Introduction to Data Management

What is Data Management?

In Loops, Data Management is a semantic layer that allows you to define and manage your data using common business terms, which can then be used in Loops analyses.

You can access the Data Management page by logging into Loops and clicking “Data Management” at the bottom of the left-side navigation bar. Once you do, there are two sections for managing your data:

1. “Raw Data” provides the foundation for your data management.
   • Views is where you map data that exists in your database or data warehouse to virtual tables, thus enabling use of this data within Loops.
   • Events is where you see all of the raw events that have been written to your database or data warehouse and included in your views.
2. “Data Modeling” is where you create data objects based on the views you have created. This includes:
   • KPIs
   • Segments
   • Features
   • Content
   • Funnels
   • Event Groups
   • Milestones

Why is Data Management important?

Data Management is all about structuring your data, which is what allows Loops to interpret and analyze your data and yield better insights. Here are a few key benefits to structuring your data within Loops:

• It allows you to define the data objects you’d like to focus on in your analyses (e.g. Segment, Order Amount, Churn Status).
• You can define data objects and thereby align your team on data definitions. For example, “2nd-week retention” can have multiple meanings. By defining it in Data Management, you can ensure everyone is referring to the exact same KPI.
• It saves time when attempting to retrieve and analyze information. For example: upon defining a common funnel within your product, you can simply use the Funnel data object whenever you want to include that funnel in an analysis.
• Not structuring your data can lead to suboptimal insights. For example: although Loops can analyze raw events even if you don’t define the features of your product, the data will be noisy and lead to inferior insights.