Data Products

Paradigm shift from data provision to consumption

Data products package relevant data for consumers

Viewing information or data as a product has become a popular way to address the increasing demand for data and analytics, but most importantly it introduces a paradigm shift – from data provision to data consumption and value generation. Industry reports highlight that data products can help deliver new business use cases 90% faster while reducing risks and data-governance burden. In the Data Mesh concept, data as a product is one of the key principles to decentralize data and analytics, and to ensure “…data quality, decreased lead time of data consumption, and data user satisfaction…”

Data Products Keyvisual
Definition

What is a data product?

A data product is a managed artifact which satisfies recurring information needs and creates value through transforming and packaging relevant data elements into a consumable form.
(Competence Center Corporate Data Quality (CC CDQ) definition)

Characteristics of data products

In practice, it is not easy to distinguish data products from data assets or data sets. Researchers at the CC CDQ have developed a definition and identified five characteristics of data products.

5_characteristics_dataproducts
Categories of data products

How to build a portfolio of data products

We have ascertained there are three categories of data products, that build upon each other, each having distinct value propositions:
 

  • BASIC DATA PRODUCTS – Allow consumers to gain in-depth understanding and knowledge of the domain that the data represents.
    Examples comprise enriched or curated datasets around an organization’s customers, products or employees that are frequently used for operational and analytical purposes.
  • ANALYTICAL DATA PRODUCTS – Deliver key insights using basic analytics to support manual decision making.
    Examples include KPIs, reports or dashboards.
  • ADVANCED ANALYTICAL DATA PRODUCTS – Use data science methods to create prescriptive acumen and offer self-learning capabilities.
    Examples are trained AI/ML models or recommender systems.

 

Categories of data products

Why implement data products, and what to focus on

Researchers at the CC CDQ have identified three key motivations driving data product implementations, which are mapped to the foci of the initiatives:

Data product implementations
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Reading

Viewing information or data as a product has become a popular way to address the increasing demand for data and analytics, but most importantly it introduces a paradigm shift – from data  provision to data consumption and value generation. In practice, it is not easy to distinguish data products from data assets or data sets. 

C CDQ Research Briefing Data Products
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Worksheet

The CC CDQ Data Product Canvas is designed to get a more comprehensive product perspective on data. This visual inquiry tool supports cross-functional teams in understanding, designing, and analyzing Data Products. The canvas is the first step toward a systematic approach and shared language in designing Data Products in ways that technical experts and business users understand. 

CC CDQ-Data-Product-Canvas
Recording
Webinar

In this webinar, you will get an overview of data products and learn how to succeed in a data products journey. You will understand, why your organization should pursue data product thinking, discover different types of data products and their characteristics and learn how to design and manage data products. 

Recording Data Product Webinar
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