Getting Started with Data Products
Are you looking to get more value out of your organization’s data? Chances are, your answer is a resounding “yes!” But if you are like many data leaders we talk to, you may not know how to generate more value – or even where to begin. The good news is, you’ve come to the right place.
We believe that implementing a data product strategy through the design and use of a data product is the best way to get more value from your organization’s data. And to help you get started, we’ve created a guide that:
- Defines what a data product is and why you need one
- Identifies the key principles and capabilities that make up a good product
- Provides a list of steps you can follow to successfully implement a data product strategy
Here’s a sneak peek at what you can expect.
Data Products, Defined
A data product is a consumption-ready set of high-quality, trustworthy, and accessible data that people across an organization can use to solve business challenges. Organized by business entities and governed by domain, data products are the best version of data. They are comprehensive, clean, curated, continuously-updated data sets, aligned to key business entities, that both humans and machines can consume broadly and securely across an enterprise.
Data products make data tangible for your data consumers. And good data products embrace the following four key principles:
- Discoverable and interoperable using intuitive user and machine interfaces that support real-time operations
- Comprehensive and consistent by aligning to a domain-specific, universal schema and enriching data with reference data sources
- Clean, accurate, and reliable with validation and cleaning based on global standards and version control for monitoring and provenance
- Curated and continuously-updated using pre-built, machine learning-based matching models
Good data products also embody several key capabilities. For example, good data products are curated with feedback from end users and use machine interfaces to support real-time operations. They are also mastered through machine learning-based matching models and enriched with external data sources. You can see the full list of data product capabilities in our CDO’s guide.
5 Steps to Help You Get Started with Data Products
Once you know how to define a data product, the next step is to build your data product strategy. And while creating a data product strategy may sound like a daunting task, we believe that if you follow these five simple steps, you’ll be on your way to realizing results such as increasing competitiveness by improving the customer experience, creating product differentiation, and delivering value for your organization by driving growth, saving money, and reducing risks.
- Know your why
- Assess your data, your organization, and your technology
- Define your use case
- Secure buy-in and budget
- Deliver a MVDP: minimum viable data product
Our latest e-book, Getting Started with Data Products: A CDO’s Guide, will serve as your blueprint, enabling you to successfully implement a data product strategy for your organization. In it, you’ll find a deep dive into each of the key capabilities a good data product needs, a checklist that helps you navigate each of the five steps above, and case studies of how customers like you used data to increase business impact using Tamr data product templates.
Now is the time to (finally!) become a data-driven organization. Download your e-book now.