There are 100 machines in a factory. Every machine has different test frequency. In a given month, not every machine is tested but we still have the last known rating (from some previous month) of that machine. We have to show the latest rating of each machine for each month in a stacked column chart. […]
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In this simple 3 column dataset, there are 2 accounts – Konto 1 and Konto 2. Each account has a balance outstanding as on a certain date. However, if you notice carefully, there is no balance for any account on January 4-5,9-10 2020. The objective is show the balance outstanding every day. For days which […]
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Assume a simple 4 column dataset as shown below. This data shows which ID had which type of subscription in which year. So ID A, which started as a “Free” subscriber in 2018 switched to a “Premium” subscriber in 2019 and then churned out in 2020. Likewise, ID D which started as a “Pro” subscriber […]
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In the value area section of a normal Pivot Table one can only show the result of aggregation functions such as SUM(), COUNT(), AVERAGE() etc. Even if one drags a text field to the value area section of a Pivot Table, one cannot show those text fields because they automatically get counted. Consider the following […]
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Assume a simple 3 column dataset as shown below – the date of each task and the status of that task. The objective is to get the status wise count of tasks by the last time stamp. So for the Status “To-do”, the count should be 2 – Task ABC and DEF. Only these two […]
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Assume a simple dataset as shown in the image below (the input data is in columns A and B only. The desired outcome is in columns C and D). The objective is to calculate the 7 days rolling sum and average (as shown in columns C and D) ignoring blank cells. So in cell C8, […]
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Here’s a simple 3 column dataset showing Date, ID and Status – the status of each ID by Date. So, the narrative for ID A is: It was “New” on Jan 1 It remained “New” until Jan 14 On Jan 15, the status changed to “Open” It remained “Open” till Jan 31 and the status […]
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Consider a 4 column table – Respondent ID, Device ID, App Name and Category. So this dataset shows which apps are installed on which device ID by which user and which category do the apps fall into. It is a small dataset with only 4 columns and 2,000 rows. The question on this dataset is […]
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Here is a Sales dataset of 8 columns and 29 rows. It basically details the revenue earned and cash collected by service type, Customer, Country and Period. For a selected Country and time period, there could be customers availing of both services or of any 1 service. There are 2 broad questions that one may […]
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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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Determine latest condition of each equipment and show a month wise count
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