In today's data-driven world, organizations are increasingly looking to data products to gain insights and make informed decisions. However, not all data products are created equal. Some are destined to be hits, while others are quickly unmaintained, outdated, or forgotten.
In the discussion "How to Create Hit Data Products in an AI World," three AI Product experts, including Kaycee Lai Founder of Promethium, share their insights on what makes a successful data product.
Attributes of Successful "Hit" Data Products
Value for Consumption: The data product must solve a real business problem and enable users to achieve outcomes more quickly. This means that the data product must be relevant to the users' needs and must provide actionable insights. It also must be easy to use and understand.
Ease of Consumption: The data product should be easily consumable by a variety of personas, including business users, BI developers, and machine learning specialists. This means that the data product should have a user-friendly interface and should be accessible from a variety of devices, and insights should be easy to share amongst team members.
Trustworthiness: The data product must be of good quality, have a clear lineage, protect data privacy, and have reliable service level objectives. This means that the data product must be accurate, complete, and consistent. It must also be protected from unauthorized access and available when users need it.
Discoverability: The data product should be easy to find, understand, and learn how to use. This means that the data product should have a clear and concise description and should be organized in a logical way. It also should have documentation and training resources available.
Standardization: Data products should be standardized and interoperable to work together seamlessly. This means that the data products should use common data formats and standards. It also should be able to integrate with other data products and applications.
Key Points For Data Product Creators
By following these principles, you can create hit data products that drive value for your organization and help you achieve your business goals. Here are some additional tips:
Focus on creating data products that are valuable, usable, and trusted.
Make data products easy to consume by both technical and non-technical users.
Ensure that data products are trustworthy and of high quality.
Make data products easy to find and understand.
Standardize data products so they can work together seamlessly.
With these tips, you can create hit data products that will help your organization succeed in AI.
About Promethium
The Promethium Data Fabric is a game-changer for organizations aiming to build successful data products. By unifying disparate data sources and providing seamless, real-time access to the information you need, Promethium eliminates the complexities traditionally associated with data integration. Its AI-powered automation accelerates time to insight and ensures data accuracy and relevance, enabling teams to focus on innovation rather than the technical challenges of data management. Using Promethium, your data products will shine, delivering the actionable data intelligence needed to drive business success. Schedule a demo today.
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