<?xml version='1.0' encoding='utf-8' ?>
<!-- build 10400.17.0915.2112 -->
<workbook original-version='10.4' source-build='10.4.0 (10400.17.0915.2112)' source-platform='win' version='10.4' xmlns:user='http://www.tableausoftware.com/xml/user'>
<preferences>
<preference name='ui.encoding.shelf.height' value='24' />
<preference name='ui.shelf.height' value='26' />
</preferences>
<datasources>
<datasource caption='Orders (Superstore 2)' inline='true' name='federated.1632qms1k9dpce1foxool1h7j9kg' version='10.4'>
<connection class='federated'>
<named-connections>
<named-connection caption='Superstore 2' name='excel-direct.1gm9qwb09rlv1i1cky0b1027dcu3'>
<connection class='excel-direct' cleaning='no' compat='no' dataRefreshTime='' filename='C:/Users/RAJAN/Downloads/Superstore 2.xlsx' interpretationMode='0' password='' server='' validate='no' />
</named-connection>
</named-connections>
<relation connection='excel-direct.1gm9qwb09rlv1i1cky0b1027dcu3' name='Orders' table='[Orders$]' type='table'>
<columns gridOrigin='A1:Z9427:no:A1:Z9427:0' header='yes' outcome='6'>
<column datatype='string' name='Category' ordinal='0' />
<column datatype='string' name='City' ordinal='1' />
<column datatype='string' name='Container' ordinal='2' />
<column datatype='integer' name='Customer ID' ordinal='3' />
<column datatype='string' name='Customer Name' ordinal='4' />
<column datatype='string' name='Customer Segment' ordinal='5' />
<column datatype='string' name='Department' ordinal='6' />
<column datatype='real' name='Discount' ordinal='7' />
<column datatype='integer' name='Item ID' ordinal='8' />
<column datatype='string' name='Item' ordinal='9' />
<column datatype='integer' name='Number of Records' ordinal='10' />
<column datatype='date' name='Order Date' ordinal='11' />
<column datatype='integer' name='Order ID' ordinal='12' />
<column datatype='string' name='Order Priority' ordinal='13' />
<column datatype='integer' name='Order Quantity' ordinal='14' />
<column datatype='integer' name='Postal Code' ordinal='15' />
<column datatype='real' name='Product Base Margin' ordinal='16' />
<column datatype='integer' name='Profit' ordinal='17' />
<column datatype='string' name='Region' ordinal='18' />
<column datatype='date' name='Row ID' ordinal='19' />
<column datatype='integer' name='Sales' ordinal='20' />
<column datatype='date' name='Ship Date' ordinal='21' />
<column datatype='string' name='Ship Mode' ordinal='22' />
<column datatype='integer' name='Shipping Cost' ordinal='23' />
<column datatype='string' name='State' ordinal='24' />
<column datatype='integer' name='Unit Price' ordinal='25' />
</columns>
</relation>
<metadata-records>
<metadata-record class='column'>
<remote-name>Category</remote-name>
<remote-type>130</remote-type>
<local-name>[Category]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Category</remote-alias>
<ordinal>0</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>City</remote-name>
<remote-type>130</remote-type>
<local-name>[City]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>City</remote-alias>
<ordinal>1</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Container</remote-name>
<remote-type>130</remote-type>
<local-name>[Container]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Container</remote-alias>
<ordinal>2</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Customer ID</remote-name>
<remote-type>20</remote-type>
<local-name>[Customer ID]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Customer ID</remote-alias>
<ordinal>3</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Customer Name</remote-name>
<remote-type>130</remote-type>
<local-name>[Customer Name]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Customer Name</remote-alias>
<ordinal>4</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Customer Segment</remote-name>
<remote-type>130</remote-type>
<local-name>[Customer Segment]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Customer Segment</remote-alias>
<ordinal>5</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Department</remote-name>
<remote-type>130</remote-type>
<local-name>[Department]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Department</remote-alias>
<ordinal>6</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Discount</remote-name>
<remote-type>5</remote-type>
<local-name>[Discount]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Discount</remote-alias>
<ordinal>7</ordinal>
<local-type>real</local-type>
<aggregation>Sum</aggregation>
<precision>15</precision>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"R8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Item ID</remote-name>
<remote-type>20</remote-type>
<local-name>[Item ID]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Item ID</remote-alias>
<ordinal>8</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Item</remote-name>
<remote-type>130</remote-type>
<local-name>[Item]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Item</remote-alias>
<ordinal>9</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Number of Records</remote-name>
<remote-type>20</remote-type>
<local-name>[Number of Records]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Number of Records</remote-alias>
<ordinal>10</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Order Date</remote-name>
<remote-type>7</remote-type>
<local-name>[Order Date]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Order Date</remote-alias>
<ordinal>11</ordinal>
<local-type>date</local-type>
<aggregation>Year</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"DATE"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Order ID</remote-name>
<remote-type>20</remote-type>
<local-name>[Order ID]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Order ID</remote-alias>
<ordinal>12</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Order Priority</remote-name>
<remote-type>130</remote-type>
<local-name>[Order Priority]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Order Priority</remote-alias>
<ordinal>13</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Order Quantity</remote-name>
<remote-type>20</remote-type>
<local-name>[Order Quantity]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Order Quantity</remote-alias>
<ordinal>14</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Postal Code</remote-name>
<remote-type>20</remote-type>
<local-name>[Postal Code]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Postal Code</remote-alias>
<ordinal>15</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Product Base Margin</remote-name>
<remote-type>5</remote-type>
<local-name>[Product Base Margin]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Product Base Margin</remote-alias>
<ordinal>16</ordinal>
<local-type>real</local-type>
<aggregation>Sum</aggregation>
<precision>15</precision>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"R8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Profit</remote-name>
<remote-type>20</remote-type>
