Managing external data is challenging. Local markets want local data, different data suppliers structure their data in their own way, and it doesn’t match in-house data. So how do you deliver a global picture amidst all this fragmentation?

For many organizations, managing external data has become a huge manual collation task – one that takes so much effort that its often only done to respond to high priority ad-hoc analyses. But think of the potential for accessing this aligned data at any time, being able to respond quickly to short-term imperatives or use external data as part of your standard analytics reviews.

During this recorded we present a case study carried out for a major manufacturer to set up a data repository to collate all of their local external data, including Nielsen, Ipsos MORI and others, into a single dataset with common terminology. We show how the process was fully automated to deliver a powerful dataset of combined internal and external data, along with a golden source of product master data.

What we cover:

• Aligning disparate local sources into a single data model
• Automating processes for linking data
• Use of machine learning techniques to assist mapping data
• Developing a product master from internal and external data

Is it for you?

• Are you starting on an external data journey and looking to understand how best to manage it?
• Are you struggling to process external data in a practical timeframe?
• Are you spending too much time and resources to get the job done?
• Do you want to overcome the disconnect between internal and external data?