In the previous post, you have learnt how to perform ABC analysis/Pareto analysis using the DSUM function. By now, after reading that post you must have realised that there were no product categories in the previous data – as a result of which all the SKUs (regardless of their product categories) that contributed to top 80% of the sales were classified as A class items. Now, it is quite possible that a particular SKU could have sales not in the top 80% of the overall sales but in the top 80% of the category sales that it belongs to. In order words, you would want each categories to have its own A , B & C Class SKUs. This requirement is a simple extension of the following two posts:
Let us see how…
In this post, you will be learning to perform ABC analysis using the DSUM() function. There are instances when a small percentage of causes in your business lead to a large percentage of impacts – meaning that drawing your focus on these small percentages of causes could help you have better control over the large percentage of impacts.
Now, Let us understand how we can use the DSUM() function that we have already learnt to perform ABC/Pareto Analysis….
As you have seen in the previous post, you can easily create a running total on a given set of data. A slight modification can be added to this by making MS Access re-start the running total at certain point as decided by you.
In this post, you’ll learn how to do so….
While analysing data, there are many instances when you need to create a running total (also known as a ‘Cumulative Sum’). In this post, you will learn to create a running total using MS Access Query. Actually, if you know how a DSUM() function works, then creating a running total is very easy.
Let’s see how we can use this MS Access function to create a running total using just a query design grid.
In this post, you’ll learn to solve a specific query raised by one of our reader. The query is as follows:
Lets see how to solve this..
In this post, you’ll learn to work with DSUM() function with date as a criteria. It is very similar to the way you create the text criteria with the only exception being the delimiters used. In case of dates, you’ll use hash (#) as a delimiter instead of a single quote (‘ ‘) that you use in case of text values.
The date criteria enables you to extract data within a particular time period or before/after a certain date as explained in this post…