SUM([SalesAmount]), 1, 0) OVER(ORDER BY [CalendarYear],[MonthNumberOfYear] ASC))/LAG(SUM([SalesAmount]), 1) OVER(ORDER BY [CalendarYear],[MonthNumberOfYear] ASC)
,'%'
) AS [MoM Growth]
FROM [dbo].[FactResellerSales] A
LEFT JOIN [dbo].[DimDate] B ON A.OrderDateKey=B.DateKey
GROUP BY [CalendarYear] ,
[MonthNumberOfYear]
ORDER BY [Year] DESC,
[Month] DESC;The Result Set:
| Year | Month | ResellerRevenue | MoM Growth |
|---|---|---|---|
| 2013 | 11 | $3,416,234.85 | 3.07% |
| 2013 | 10 | $3,314,600.78 | 50.20% |
| 2013 | 9 | $2,206,725.22 | -19.42% |
| 2013 | 8 | $2,738,653.62 | 1.46% |
| 2013 | 7 | $2,699,300.79 | 62.36% |
| 2013 | 6 | $1,662,547.32 | -52.65% |
| 2013 | 5 | $3,510,948.73 | 0.80% |
| 2013 | 4 | $3,483,161.40 | 52.63% |
| 2013 | 3 | $2,282,115.88 | -43.62% |
| 2013 | 2 | $4,047,574.04 | -3.93% |
| 2013 | 1 | $4,212,971.51 | 58.05% |
| 2012 | 12 | $2,665,650.54 | 34.10% |
| 2012 | 11 | $1,987,872.71 | -30.99% |
| 2012 | 10 | $2,880,752.68 | 54.44% |
| 2012 | 9 | $1,865,278.43 | 19.27% |
| 2012 | 8 | $1,563,955.08 | -34.42% |
| 2012 | 7 | $2,384,846.59 | 81.01% |
| 2012 | 6 | $1,317,541.83 | -39.71% |
| 2012 | 5 | $2,185,213.21 | -28.44% |
| 2012 | 4 | $3,053,816.33 | 69.45% |
| 2012 | 3 | $1,802,154.21 | -37.54% |
| 2012 | 2 | $2,885,359.20 | -19.88% |
| 2012 | 1 | $3,601,190.71 | 50.45% |
| 2011 | 12 | $2,393,689.53 | 138.94% |
| 2011 | 11 | $1,001,803.77 | -55.85% |
| 2011 | 10 | $2,269,116.71 | 157.01% |
| 2011 | 9 | $882,899.94 | -73.69% |
| 2011 | 8 | $3,356,069.34 | 370.62% |
| 2011 | 7 | $713,116.69 | -82.29% |
| 2011 | 5 | $4,027,080.34 | 100.29% |
| 2011 | 3 | $2,010,618.07 | 30.69% |
| 2011 | 1 | $1,538,408.31 | 214.39% |
| 2010 | 12 | $489,328.58 | % |
The query:
SELECT
[MonthNumberOfYear]
,[CalendarYear] AS Year
,[EnglishMonthName] AS Month
,COUNT(DISTINCT[CustomerKey]) AS TotalCustomer
FROM
[dbo].[FactInternetSales] A
LEFT JOIN [dbo].[DimDate] B
ON A.OrderDateKey=B.DateKey
GROUP BY
[MonthNumberOfYear]
,[CalendarYear]
,[EnglishMonthName]
ORDER BY
[CalendarYear] DESC
,[MonthNumberOfYear] DESC;The Result Set:
| MonthNumberOfYear | Year | Month | TotalCustomer |
|---|---|---|---|
| 1 | 2014 | January | 834 |
| 12 | 2013 | December | 2133 |
| 11 | 2013 | November | 2036 |
| 10 | 2013 | October | 2073 |
| 9 | 2013 | September | 1832 |
| 8 | 2013 | August | 1900 |
| 7 | 2013 | July | 1796 |
| 6 | 2013 | June | 1948 |
| 5 | 2013 | May | 1719 |
| 4 | 2013 | April | 1564 |
| 3 | 2013 | March | 1631 |
| 2 | 2013 | February | 1373 |
| 1 | 2013 | January | 627 |
| 12 | 2012 | December | 354 |
| 11 | 2012 | November | 324 |
| 10 | 2012 | October | 313 |
| 9 | 2012 | September | 269 |
| 8 | 2012 | August | 294 |
| 7 | 2012 | July | 246 |
| 6 | 2012 | June | 318 |
| 5 | 2012 | May | 207 |
| 4 | 2012 | April | 219 |
| 3 | 2012 | March | 212 |
| 2 | 2012 | February | 260 |
| 1 | 2012 | January | 252 |
| 12 | 2011 | December | 222 |
| 11 | 2011 | November | 208 |
| 10 | 2011 | October | 221 |
| 9 | 2011 | September | 185 |
| 8 | 2011 | August | 193 |
| 7 | 2011 | July | 188 |
| 6 | 2011 | June | 230 |
| 5 | 2011 | May | 174 |
| 4 | 2011 | April | 157 |
| 3 | 2011 | March | 150 |
| 2 | 2011 | February | 144 |
| 1 | 2011 | January | 144 |
| 12 | 2010 | December | 14 |
The query:
SELECT
SELECT
[MonthNumberOfYear]
,[CalendarYear] AS Year
,[EnglishMonthName] AS Month
,COUNT(DISTINCT[ResellerKey]) AS TotalReseller
FROM
[dbo].[FactResellerSales] A
LEFT JOIN [dbo].[DimDate] B
ON A.OrderDateKey=B.DateKey
GROUP BY
[MonthNumberOfYear]
,[CalendarYear]
,[EnglishMonthName]
ORDER BY
[CalendarYear] DESC
,[MonthNumberOfYear] DESC;The Result Set:
| MonthNumberOfYear | Year | Month | TotalReseller |
|---|---|---|---|
| 11 | 2013 | November | 179 |
| 10 | 2013 | October | 178 |
| 9 | 2013 | September | 91 |
| 8 | 2013 | August | 173 |
| 7 | 2013 | July | 174 |
| 6 | 2013 | June | 93 |
| 5 | 2013 | May | 174 |
| 4 | 2013 | April | 177 |
| 3 | 2013 | March | 96 |
| 2 | 2013 | February | 174 |
| 1 | 2013 | January | 183 |
| 12 | 2012 | December | 93 |
| 11 | 2012 | November | 102 |
| 10 | 2012 | October | 134 |
| 9 | 2012 | September | 74 |
| 8 | 2012 | August | 106 |
| 7 | 2012 | July | 132 |
| 6 | 2012 | June | 65 |
| 5 | 2012 | May | 114 |
| 4 | 2012 | April | 133 |
| 3 | 2012 | March | 73 |
| 2 | 2012 | February | 111 |
| 1 | 2012 | January | 139 |
| 12 | 2011 | December | 72 |
| 11 | 2011 | November | 68 |
| 10 | 2011 | October | 85 |
| 9 | 2011 | September | 37 |
| 8 | 2011 | August | 143 |
| 7 | 2011 | July | 40 |
| 5 | 2011 | May | 153 |
| 3 | 2011 | March | 100 |
| 1 | 2011 | January | 75 |
| 12 | 2010 | December | 38 |