Archive for September, 2018

Rearrange travel data to clearly show travel from and travel to locations

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Consider a 2 column dataset as shown below User Location AAA Tokyo AAA Osaka AAA Nagoya AAA Hakone AAA Kyoto BBB Sapporo BBB Nara CCC Tokyo CCC Hakone CCC Osaka DDD Osaka DDD Tokyo Customer AAA travelled from Tokyo to Osaka, Osaka to Nagoya, Nagoya to Hakone and Hakone to Kyoto.  All locations appear in […]

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Identify Customers that Organisations can upsell or cross sell their products to

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Here’s a simple Sales data of a retail Store which sells Apple Products.  Since a customer can transact multiple times, there will be repetitions in the Cust ID column.  While Cust ID 123 and 782 purchased multiple products from the same Store in one transaction, Cust ID 53 purchased multiple products from different stores (Store […]

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