In many organizations, AI exists as a secret weapon. It’s essentially locked away in a box, brought out to work on a limited use case, and then put back into the box. However, using AI in this limited fashion eliminates the huge potential impact that AI can have across one’s business. This is where DataOps, short […]
Innovating with Data Mesh and Data Governance
Large organizations want to create a flexible environment to innovate and respond quickly based on new data insights. But at the same time, these businesses want some structure for good Data Quality, data fit for consumption, simplifying and speeding up data access. Using a data mesh, which is a decentralized data architecture (collecting, integrating, and analyzing […]
Quantifying the Value of Data to Business Leaders
When you hear the phrase “data monetization,” you might think of selling data to a third party – along with the many ethical and privacy issues that go with it. While this practice plays a significant role in our modern economy, there is another type of data monetization that receives less buzz but is equally […]
Key Principles of Data Product Management for Maximizing Business Value
Although almost every company in the world recognizes the power of data, most struggle to unlock its full potential. Companies such as Google, Amazon, and Uber that primarily deal with data are among the most valuable in the world, in terms of market capitalization, business performance, and innovation. One of the key reasons for their […]
Harnessing Data: From Resource to Asset to Product
Companies that are data-driven demonstrate improved business performance. McKinsey says that data and analytics can provide EBITDA (earnings before interest, taxes, depreciation, and amortization) increases of up to 25% [1]. According to MIT, digitally mature firms are 26% more profitable than their peers [2]. Forrester research found that organizations using data are three times more […]
Data Product vs. Data as a Product (DaaP): Understanding the Difference
Data quality (DQ), which ensures that data is fit for business and consumer needs, remains a significant challenge and is growing more complex. According to a dbt Labs 2024 report, 57% of survey respondents identified data quality as a challenging aspect to data preparation, up from 41% in 2022. To address these data quality challenges, companies increasingly […]
Mind the Gap: The Product in Data Product Is Reliability
Welcome to the latest edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). Last month, we explored analytics architecture stuck in the 1990s. This month, we’ll look at the rise of the data product. It wasn’t so long ago […]
How to Become a Data Product Manager
Becoming a data product manager means taking responsibility for the development and management of data products. Broadly speaking, a data product is any software or algorithms that use data to accomplish a goal. The data product manager is a management position, and requires several years of experience within the data industry to be done well. […]
What Are Data Products and Why Do They Matter?
Data products are software in the form of specialty tools and apps that are designed to support data used as a service. They may be as simple and straightforward as a program that converts a dataset into a visualization, or as complex as a machine learning system based on large language models (LLM), such as ChatGPT. […]
Data as a Product: What We Can Learn from More Established Industries
A concise definition of data product was coined by DJ Patil as “a product that facilitates an end goal through the use of data.” This includes not only pure datasets, both raw and refined, but also products based heavily on algorithms, models, and similar data-intensive workloads. Leaders in data are leaders in business, and treating data as a product is […]