<local-name>[Profit]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Profit</remote-alias>
<ordinal>17</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Region</remote-name>
<remote-type>130</remote-type>
<local-name>[Region]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Region</remote-alias>
<ordinal>18</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Row ID</remote-name>
<remote-type>7</remote-type>
<local-name>[Row ID]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Row ID</remote-alias>
<ordinal>19</ordinal>
<local-type>date</local-type>
<aggregation>Year</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"DATE"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Sales</remote-name>
<remote-type>20</remote-type>
<local-name>[Sales]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Sales</remote-alias>
<ordinal>20</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Ship Date</remote-name>
<remote-type>7</remote-type>
<local-name>[Ship Date]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Ship Date</remote-alias>
<ordinal>21</ordinal>
<local-type>date</local-type>
<aggregation>Year</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"DATE"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Ship Mode</remote-name>
<remote-type>130</remote-type>
<local-name>[Ship Mode]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Ship Mode</remote-alias>
<ordinal>22</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Shipping Cost</remote-name>
<remote-type>20</remote-type>
<local-name>[Shipping Cost]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Shipping Cost</remote-alias>
<ordinal>23</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>State</remote-name>
<remote-type>130</remote-type>
<local-name>[State]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>State</remote-alias>
<ordinal>24</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Unit Price</remote-name>
<remote-type>20</remote-type>
<local-name>[Unit Price]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Unit Price</remote-alias>
<ordinal>25</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='capability'>
<remote-name />
<remote-type>0</remote-type>
<parent-name>[Orders]</parent-name>
<remote-alias />
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='integer' name='context'>0</attribute>
<attribute datatype='string' name='gridOrigin'>"A1:Z9427:no:A1:Z9427:0"</attribute>
<attribute datatype='boolean' name='header'>true</attribute>
<attribute datatype='integer' name='outcome'>6</attribute>
</attributes>
</metadata-record>
</metadata-records>
</connection>
<column datatype='string' name='[City]' role='dimension' semantic-role='[City].[Name]' type='nominal' />
<column datatype='integer' name='[Customer ID]' role='dimension' type='ordinal' />
<column datatype='string' name='[Customer Segment]' role='dimension' type='nominal' />
<column datatype='integer' name='[Item ID]' role='dimension' type='ordinal' />
<column datatype='integer' name='[Number of Records]' role='measure' type='quantitative' user:auto-column='numrec' />
<column datatype='integer' name='[Order ID]' role='dimension' type='ordinal' />
<column datatype='integer' default-format='*00000' name='[Postal Code]' role='dimension' semantic-role='[ZipCode].[Name]' type='ordinal' />
<column datatype='string' name='[State]' role='dimension' semantic-role='[State].[Name]' type='nominal' />
<column-instance column='[Customer Segment]' derivation='None' name='[none:Customer Segment:nk]' pivot='key' type='nominal' />
<layout dim-ordering='alphabetic' dim-percentage='0.624579' measure-ordering='alphabetic' measure-percentage='0.375421' show-structure='true' />
<style>
<style-rule element='mark'>
<encoding attr='color' field='[none:Customer Segment:nk]' type='palette'>
<map to='#4e79a7'>
<bucket>"Consumer"</bucket>
</map>
<map to='#76b7b2'>
<bucket>"Small Business"</bucket>
</map>
<map to='#e15759'>
<bucket>"Home Office"</bucket>
</map>
<map to='#f28e2b'>
<bucket>"Corporate"</bucket>
</map>
</encoding>
</style-rule>
</style>
<semantic-values>
<semantic-value key='[Country].[Name]' value='"United States"' />
</semantic-values>
</datasource>
<datasource caption='Orders+ (Superstore 2)' inline='true' name='federated.0q9hf1i18nuchx1bfritc1nke7i9' version='10.4'>
<connection class='federated'>
<named-connections>
<named-connection caption='Superstore 2' name='excel-direct.07zl2so0hzk83h10cpiw51nxwzj4'>
<connection class='excel-direct' cleaning='no' compat='no' dataRefreshTime='' filename='C:/Users/RAJAN/Downloads/Superstore 2.xlsx' interpretationMode='0' password='' server='' validate='no' />
</named-connection>
</named-connections>
<relation join='inner' type='join'>
<clause type='join'>
<expression op='='>
<expression op='[Orders].[Order ID]' />
<expression op='[Returns].[Order ID]' />
</expression>
</clause>
<relation connection='excel-direct.07zl2so0hzk83h10cpiw51nxwzj4' name='Orders' table='[Orders$]' type='table'>
<columns gridOrigin='A1:Z9427:no:A1:Z9427:0' header='yes' outcome='6'>
<column datatype='string' name='Category' ordinal='0' />
<column datatype='string' name='City' ordinal='1' />
<column datatype='string' name='Container' ordinal='2' />
<column datatype='integer' name='Customer ID' ordinal='3' />
<column datatype='string' name='Customer Name' ordinal='4' />
<column datatype='string' name='Customer Segment' ordinal='5' />
<column datatype='string' name='Department' ordinal='6' />
<column datatype='real' name='Discount' ordinal='7' />
<column datatype='integer' name='Item ID' ordinal='8' />
<column datatype='string' name='Item' ordinal='9' />
<column datatype='integer' name='Number of Records' ordinal='10' />
<column datatype='date' name='Order Date' ordinal='11' />
<column datatype='integer' name='Order ID' ordinal='12' />
<column datatype='string' name='Order Priority' ordinal='13' />
<column datatype='integer' name='Order Quantity' ordinal='14' />
<column datatype='integer' name='Postal Code' ordinal='15' />
<column datatype='real' name='Product Base Margin' ordinal='16' />
<column datatype='integer' name='Profit' ordinal='17' />
<column datatype='string' name='Region' ordinal='18' />
<column datatype='date' name='Row ID' ordinal='19' />
<column datatype='integer' name='Sales' ordinal='20' />
<column datatype='date' name='Ship Date' ordinal='21' />
<column datatype='string' name='Ship Mode' ordinal='22' />
<column datatype='integer' name='Shipping Cost' ordinal='23' />
<column datatype='string' name='State' ordinal='24' />
<column datatype='integer' name='Unit Price' ordinal='25' />
</columns>
</relation>
<relation connection='excel-direct.07zl2so0hzk83h10cpiw51nxwzj4' name='Returns' table='[Returns$]' type='table'>
<columns gridOrigin='A1:C618:no:A1:C618:0' header='yes' outcome='6'>
<column datatype='integer' name='Order ID' ordinal='0' />
<column datatype='date' name='Return Date' ordinal='1' />
<column datatype='string' name='Return Reason' ordinal='2' />
</columns>
</relation>
</relation>
<cols>
<map key='[Category]' value='[Orders].[Category]' />
