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shuijian-xu / hive

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The need to monitor churn and to establish the reasons for it tends to create a need for queries that return results in the form of a time series. The following exemplifies the type of questions we would like to express #39

Open shuijian-xu opened 5 years ago

shuijian-xu commented 5 years ago

How many customers did we lose during the last quarter of 2000, compared to 1999 and 1998?

The result of such a query would be a time series containing three periods and a number attached to each period. This is an example of a temporal selection query.

shuijian-xu commented 5 years ago

Of the customers who were lost, how many had been customers continuously for at least one year?

The loss of long-standing customers might be considered to be as a result of worsening service. The result from this question is also a time series, but the query contains an examination of durations of time. So this query is a state duration query.

shuijian-xu commented 5 years ago

How many of these customers experienced a change of administration because they moved in the year that they left?

Perhaps they are unhappy with the level of service provided by the new area. This question is concerned with the existence of the relationship between the customer and the sales area. It is also an example of a transition detection query.

shuijian-xu commented 5 years ago

How many price changes did they experience in the year that they left?

Perhaps they were unhappy with the number of price rises imposed. This is similar to question 3 in that it is a transition detection query, but it is applied to the value of an attribute, in this case the selling price of a bottle of wine, instead of a relationship.