For consistent seasonal sales analysis, which steps should a retail company take in SAP Analytics Cloud?

For a retail company seeking to perform consistent seasonal sales analysis, applying data quality rules is essential. Data quality rules help ensure that the data being analyzed is accurate, complete, and reliable. In the context of seasonal sales, where trends and patterns are scrutinized for strategic decision-making, any discrepancies or errors in the data can lead to misguided insights.

Establishing robust data quality rules can involve validating the data against defined standards, checking for inconsistencies, and ensuring that the data aligns with the expected formats and values. This process is crucial as it guarantees that the sales data reflects true performance across different seasons, enabling the company to make well-informed projections, identify trends, and devise effective marketing strategies.

While other options like data blending, data versioning, and data enrichment have their importance in the data handling process, they do not directly address the need for accuracy and reliability in the data, which is fundamental for a consistent analysis of seasonal sales. Data blending focuses on integrating data from various sources, data versioning tracks changes in datasets, and data enrichment augments datasets with additional information—none of these steps directly ensures the integrity of the data used for analysis in the same way that applying data quality rules does.