Data enrichment is designed to improve, enhance, and refine data. How can you streamline and speed up data enrichment, so you can get to insights faster?

What is data enrichment?

In order to make data-driven decisions, you need data you can rely on. Data enrichment is the process of cleaning up the raw data and enriching it with information from disparate data (which comes from both internal and external systems) to create one accurate, error-free data set, with proper tags and codes, to be consumed as a single source of truth.

The challenges of enriching marketing data

As with other steps of the data engineering process, enrichment for marketing data poses unique challenges, including:

• Large number of variables: data structure changes significantly over time; for example, survey data might have a different number of columns each month, with different types of data in each column from month to month
• Increasing number of data providers, each with unique formats and metrics
• Velocity of data: 24/7 social media, streaming data, and other sources make it difficult to keep up
• Complexity of data: from weighted surveys to inconsistent brand names, marketing data requires expert attention for accurate enrichment