<map key='[City]' value='[Orders].[City]' />
<map key='[Container]' value='[Orders].[Container]' />
<map key='[Customer ID]' value='[Orders].[Customer ID]' />
<map key='[Customer Name]' value='[Orders].[Customer Name]' />
<map key='[Customer Segment]' value='[Orders].[Customer Segment]' />
<map key='[Department]' value='[Orders].[Department]' />
<map key='[Discount]' value='[Orders].[Discount]' />
<map key='[Item ID]' value='[Orders].[Item ID]' />
<map key='[Item]' value='[Orders].[Item]' />
<map key='[Number of Records]' value='[Orders].[Number of Records]' />
<map key='[Order Date]' value='[Orders].[Order Date]' />
<map key='[Order ID (Returns)]' value='[Returns].[Order ID]' />
<map key='[Order ID]' value='[Orders].[Order ID]' />
<map key='[Order Priority]' value='[Orders].[Order Priority]' />
<map key='[Order Quantity]' value='[Orders].[Order Quantity]' />
<map key='[Postal Code]' value='[Orders].[Postal Code]' />
<map key='[Product Base Margin]' value='[Orders].[Product Base Margin]' />
<map key='[Profit]' value='[Orders].[Profit]' />
<map key='[Region]' value='[Orders].[Region]' />
<map key='[Return Date]' value='[Returns].[Return Date]' />
<map key='[Return Reason]' value='[Returns].[Return Reason]' />
<map key='[Row ID]' value='[Orders].[Row ID]' />
<map key='[Sales]' value='[Orders].[Sales]' />
<map key='[Ship Date]' value='[Orders].[Ship Date]' />
<map key='[Ship Mode]' value='[Orders].[Ship Mode]' />
<map key='[Shipping Cost]' value='[Orders].[Shipping Cost]' />
<map key='[State]' value='[Orders].[State]' />
<map key='[Unit Price]' value='[Orders].[Unit Price]' />
</cols>
<metadata-records>
<metadata-record class='column'>
<remote-name>Category</remote-name>
<remote-type>130</remote-type>
<local-name>[Category]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Category</remote-alias>
<ordinal>0</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>City</remote-name>
<remote-type>130</remote-type>
<local-name>[City]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>City</remote-alias>
<ordinal>1</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Container</remote-name>
<remote-type>130</remote-type>
<local-name>[Container]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Container</remote-alias>
<ordinal>2</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Customer ID</remote-name>
<remote-type>20</remote-type>
<local-name>[Customer ID]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Customer ID</remote-alias>
<ordinal>3</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Customer Name</remote-name>
<remote-type>130</remote-type>
<local-name>[Customer Name]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Customer Name</remote-alias>
<ordinal>4</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Customer Segment</remote-name>
<remote-type>130</remote-type>
<local-name>[Customer Segment]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Customer Segment</remote-alias>
<ordinal>5</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Department</remote-name>
<remote-type>130</remote-type>
<local-name>[Department]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Department</remote-alias>
<ordinal>6</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Discount</remote-name>
<remote-type>5</remote-type>
<local-name>[Discount]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Discount</remote-alias>
<ordinal>7</ordinal>
<local-type>real</local-type>
<aggregation>Sum</aggregation>
<precision>15</precision>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"R8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Item ID</remote-name>
<remote-type>20</remote-type>
<local-name>[Item ID]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Item ID</remote-alias>
<ordinal>8</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Item</remote-name>
<remote-type>130</remote-type>
<local-name>[Item]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Item</remote-alias>
<ordinal>9</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Number of Records</remote-name>
<remote-type>20</remote-type>
<local-name>[Number of Records]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Number of Records</remote-alias>
<ordinal>10</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Order Date</remote-name>
<remote-type>7</remote-type>
<local-name>[Order Date]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Order Date</remote-alias>
<ordinal>11</ordinal>
<local-type>date</local-type>
<aggregation>Year</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"DATE"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Order ID</remote-name>
<remote-type>20</remote-type>
<local-name>[Order ID]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Order ID</remote-alias>
<ordinal>12</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Order Priority</remote-name>
<remote-type>130</remote-type>
<local-name>[Order Priority]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Order Priority</remote-alias>
<ordinal>13</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Order Quantity</remote-name>
<remote-type>20</remote-type>
<local-name>[Order Quantity]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Order Quantity</remote-alias>
<ordinal>14</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Postal Code</remote-name>
<remote-type>20</remote-type>
<local-name>[Postal Code]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Postal Code</remote-alias>
<ordinal>15</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Product Base Margin</remote-name>
<remote-type>5</remote-type>
<local-name>[Product Base Margin]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Product Base Margin</remote-alias>
<ordinal>16</ordinal>
<local-type>real</local-type>
<aggregation>Sum</aggregation>
<precision>15</precision>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"R8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Profit</remote-name>
<remote-type>20</remote-type>
<local-name>[Profit]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Profit</remote-alias>
<ordinal>17</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Region</remote-name>
<remote-type>130</remote-type>
<local-name>[Region]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Region</remote-alias>
<ordinal>18</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Row ID</remote-name>
<remote-type>7</remote-type>
<local-name>[Row ID]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Row ID</remote-alias>
<ordinal>19</ordinal>
<local-type>date</local-type>
<aggregation>Year</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"DATE"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Sales</remote-name>
<remote-type>20</remote-type>
<local-name>[Sales]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Sales</remote-alias>
<ordinal>20</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Ship Date</remote-name>
<remote-type>7</remote-type>
<local-name>[Ship Date]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Ship Date</remote-alias>
