On-Demand Content

Data Maturity: How to Evolve and Future Proof your DAM for the Digital Ecosystem

What is Data Maturity? For DAM,  it’s mostly about:

• Understanding the larger context of the data ecosystem and its key dependencies
• Identifying measures of what constitutes success and then achieving those targets

We are inundated with data and, if not properly curated, this deluge can quickly turn to noise. 

In this course, we provide a step-by-step guide on how to keep your DAM data healthy, usable, actionable and measurable. 

The four part series introduces the ways to manage data proliferation by providing steps for continuous improvement, guideposts for identifying dependencies, and help on positioning the DAM for future automation and personalisation.

• Four detailed sessions exploring how to position data for omnichannel/cross channel distribution
• Sessions are available online in self paced modules
• Teaching by Taxonomy and Metadata expert Madi Weland Solomon
• Each session is 75 minutes, including 25 minutes of Madi answering participants' questions on challenges they have faced

Pricing

Fees for the 4 part course in US Dollars: $299. Click here to register

Fees for the 4 part course in Pound Sterling: £235 +VAT. Click here to register

About the series

This is an intermediate level course for Managers who are interested in taking their DAM to the next level.

This course would target ambitious DAM Managers who understand that the DAM is only one platform in a domain of many that need to be coordinated. This DAM manager is beginning to understand the dependencies in their digital ecosystem and understands that they may want to integrate with their PIM system for product data, their campaign development workflow, and/or their Customer Data Platform. 

The DAM manager may also be asked by their executive teams to automate metadata, but don't know how or where to begin. This course will help them understand the full breadth of their DAM data and, depending on their current state, a place to begin making plans for automation. This might include a data cleanse following an audit (which metadata is never used, which metadata is the most important), refining their taxonomy or controlled vocabularies, and exploring AI image recognition software available in their DAM.

Schedule​

• Session 1: Data Maturity: Playing well with others
• Session 2: Maintaining Relevance: Keeping data relevant and useful for you and for others
• Session 3: Data Audits: Know your data
• Session 4:  Measuring DAM ROI 

You can view the full course summary here.