Post by account_disabled on Nov 26, 2023 1:30:29 GMT -7
It is indeed good to collect a lot of information and create analyzes based on it but there must be meaning and purpose in everything. It is normal that not all prepared analyzes will be equally useful and some may even disturb correct conclusions. It all depends on the purpose of their preparation and on the ability to analyze and interpret this data. Without advanced analytical competences and preparation of appropriate analyses it may be difficult to draw the right conclusions. There are of course strategies that assume that since we have a lot of data we create a lot of analyzes based on it.
A more optimal solution is to prepare analyzes for specific actions. Therefore we select data depending on the specific purpose of the analysis. For example to draw conclusions about the effectiveness of marketing Email Marketing List campaigns we will need analyzes of sales during the campaign online advertising and customer analyzes which customers bought which goods. However to forecast the number of orders for new goods to the warehouse we need an analysis of sales dynamics for the same period last year an analysis of competitors' sales and a weather analysis telling us whether it will be warm whether it will rain etc.
In this situation we do not need customer and shipment analyzes to order the right goods. Therefore it is worth considering whether it makes sense to waste time and prepare analyzes exaggeratedly because we have the time or idea or to simply prepare the analysis only after knowing the goal. Third data cleansing Once we know which data constitutes the basis for our considerations regarding further business steps and which are extra and ultimately need to be treated as secondary or excluded from the database altogether tough enforcement should be used.
A more optimal solution is to prepare analyzes for specific actions. Therefore we select data depending on the specific purpose of the analysis. For example to draw conclusions about the effectiveness of marketing Email Marketing List campaigns we will need analyzes of sales during the campaign online advertising and customer analyzes which customers bought which goods. However to forecast the number of orders for new goods to the warehouse we need an analysis of sales dynamics for the same period last year an analysis of competitors' sales and a weather analysis telling us whether it will be warm whether it will rain etc.
In this situation we do not need customer and shipment analyzes to order the right goods. Therefore it is worth considering whether it makes sense to waste time and prepare analyzes exaggeratedly because we have the time or idea or to simply prepare the analysis only after knowing the goal. Third data cleansing Once we know which data constitutes the basis for our considerations regarding further business steps and which are extra and ultimately need to be treated as secondary or excluded from the database altogether tough enforcement should be used.