<ordinal>21</ordinal>
<local-type>date</local-type>
<aggregation>Year</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"DATE"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Ship Mode</remote-name>
<remote-type>130</remote-type>
<local-name>[Ship Mode]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Ship Mode</remote-alias>
<ordinal>22</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Shipping Cost</remote-name>
<remote-type>20</remote-type>
<local-name>[Shipping Cost]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Shipping Cost</remote-alias>
<ordinal>23</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>State</remote-name>
<remote-type>130</remote-type>
<local-name>[State]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>State</remote-alias>
<ordinal>24</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Unit Price</remote-name>
<remote-type>20</remote-type>
<local-name>[Unit Price]</local-name>
<parent-name>[Orders]</parent-name>
<remote-alias>Unit Price</remote-alias>
<ordinal>25</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='capability'>
<remote-name />
<remote-type>0</remote-type>
<parent-name>[Orders]</parent-name>
<remote-alias />
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='integer' name='context'>0</attribute>
<attribute datatype='string' name='gridOrigin'>"A1:Z9427:no:A1:Z9427:0"</attribute>
<attribute datatype='boolean' name='header'>true</attribute>
<attribute datatype='integer' name='outcome'>6</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Order ID</remote-name>
<remote-type>20</remote-type>
<local-name>[Order ID (Returns)]</local-name>
<parent-name>[Returns]</parent-name>
<remote-alias>Order ID</remote-alias>
<ordinal>26</ordinal>
<local-type>integer</local-type>
<aggregation>Sum</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"I8"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Return Date</remote-name>
<remote-type>7</remote-type>
<local-name>[Return Date]</local-name>
<parent-name>[Returns]</parent-name>
<remote-alias>Return Date</remote-alias>
<ordinal>27</ordinal>
<local-type>date</local-type>
<aggregation>Year</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"DATE"</attribute>
</attributes>
</metadata-record>
<metadata-record class='column'>
<remote-name>Return Reason</remote-name>
<remote-type>130</remote-type>
<local-name>[Return Reason]</local-name>
<parent-name>[Returns]</parent-name>
<remote-alias>Return Reason</remote-alias>
<ordinal>28</ordinal>
<local-type>string</local-type>
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<collation flag='1' name='LEN_RUS_S2' />
<attributes>
<attribute datatype='string' name='DebugRemoteType'>"WSTR"</attribute>
</attributes>
</metadata-record>
<metadata-record class='capability'>
<remote-name />
<remote-type>0</remote-type>
<parent-name>[Returns]</parent-name>
<remote-alias />
<aggregation>Count</aggregation>
<contains-null>true</contains-null>
<attributes>
<attribute datatype='integer' name='context'>0</attribute>
<attribute datatype='string' name='gridOrigin'>"A1:C618:no:A1:C618:0"</attribute>
<attribute datatype='boolean' name='header'>true</attribute>
<attribute datatype='integer' name='outcome'>6</attribute>
</attributes>
</metadata-record>
</metadata-records>
</connection>
<column datatype='string' name='[City]' role='dimension' semantic-role='[City].[Name]' type='nominal' />
<column datatype='integer' name='[Customer ID]' role='dimension' type='ordinal' />
<column datatype='string' name='[Customer Segment]' role='dimension' type='nominal' />
<column datatype='integer' name='[Item ID]' role='dimension' type='ordinal' />
<column datatype='integer' name='[Number of Records]' role='measure' type='quantitative' user:auto-column='numrec' />
<column datatype='integer' name='[Order ID (Returns)]' role='dimension' type='ordinal' />
<column datatype='integer' name='[Order ID]' role='dimension' type='ordinal' />
<column datatype='integer' default-format='*00000' name='[Postal Code]' role='dimension' semantic-role='[ZipCode].[Name]' type='ordinal' />
<column datatype='string' name='[State]' role='dimension' semantic-role='[State].[Name]' type='nominal' />
<column-instance column='[Customer Segment]' derivation='None' name='[none:Customer Segment:nk]' pivot='key' type='nominal' />
<layout dim-ordering='alphabetic' dim-percentage='0.612795' measure-ordering='alphabetic' measure-percentage='0.387205' show-structure='true' />
<style>
<style-rule element='mark'>
<encoding attr='color' field='[none:Customer Segment:nk]' type='palette'>
<map to='#4e79a7'>
<bucket>"Consumer"</bucket>
</map>
<map to='#76b7b2'>
<bucket>"Small Business"</bucket>
</map>
<map to='#e15759'>
<bucket>"Home Office"</bucket>
</map>
<map to='#f28e2b'>
<bucket>"Corporate"</bucket>
</map>
</encoding>
</style-rule>
</style>
<semantic-values>
<semantic-value key='[Country].[Name]' value='"United States"' />
</semantic-values>
</datasource>
</datasources>
<mapsources>
<mapsource name='Tableau' />
</mapsources>
<worksheets>
<worksheet name='QN 1'>
<layout-options>
<title>
<formatted-text>
<run bold='true' fontalignment='1' fontcolor='#4e79a7' fontsize='8'>Question 1</run>
</formatted-text>
</title>
</layout-options>
<table>
<view>
<datasources>
<datasource caption='Orders (Superstore 2)' name='federated.1632qms1k9dpce1foxool1h7j9kg' />
</datasources>
<datasource-dependencies datasource='federated.1632qms1k9dpce1foxool1h7j9kg'>
<column datatype='string' name='[Category]' role='dimension' type='nominal' />
<column datatype='string' name='[Customer Segment]' role='dimension' type='nominal' />
<column datatype='integer' name='[Profit]' role='measure' type='quantitative' />
<column-instance column='[Category]' derivation='None' name='[none:Category:nk]' pivot='key' type='nominal' />
<column-instance column='[Customer Segment]' derivation='None' name='[none:Customer Segment:nk]' pivot='key' type='nominal' />
<column-instance column='[Profit]' derivation='Sum' name='[sum:Profit:qk]' pivot='key' type='quantitative' />
</datasource-dependencies>
<aggregation value='true' />
</view>
<style>
<style-rule element='axis'>
<format attr='height' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Profit:qk]' value='40' />
</style-rule>
<style-rule element='label'>
<format attr='font-weight' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Profit:qk]' value='bold' />
<format attr='color' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Profit:qk]' value='#000000' />
<format attr='font-weight' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Category:nk]' value='bold' />
<format attr='color' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Category:nk]' value='#000000' />
<format attr='color' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Segment:nk]' value='#000000' />
<format attr='font-weight' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Segment:nk]' value='bold' />
</style-rule>
<style-rule element='legend-title-text'>
<format attr='color' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Segment:nk]' value='Customer Segment'>
