Assume a dataset with two columns which lists down the student names in column A and courses opted for in column B. Since one student can opt for multiple courses and the same course can be taken up by multiple students, there can be repetitions in both columns. The objective is to create a matrix […]
Read More →
{ 0 Comments }
Assume a two column dataset with Date in the first column and Price in the second one. The purpose is to identify times to buy and sell – buying would be just after the lowest low is confirmed and sell before or just after the highest high is in place. Confirmation is achieved through crossover of […]
Read More →
Assume there are four interrelated tables. One may want to create a pivot that allows one to filter data by using the slicers. Data should be filtered by the following interdependent slicers selections: Customer, Country and segment. The logic behind the pivot when using the slicers shall be as follows: 1. Feature N is only shown if relevant to Customer X in Segment […]
Read More →
Scenario 1 In a Stock Broking business (Firm), Customers deposit margin money through cheques. Although cheques are received from customers at branches, clearing (realization) of the same normally takes 3-4 days. On one hand, the Firm wishes to allow trading to the customers against the deposited cheques from the day it receives the cheque, on other hand there is […]
Read More →
{ 0 Comments }
Assume a five column dataset – ID, Age, Gender, Time and Class. For chosen ID’s, the objective is to: 1. Assign a Rank (in ascending order of time i.e. lowest time will be rank 1 and so on) to each ID 2. Determine the overall place of each ID – Count of unique time entries […]
Read More →
{ 0 Comments }
Assume a three column dataset which has Year, Company ID and Cash flows. For each Company, there are cash flows for multiple years. So for Company ID A001, there are 7 rows, one each for 2010 to 2004 and cash flows appearing in a third column. Let’s assume the number of rows are 750,000. The task is to compute […]
Read More →
{ 0 Comments }
Assume a three column dataset showing Audit ID, Date of receipt of audit mandate and Date of audit completion. There are other columns as well but they are not important for our Analysis. One may want to compute the following month wise: 1. Which (Audit ID) are the audits pending at the end of every […]
Read More →
Assume a simple three column dataset showing hours worked by different machine on different dates. So column A is Date, column B is Machine Name and column C is hours worked. There are duplicates appearing in column A and B . Blanks in column C depict machine idle time. The task is to create a simple […]
Read More →
{ 30 Comments }
Visualise Sales Data of a Non-Alcoholic Beverage Company with basic columnar information such as Date of Sale, Time of Sale, Brand, Stock Keeping Unit (SKU), State, City, Quantity sold, Unit Price and Salesman Code. In this sales dataset, each line item represents one visit for one SKU. If nothing is sold in a certain visit, then the SKU […]
Read More →
Visualise a Pivot Table with a few Fields dragged in the Report filter, Row labels and Value Area section. In the Column labels are two fields, Month and then Year – so in the column labels, for every month, there is data for three years 2005, 2006 and 2007. For some months, there is data […]
Read More →
Quantify combination courses opted by students
{ 0 Comments }