Business reporting is key to understanding customers, opportunities, and investments including marketing and product development. Most companies have tons of raw data from across the organization – and exceptional insights are possible when this data can be connected and correlated.
Data transformation is process of converting raw data into a format that is suitable for analysis and modeling. Often this is used to unite separate data sources in a common reporting database for use with visualization tools such as Tableau, Power BI, and Looker.
The goal of data transformation is to prepare the data so that it can be used to extract useful insights and knowledge. Data transformation requires multiple steps, including:
- Data cleaning: Removing or correcting errors, inconsistencies, and missing values in the data.
- Data integration: Combining data from multiple sources, such as databases and spreadsheets, into a single format.
- Data normalization: Scaling the data to a common range of values, to facilitate comparison and analysis.
- Data reduction: Reducing the dimensionality of the data by selecting a subset of relevant features or attributes.
- Data aggregation: Combining data at different levels of granularity, such as by summing or averaging, to create new features or attributes.
Data transformation is a key step in business reporting. It ensures that the data is in a format that is suitable for analysis and modeling, and that it’s free of errors and inconsistencies.
There are a large variety of tools for data transformation: Google, Microsoft, Oracle, and Amazon have powerful cloud based tools. And there are many more exceptional products that can be used.
Contact us if you want help transforming your data for better business reporting. Our team has decades of experience making it happen.