<formatted-text>
<run bold='true' fontalignment='1'>Customer Segment</run>
</formatted-text>
</format>
</style-rule>
</style>
<panes>
<pane selection-relaxation-option='selection-relaxation-allow'>
<view>
<breakdown value='auto' />
</view>
<mark class='Automatic' />
<encodings>
<color column='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Segment:nk]' />
</encodings>
</pane>
</panes>
<rows>([federated.1632qms1k9dpce1foxool1h7j9kg].[none:Category:nk] / [federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Segment:nk])</rows>
<cols>[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Profit:qk]</cols>
</table>
</worksheet>
<worksheet name='QN 2'>
<layout-options>
<title>
<formatted-text>
<run bold='true' fontalignment='1' fontcolor='#59a14f' fontsize='10'>Question 2</run>
</formatted-text>
</title>
</layout-options>
<table>
<view>
<datasources>
<datasource caption='Orders+ (Superstore 2)' name='federated.0q9hf1i18nuchx1bfritc1nke7i9' />
</datasources>
<datasource-dependencies datasource='federated.0q9hf1i18nuchx1bfritc1nke7i9'>
<column datatype='string' name='[Category]' role='dimension' type='nominal' />
<column datatype='string' name='[Customer Segment]' role='dimension' type='nominal' />
<column datatype='integer' name='[Profit]' role='measure' type='quantitative' />
<column-instance column='[Category]' derivation='None' name='[none:Category:nk]' pivot='key' type='nominal' />
<column-instance column='[Customer Segment]' derivation='None' name='[none:Customer Segment:nk]' pivot='key' type='nominal' />
<column-instance column='[Profit]' derivation='Sum' name='[sum:Profit:qk]' pivot='key' type='quantitative' />
</datasource-dependencies>
<sort class='alphabetic' column='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk]' direction='ASC' />
<aggregation value='true' />
</view>
<style>
<style-rule element='axis'>
<format attr='height' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[sum:Profit:qk]' value='40' />
</style-rule>
<style-rule element='label'>
<format attr='font-weight' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[sum:Profit:qk]' value='bold' />
<format attr='color' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[sum:Profit:qk]' value='#000000' />
<format attr='font-weight' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Category:nk]' value='bold' />
<format attr='color' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Category:nk]' value='#000000' />
<format attr='font-weight' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk]' value='bold' />
<format attr='color' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk]' value='#000000' />
</style-rule>
<style-rule element='legend-title-text'>
<format attr='color' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk]' value='Customer Segment'>
<formatted-text>
<run bold='true' fontalignment='1'>Customer Segment</run>
</formatted-text>
</format>
</style-rule>
</style>
<panes>
<pane selection-relaxation-option='selection-relaxation-allow'>
<view>
<breakdown value='auto' />
</view>
<mark class='Automatic' />
<encodings>
<color column='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk]' />
</encodings>
</pane>
</panes>
<rows>([federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Category:nk] / [federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk])</rows>
<cols>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[sum:Profit:qk]</cols>
</table>
</worksheet>
<worksheet name='QN 3'>
<layout-options>
<title>
<formatted-text>
<run bold='true' fontalignment='1' fontcolor='#e15759' fontsize='8'>Question 3</run>
</formatted-text>
</title>
</layout-options>
<table>
<view>
<datasources>
<datasource caption='Orders+ (Superstore 2)' name='federated.0q9hf1i18nuchx1bfritc1nke7i9' />
</datasources>
<datasource-dependencies datasource='federated.0q9hf1i18nuchx1bfritc1nke7i9'>
<column datatype='date' name='[Order Date]' role='dimension' type='ordinal' />
<column datatype='string' name='[Region]' role='dimension' type='nominal' />
<column datatype='string' name='[Ship Mode]' role='dimension' type='nominal' />
<column datatype='integer' name='[Shipping Cost]' role='measure' type='quantitative' />
<column-instance column='[Region]' derivation='None' name='[none:Region:nk]' pivot='key' type='nominal' />
<column-instance column='[Ship Mode]' derivation='None' name='[none:Ship Mode:nk]' pivot='key' type='nominal' />
<column-instance column='[Shipping Cost]' derivation='Sum' name='[sum:Shipping Cost:qk]' pivot='key' type='quantitative' />
<column-instance column='[Order Date]' derivation='Quarter-Trunc' name='[tqr:Order Date:qk]' pivot='key' type='quantitative' />
</datasource-dependencies>
<filter class='categorical' column='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Ship Mode:nk]'>
<groupfilter function='union' user:ui-domain='database' user:ui-enumeration='inclusive' user:ui-marker='enumerate'>
<groupfilter function='member' level='[none:Ship Mode:nk]' member='"Express Air"' />
<groupfilter function='member' level='[none:Ship Mode:nk]' member='"Regular Air"' />
</groupfilter>
</filter>
<slices>
<column>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Ship Mode:nk]</column>
</slices>
<aggregation value='true' />
</view>
<style>
<style-rule element='axis'>
<encoding attr='space' class='0' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[tqr:Order Date:qk]' field-type='quantitative' major-origin='#2015-11-16 12:00:00#' major-spacing='1' major-units='quarters' scope='cols' type='space' />
<format attr='subtitle' class='0' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[tqr:Order Date:qk]' scope='cols' value='' />
<format attr='auto-subtitle' class='0' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[tqr:Order Date:qk]' scope='cols' value='true' />
<format attr='height' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[tqr:Order Date:qk]' value='38' />
<format attr='width' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[sum:Shipping Cost:qk]' value='56' />
</style-rule>
<style-rule element='header'>
<format attr='background-color' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[sum:Shipping Cost:qk]' value='#ffffff' />
</style-rule>
<style-rule element='label'>
<format attr='font-weight' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[tqr:Order Date:qk]' value='bold' />
<format attr='color' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[tqr:Order Date:qk]' value='#000000' />
<format attr='font-weight' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[sum:Shipping Cost:qk]' value='bold' />
<format attr='color' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[sum:Shipping Cost:qk]' value='#000000' />
<format attr='font-size' field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[tqr:Order Date:qk]' value='8' />
</style-rule>
</style>
<panes>
<pane selection-relaxation-option='selection-relaxation-allow'>
<view>
<breakdown value='auto' />
</view>
<mark class='Automatic' />
<mark-sizing mark-sizing-setting='marks-scaling-off' />
