You may have a good handle on what a product manager is, but what's a data product manager? A data product manager, at its core, is still responsible for the success of their product. If you're not familiar with the role of a traditional product manager or want to know more about it in general, I suggest reading First Round Review's What Every Engineer Should Know About Being A Product Manager by Kevin Hale from Y Combinator.
Before we continue exploring the role of the data product manager and why organizations are looking to hire them, it's important that we define what a data product is.
At its core, a data product is an interface for interacting with datasets; this could be through visualization tools like Google Data Studio & Tableau or via API. A key feature of these products is that they provide value beyond simple analytics (which can usually be provided by Excel); this additional value comes through increased usability as well as other intangible benefits like trust and collaboration.
Data product managers build things that can be turned into useful data.
Now that you're up to speed on what a data product is, let's look at what exactly a data product manager does and see if it's the right career path for you.
As we mentioned above, the goal of a data product manager is to create tools that help people or organizations extract value from the data they have collected. Data products can be used for many different purposes: monitoring, analysis, sharing information, making predictions...you name it! Depending on its function and audience, a data product could be web-based and distributed in the cloud (like Google Analytics), or embedded into another product (like how Facebook uses AI to scan photos and suggest who you should tag). Even though there are many types of data products out there doing many different things, all of them have one thing in common: good data product managers are key to their success.
You might be wondering: what is a data product?
A data product is not just software—it's a specific kind of software that's used within an organization or sold to external customers. Data products are built with data at the core, but they're also focused on how users can interact with, understand and benefit from that data. Unlike other types of software—like consumer-facing apps —data products have users who don't necessarily have technical skills.
At the most foundational level, a data product is built to solve a problem for someone. That problem could be internal (for example, helping people in your business make better decisions) or external (for example, helping your customers use your company's services more effectively).
A data product manager needs strong technical skills to handle the complexity of modern products.
To be a Data Product Manager (DPM) means being able to write software using various programming languages, including Java, PHP, Python and Ruby. DPMs must also have strong technical skills—including the ability to build web applications, databases and mobile apps. The product manager will work closely with software development teams to develop features of their products that satisfy business goals and user needs. As the product manager learns new technologies relating to their team's field, they need to stay abreast of changes in the business world as well as make sure they are on top of current trends in technology. "At the end of the day," says Luke O'Brien, a data product manager at LinkedIn , "a data product manager is a skilled communicator across all disciplines."
DPM have to have deep knowledge of databases, programming languages and web development tools
Plus an understanding of business processes that generate the data they produce. As with most deep knowledge, developing expertise in these fields requires a significant time investment.
If you have the appropriate qualifications and background and are considering a career in this field, you will be well-paid for your efforts. The median salary for Data Product Manager is $144k, according to Glassdoor.com.
Data Product Managers are people who understand business, technology and how to work with people to deliver a great product. They're like the combination of a product manager, a project manager and an engineering manager. The lines between different kinds of engineering disciplines keep getting blurry, small teams are developing data products and it will be common for large enterprises to spin out their own software divisions dedicated to building data products for internal and external customers.
I think this is one of the most exciting roles in the field of software right now because it's still so new and each time I talk about it with someone else I learn something new about what makes good Data Product Management. I also think that every organization needs someone in this role asap if they don't have it already.
Example 1: Netflix
Netflix is an excellent example of data product management. The company uses data extensively to improve its recommendation engine, which is a core component of its business. The recommendation engine uses data from users' viewing history, ratings, and preferences to suggest content that they are likely to enjoy. Netflix also uses data to determine which shows and movies are most popular, and it uses this information to create its original content.
Example 2: MyFitnessPal
MyFitnessPal collects data on users' physical activity, sleep patterns, heart rate, and other health metrics. They use this data to provide personalized recommendations to users, such as exercise plans, sleep schedules, and nutrition advice.
Example 3: Airbnb
Airbnb is a great example of how data product management can be used to improve customer experiences. The company uses data to personalize its recommendations to users, based on their past bookings and preferences. Airbnb also uses data to optimize its pricing algorithms, ensuring that hosts receive fair prices for their listings while also offering competitive rates to customers. Additionally, the company uses data to identify and address any issues that may arise during a guest's stay, ensuring that the overall experience is positive.
Data Product Managers are constantly looking for ways to improve their product offerings, and this is where Secoda comes in handy. Secoda provides an intuitive and user-friendly interface that enables Data Product Managers to easily access and analyze their data. With Secoda, they can quickly spot trends, identify anomalies, and track key metrics that are essential for making informed business decisions. Moreover, Secoda's AI-powered suggestions and recommendations enable Data Product Managers to optimize their data models and improve the accuracy of their predictions. Overall, Secoda's comprehensive data management platform is an indispensable tool for any Data Product Manager looking to take their product to the next level.