One of the key takeaways from my first week was understanding the importance of planning before beginning analysis. While it can be tempting to immediately explore and manipulate data, effective analytics depends on first understanding the business problem, and identifying the appropriate level of detail required for analysis. Planning step helps narrow down the specific data needed for the analysis and prevents time being wasted on unnecessary or repeated work.
Example
One table contains sales value information, while another contains product information where multiple products could belong to a single order.
The total sales value is 300.
After joining the Sales and Product tables, the sales values are duplicated, causing the total sales figure to increase from 300 to 600.
This example demonstrated how failing to consider table relationships and level of detail can result in misleading analysis.
Hope this example provides an understanding of why planning is essential for producing accurate and reliable analysis.
Successful analytics begins long before the analysis itself. Careful planning, understanding data structure, and considering the level of detail are essential steps in producing meaningful and reliable insights.