<encodings>
<color column='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Region:nk]' />
<text column='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Region:nk]' />
</encodings>
<style>
<style-rule element='datalabel'>
<format attr='color-mode' value='match' />
<format attr='font-weight' value='bold' />
</style-rule>
<style-rule element='mark'>
<format attr='size' value='0.93353593349456787' />
<format attr='mark-labels-show' value='true' />
<format attr='mark-labels-cull' value='true' />
</style-rule>
</style>
</pane>
</panes>
<rows>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[sum:Shipping Cost:qk]</rows>
<cols>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[tqr:Order Date:qk]</cols>
</table>
</worksheet>
<worksheet name='QN 4'>
<layout-options>
<title>
<formatted-text>
<run bold='true' fontalignment='1' fontcolor='#79706e' fontsize='8'>Question 4</run>
</formatted-text>
</title>
</layout-options>
<table>
<view>
<datasources>
<datasource caption='Orders (Superstore 2)' name='federated.1632qms1k9dpce1foxool1h7j9kg' />
</datasources>
<mapsources>
<mapsource name='Tableau' />
</mapsources>
<datasource-dependencies datasource='federated.1632qms1k9dpce1foxool1h7j9kg'>
<column datatype='string' name='[City]' role='dimension' semantic-role='[City].[Name]' type='nominal' />
<column datatype='real' name='[Discount]' role='measure' type='quantitative' />
<column datatype='integer' name='[Profit]' role='measure' type='quantitative' />
<column-instance column='[City]' derivation='None' name='[none:City:nk]' pivot='key' type='nominal' />
<column-instance column='[Discount]' derivation='Sum' name='[sum:Discount:qk]' pivot='key' type='quantitative' />
<column-instance column='[Profit]' derivation='Sum' name='[sum:Profit:qk]' pivot='key' type='quantitative' />
</datasource-dependencies>
<filter class='quantitative' column='[federated.1632qms1k9dpce1foxool1h7j9kg].[Latitude (generated)]' included-values='non-null' />
<filter class='quantitative' column='[federated.1632qms1k9dpce1foxool1h7j9kg].[Longitude (generated)]' included-values='non-null' />
<slices>
<column>[federated.1632qms1k9dpce1foxool1h7j9kg].[Latitude (generated)]</column>
<column>[federated.1632qms1k9dpce1foxool1h7j9kg].[Longitude (generated)]</column>
</slices>
<aggregation value='true' />
</view>
<style>
<style-rule element='axis'>
<encoding attr='space' class='0' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[Longitude (generated)]' field-type='quantitative' max='-5398333.6592960507' min='-16372824.248356607' projection='EPSG:3857' range-type='fixed' scope='cols' type='space' />
<encoding attr='space' class='0' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[Latitude (generated)]' field-type='quantitative' max='6385057.8389908141' min='3320110.0168207493' projection='EPSG:3857' range-type='fixed' scope='rows' type='space' />
</style-rule>
<style-rule element='mark'>
<encoding attr='color' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Profit:qk]' max='46595' num-steps='5' symmetric='false' type='custom-interpolated'>
<color-palette custom='true' name='' type='ordered-diverging'>
<color>#ff0000</color>
<color>#fb1616</color>
<color>#f82d2d</color>
<color>#f44242</color>
<color>#f15757</color>
<color>#ed6c6c</color>
<color>#ea7f7f</color>
<color>#e69292</color>
<color>#e3a5a5</color>
<color>#dfb7b7</color>
<color>#dcc8c8</color>
<color>#d9d9d9</color>
<color>#c1d4c1</color>
<color>#aad0aa</color>
<color>#94cc94</color>
<color>#7fc77f</color>
<color>#6ac36a</color>
<color>#56bf56</color>
<color>#44bb44</color>
<color>#31b631</color>
<color>#20b220</color>
<color>#0fae0f</color>
<color>#00aa00</color>
</color-palette>
</encoding>
<encoding attr='size' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Discount:qk]' field-type='quantitative' max='22.350000000000001' max-size='1' min-size='0.0261203' type='rangesize' />
</style-rule>
<style-rule element='table'>
<format attr='omit-on-special' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:City:nk]' value='false' />
<format attr='break-on-special' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:City:nk]' value='false' />
<format attr='show-null-value-warning' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:City:nk]' value='false' />
</style-rule>
<style-rule element='map-layer'>
<format attr='enabled' id='tab_base' value='true' />
<format attr='enabled' id='um_lcover' value='true' />
<format attr='enabled' id='tab_coastline' value='false' />
<format attr='enabled' id='pp2_line' value='false' />
<format attr='enabled' id='light_adm0_bnd' value='false' />
<format attr='enabled' id='light_adm0_lbl' value='false' />
<format attr='enabled' id='um_adm0_bnd' value='true' />
<format attr='enabled' id='um_adm0_lbl' value='true' />
<format attr='enabled' id='light_pp2_statebounds' value='false' />
<format attr='enabled' id='light_pp2_statelabels' value='false' />
<format attr='enabled' id='pp2_adminlabels' value='false' />
<format attr='enabled' id='pp2_statebounds' value='true' />
<format attr='enabled' id='pp2_statelabels' value='true' />
<format attr='enabled' id='countybounds' value='false' />
<format attr='enabled' id='countylabels' value='false' />
<format attr='enabled' id='zipbounds' value='false' />
<format attr='enabled' id='ziplabels' value='false' />
<format attr='enabled' id='tab_areabounds' value='false' />
<format attr='enabled' id='tab_arealabels' value='false' />
<format attr='enabled' id='tab_msabounds' value='false' />
<format attr='enabled' id='tab_msalabels' value='false' />
</style-rule>
<style-rule element='map'>
<format attr='washout' value='0.0' />
</style-rule>
</style>
<panes>
<pane selection-relaxation-option='selection-relaxation-allow'>
<view>
<breakdown value='auto' />
</view>
<mark class='Automatic' />
<mark-sizing mark-sizing-setting='marks-scaling-off' />
<encodings>
<color column='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Profit:qk]' />
<size column='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Discount:qk]' />
<lod column='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:City:nk]' />
</encodings>
<style>
<style-rule element='mark'>
<format attr='size' value='2.5083334445953369' />
<format attr='has-halo' value='false' />
<format attr='has-stroke' value='true' />
<format attr='stroke-color' value='#8cd17d' />
</style-rule>
</style>
</pane>
</panes>
<rows>[federated.1632qms1k9dpce1foxool1h7j9kg].[Latitude (generated)]</rows>
<cols>[federated.1632qms1k9dpce1foxool1h7j9kg].[Longitude (generated)]</cols>
</table>
</worksheet>
<worksheet name='QN 5'>
<layout-options>
<title>
<formatted-text>
<run bold='true' fontalignment='1' fontcolor='#76b7b2' fontsize='8'>Question 5</run>
</formatted-text>
</title>
</layout-options>
<table>
<view>
<datasources>
<datasource caption='Orders (Superstore 2)' name='federated.1632qms1k9dpce1foxool1h7j9kg' />
</datasources>
<mapsources>
<mapsource name='Tableau' />
</mapsources>
<datasource-dependencies datasource='federated.1632qms1k9dpce1foxool1h7j9kg'>
