What are the Stages in Data Manager?

Assets Data Manager helps teams to ensure data is complete, current and correct.

Data Manager works by moving through a series of steps that progressively improve the quality of your data and reconcile multiple data sources to create a single, trustworthy source of truth - also commonly known as a golden record.

Data Stages

The steps that Data Manager moves through are called the Data Stages.

There are five Data Stages:

1. Move data from a file, database, or tool into Data Manager to create Raw Data.

2. Remove unwanted values and characters to create Transformed Data.

3. Eliminate records that are stale, null, or unneeded to create Cleansed Data.

4. Reconcile multiple data sources down to create Data Manager Objects (golden records).

5. Import your objects into an Assets Schema to create Schema Objects.

Configuring, running, and reviewing

Depending on your team (and the tools they are using), configuring and testing of these Data Stages may be very simple, or it may involve reviewing and iterating the results with different stakeholders to ensure accuracy and completeness.

This is why we encourage teams to use Data Manager in an iterative way for each Data Stage, by:

1. Configuring the features within Data Manager for each Data Stage.

2. Running an operation to change the data.

3. Reviewing the changed data with stakeholders and subject matter experts (SMEs).

How to use Data Manager

Here’s a breakdown of how we encourage teams to use Data Manager - by configuring, running, and reviewing for each Data Stage.

We encourage teams to go through this process separately for each individual data source because certain operations such as Cleansing and Importing cannot be performed while there is still unmapped data in any other data source.

If the data doesn’t look how it should, it’s always possible to modify your data by changing the configuration options and running the operation again.

Once things look good, it’s on to the next stage!