Adopting a product (vs a project) approach to data management

Let’s face it: When it comes to data, most companies are project-driven.??

For example, if a business domain requires certain data to address a particular need, it typically opens a ticket with IT or the relevant data team. This usually represents a “project” to identify, collect, prepare, and deliver the relevant dataset to the data consumer. This same pattern is typically followed every time a new need emerges for data in the organization.?

This “data as a project” approach has obvious drawbacks, such as slow time-to-delivery, no reusability, rigidity, and the risk of delivering faulty, or incomplete, data.?

On the other hand, a “data as a product” approach assumes that data is a reusable data asset that must deliver the desired value for data consumers. Data products can support any number of use cases, and serve any number and variety of data consumers – so long as they have the right access rights.

A project-driven approach to data is complex, one-off, and produces no reusable assets.?A product-driven approach is simpler, cyclical, and produces reusable data products.?

Advantages of Data Products ?

Over time, data products deliver better ROI, and cost-per-use, than data projects. From the perspective of a data consumer, data products offer:?

• Quicker time-to-insight, using pre-built data products (instead of having to initiate a new project)?
• Full data integrity, with trusted datasets that are always in sync?
• Situational awareness, where the data is augmented with real-time insights?
• Real-time response times, for operational use cases, when timely and informed decision-making is of the essence?
• Data governance, for high-quality, compliant datasets every time?
• Total accessibility, with easily discoverable and instantly available information?

Read more about data products (vs projects), and the emerging role of data product managers, in the full article.?