<column datatype='integer' name='[Order Quantity]' role='measure' type='quantitative' />
<column datatype='integer' name='[Shipping Cost]' role='measure' type='quantitative' />
<column datatype='string' name='[State]' role='dimension' semantic-role='[State].[Name]' type='nominal' />
<column-instance column='[State]' derivation='None' name='[none:State:nk]' pivot='key' type='nominal' />
<column-instance column='[Order Quantity]' derivation='Sum' name='[sum:Order Quantity:qk]' pivot='key' type='quantitative' />
<column-instance column='[Shipping Cost]' derivation='Sum' name='[sum:Shipping Cost:qk]' pivot='key' type='quantitative' />
</datasource-dependencies>
<aggregation value='true' />
</view>
<style>
<style-rule element='axis'>
<encoding attr='space' class='0' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[Longitude (generated)]' field-type='quantitative' max='-5482047.4126943741' min='-16498862.735264109' projection='EPSG:3857' range-type='fixed' scope='cols' type='space' />
<encoding attr='space' class='0' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[Latitude (generated)]' field-type='quantitative' max='6311489.360306005' min='3233466.2326727812' projection='EPSG:3857' range-type='fixed' scope='rows' type='space' />
</style-rule>
<style-rule element='mark'>
<encoding attr='color' field='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Shipping Cost:qk]' reverse='true' type='custom-interpolated'>
<color-palette custom='true' name='' type='ordered-diverging'>
<color>#be682b</color>
<color>#c27945</color>
<color>#c78a60</color>
<color>#cb9d7c</color>
<color>#d0b09a</color>
<color>#d4c4b9</color>
<color>#d9d9d9</color>
<color>#b8c4d0</color>
<color>#99b1c7</color>
<color>#7d9fbf</color>
<color>#628db6</color>
<color>#497dad</color>
<color>#336ea5</color>
</color-palette>
</encoding>
</style-rule>
<style-rule element='map-layer'>
<format attr='enabled' id='tab_base' value='true' />
<format attr='enabled' id='um_lcover' value='true' />
<format attr='enabled' id='tab_coastline' value='false' />
<format attr='enabled' id='pp2_line' value='false' />
<format attr='enabled' id='light_adm0_bnd' value='false' />
<format attr='enabled' id='light_adm0_lbl' value='false' />
<format attr='enabled' id='um_adm0_bnd' value='true' />
<format attr='enabled' id='um_adm0_lbl' value='true' />
<format attr='enabled' id='light_pp2_statebounds' value='false' />
<format attr='enabled' id='light_pp2_statelabels' value='false' />
<format attr='enabled' id='pp2_adminlabels' value='false' />
<format attr='enabled' id='pp2_statebounds' value='true' />
<format attr='enabled' id='pp2_statelabels' value='true' />
<format attr='enabled' id='countybounds' value='false' />
<format attr='enabled' id='countylabels' value='false' />
<format attr='enabled' id='zipbounds' value='false' />
<format attr='enabled' id='ziplabels' value='false' />
<format attr='enabled' id='tab_areabounds' value='false' />
<format attr='enabled' id='tab_arealabels' value='false' />
<format attr='enabled' id='tab_msabounds' value='false' />
<format attr='enabled' id='tab_msalabels' value='false' />
</style-rule>
<style-rule element='map'>
<format attr='washout' value='0.0' />
</style-rule>
</style>
<panes>
<pane selection-relaxation-option='selection-relaxation-allow'>
<view>
<breakdown value='auto' />
</view>
<mark class='Multipolygon' />
<encodings>
<color column='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Shipping Cost:qk]' />
<text column='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Order Quantity:qk]' />
<lod column='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:State:nk]' />
<geometry column='[federated.1632qms1k9dpce1foxool1h7j9kg].[Geometry (generated)]' />
</encodings>
<customized-label>
<formatted-text>
<run bold='true' fontcolor='#ffffff' fontsize='8'><</run>
<run bold='true' fontcolor='#ffffff' fontsize='8'>[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Order Quantity:qk]</run>
<run bold='true' fontcolor='#ffffff' fontsize='8'>></run>
</formatted-text>
</customized-label>
<style>
<style-rule element='mark'>
<format attr='mark-labels-show' value='true' />
<format attr='mark-labels-cull' value='true' />
</style-rule>
</style>
</pane>
</panes>
<rows>[federated.1632qms1k9dpce1foxool1h7j9kg].[Latitude (generated)]</rows>
<cols>[federated.1632qms1k9dpce1foxool1h7j9kg].[Longitude (generated)]</cols>
</table>
</worksheet>
</worksheets>
<dashboards>
<dashboard name='Dashboard 1'>
<style />
<size maxheight='768' maxwidth='1366' minheight='768' minwidth='1366' preset-index='0' sizing-mode='fixed' />
<zones use-insets='false'>
<zone h='100000' id='2' type='layout-basic' w='100000' x='0' y='0'>
<zone h='97916' id='21' param='horz' type='layout-flow' w='98828' x='586' y='1042'>
<zone h='97916' id='19' type='layout-basic' w='98828' x='586' y='1042'>
<zone h='64453' id='13' param='horz' type='layout-flow' w='98828' x='586' y='1042'>
<zone h='64453' id='9' param='horz' type='layout-flow' w='98828' x='586' y='1042'>
<zone h='64453' id='5' param='horz' type='layout-flow' w='98828' x='586' y='1042'>
<zone h='64453' id='3' type='layout-basic' w='98828' x='586' y='1042'>
<zone h='29358' id='1' name='QN 1' show-title='false' w='50439' x='586' y='1042'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='29358' id='7' name='QN 2' show-title='false' w='48389' x='51025' y='1042'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='25399' id='11' name='QN 4' show-title='false' w='49415' x='586' y='34907'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='25399' id='16' name='QN 5' show-title='false' w='49413' x='50001' y='34907'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='5189' id='14' name='QN 4' pane-specification-id='0' param='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Profit:qk]' type='color' w='32723' x='586' y='60306'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='5189' id='15' name='QN 4' pane-specification-id='0' param='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Discount:qk]' type='size' w='16692' x='33309' y='60306'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='5189' id='17' name='QN 5' pane-specification-id='0' param='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Shipping Cost:qk]' type='color' w='49413' x='50001' y='60306'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='4507' id='10' name='QN 2' pane-specification-id='0' param='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk]' type='color' w='49413' x='50001' y='30400'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='4507' id='6' name='QN 1' pane-specification-id='0' param='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Segment:nk]' type='color' w='49415' x='586' y='30400'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
</zone>
</zone>
</zone>
</zone>
<zone h='33463' id='18' name='QN 3' show-title='false' w='98828' x='586' y='65495'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
</zone>
</zone>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='8' />
</zone-style>
</zone>
<zone h='14193' id='22' name='QN 3' pane-specification-id='0' param='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Region:nk]' type='color' w='10249' x='91947' y='65234'>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone forceUpdate='true' h='5469' id='23' type='text' w='7906' x='2196' y='34505'>
<formatted-text>
<run bold='true' fontcolor='#000000' underline='true'>QN 4</run>
</formatted-text>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone forceUpdate='true' h='5469' id='24' type='text' w='7906' x='90410' y='34115'>
<formatted-text>
<run bold='true' fontalignment='2' fontcolor='#000000' underline='true'>QN 5</run>
</formatted-text>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='5469' id='25' type='text' w='7906' x='25256' y='-911'>
<formatted-text>
<run bold='true' fontcolor='#000000' underline='true'>QN 1</run>
</formatted-text>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='5469' id='26' type='text' w='7906' x='71230' y='-391'>
<formatted-text>
<run bold='true' fontalignment='1' fontcolor='#000000' underline='true'>QN 2</run>
</formatted-text>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
<zone h='5469' id='27' type='text' w='7906' x='47657' y='66276'>
<formatted-text>
<run bold='true' fontcolor='#000000' underline='true'>QN 3</run>
</formatted-text>
<zone-style>
<format attr='border-color' value='#000000' />
<format attr='border-style' value='none' />
<format attr='border-width' value='0' />
<format attr='margin' value='4' />
</zone-style>
</zone>
</zones>
</dashboard>
</dashboards>
<windows source-height='51'>
<window class='worksheet' name='QN 1'>
<cards>
<edge name='left'>
<strip size='160'>
<card type='pages' />
<card type='filters' />
<card type='marks' />
</strip>
</edge>
<edge name='top'>
<strip size='2147483647'>
<card type='columns' />
</strip>
<strip size='2147483647'>
<card type='rows' />
</strip>
<strip size='31'>
<card type='title' />
</strip>
</edge>
<edge name='right'>
<strip size='160'>
<card pane-specification-id='0' param='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Segment:nk]' type='color' />
</strip>
</edge>
</cards>
<viewpoint>
<highlight>
<color-one-way>
<field>[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Category:nk]</field>
<field>[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Name:nk]</field>
<field>[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Segment:nk]</field>
</color-one-way>
</highlight>
</viewpoint>
</window>
<window class='worksheet' name='QN 2'>
<cards>
<edge name='left'>
<strip size='160'>
<card type='pages' />
<card type='filters' />
<card type='marks' />
</strip>
</edge>
<edge name='top'>
<strip size='2147483647'>
<card type='columns' />
</strip>
<strip size='2147483647'>
<card type='rows' />
</strip>
<strip size='31'>
<card type='title' />
</strip>
</edge>
<edge name='right'>
<strip size='160'>
<card pane-specification-id='0' param='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk]' type='color' />
</strip>
</edge>
</cards>
<viewpoint>
<highlight>
<color-one-way>
<field>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Category:nk]</field>
<field>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk]</field>
</color-one-way>
</highlight>
</viewpoint>
</window>
<window class='worksheet' name='QN 3'>
<cards>
<edge name='left'>
<strip size='133'>
<card type='pages' />
<card type='filters' />
<card type='marks' />
</strip>
</edge>
<edge name='top'>
<strip size='2147483647'>
<card type='columns' />
</strip>
<strip size='2147483647'>
<card type='rows' />
</strip>
<strip size='31'>
<card type='title' />
</strip>
</edge>
<edge name='right'>
<strip size='100'>
<card pane-specification-id='0' param='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Region:nk]' type='color' />
</strip>
</edge>
</cards>
<viewpoint>
<highlight>
<color-one-way>
<field>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Region:nk]</field>
<field>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Ship Mode:nk]</field>
<field>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[qr:Order Date:ok]</field>
<field>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[tqr:Order Date:qk]</field>
<field>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[yr:Order Date:ok]</field>
</color-one-way>
</highlight>
</viewpoint>
</window>
<window class='worksheet' name='QN 4'>
<cards>
<edge name='left'>
<strip size='160'>
<card type='pages' />
<card type='filters' />
<card type='marks' />
</strip>
</edge>
<edge name='top'>
<strip size='2147483647'>
<card type='columns' />
</strip>
<strip size='2147483647'>
<card type='rows' />
</strip>
<strip size='31'>
<card type='title' />
</strip>
</edge>
<edge name='right'>
<strip size='160'>
<card pane-specification-id='0' param='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Profit:qk]' type='color' />
<card pane-specification-id='0' param='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Discount:qk]' type='size' />
</strip>
</edge>
</cards>
</window>
<window class='worksheet' name='QN 5'>
<cards>
<edge name='left'>
<strip size='160'>
<card type='pages' />
<card type='filters' />
<card type='marks' />
</strip>
</edge>
<edge name='top'>
<strip size='2147483647'>
<card type='columns' />
</strip>
<strip size='2147483647'>
<card type='rows' />
</strip>
<strip size='31'>
<card type='title' />
</strip>
</edge>
<edge name='right'>
<strip size='160'>
<card pane-specification-id='0' param='[federated.1632qms1k9dpce1foxool1h7j9kg].[sum:Shipping Cost:qk]' type='color' />
</strip>
</edge>
</cards>
</window>
<window class='dashboard' maximized='true' name='Dashboard 1'>
<viewpoints>
<viewpoint name='QN 1'>
<highlight field='[federated.1632qms1k9dpce1foxool1h7j9kg].[none:Customer Segment:nk]'>
<bucket-selection />
</highlight>
</viewpoint>
<viewpoint name='QN 2'>
<highlight field='[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Customer Segment:nk]'>
<bucket-selection />
</highlight>
</viewpoint>
<viewpoint name='QN 3'>
<zoom type='entire-view' />
<highlight>
<color-one-way>
<field>[federated.0q9hf1i18nuchx1bfritc1nke7i9].[none:Region:nk]</field>
</color-one-way>
</highlight>
</viewpoint>
<viewpoint name='QN 4'>
<zoom type='entire-view' />
</viewpoint>
<viewpoint name='QN 5'>
<zoom type='entire-view' />
</viewpoint>
</viewpoints>
<active id='11' />
</window>
</windows>
<thumbnails>
<thumbnail height='192' name='Dashboard 1' width='192'>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</thumbnail>
<thumbnail height='192' name='QN 1' width='192'>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</thumbnail>
<thumbnail height='192' name='QN 2' width='192'>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</thumbnail>
<thumbnail height='192' name='QN 3' width='192'>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==
</thumbnail>
<thumbnail height='192' name='QN 4' width='192'>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</thumbnail>
<thumbnail height='192' name='QN 5' width='192'>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</thumbnail>
</thumbnails>
</workbook>