Become a business enabler and empower your business partners how it matters most.
Our goal at Transform is to empower users to have confidence in their data to make decisions. We believe that metrics are at the center of analytical workflows, but often those metrics lack fundamental support. Organizations without a strategy for managing metrics see a continual and unintentional redefinition of key business concepts, loss of productivity, and general distrust of data. If you use data for your day-to-day decision-making, you've likely asked a set of familiar questions multiple times when encountering metrics. If you're an analyst producing the data, you may be at the other end of these piling and redundant inquiries.
These questions could vary from what the particular metric means fundamentally, as well as how it was calculated. Or they may be focused on whether the metric is still valid for reporting to the executive team. Perhaps the business teams are wondering how they might slice the metric by a given attribute. And, finally, one of the most common types of inquiries in my experience is something like this… Why was there such an odd spike in the value last year on October 11th?
Transform can help answer all those common questions a user may have accurately in one interface. Transform is a centralized metrics store in your data stack that enables you to define all your important metrics in a single place using MetricFlow, our Metrics Framework, explore and collaborate on these metrics using the Metrics Catalog, and perform further analysis by querying for metrics within your favorite tools using our Metrics API.
Our Metrics Catalog provides an easy-to-use UI for your data consumers to explore and understand the context around important metrics. When paired with MetricFlow, which analysts use to define metrics consistently in code, the Metrics Catalog becomes a single source of truth for your organization's metrics, which both data teams and businesses can contribute to and collaborate on.
By giving data consumers a single place to access the important data and all the context around it, we build a new way of working that benefits both business users and data teams. Not only does our Metrics Catalog empower consumers to make decisions confidently with consistent and accurate metrics, but it also reduces excessive and repetitive requests made to data teams, builds trust in data across the organization, and frees up data teams to focus on novel and higher-value problems.
At its core, Transform's Metrics Catalog contains a page for each metric that's been defined in MetricFlow. It shows a variety of information about the metric, including a visual representation of the values and important context around the metric. In this blog post, we'll walk through the details of Transform's Metrics Catalog, and why each component is important for achieving successful data governance.
Metric lineage and definitions
One of the most common questions both analysts and business users might have about the data is how a particular metric is defined and where it came from. If you've ever reported an inaccurate metric (it happens to the best of us), you will probably be extra cautious, and you'll want to understand the derivation and source of the data.
For each metric in Transform's Metric Catalog, you can dig into the lineage, which shows the MetricFlow code that was defined by your data teams (in YAML). Take the following example metric—Paid Organizations—clicking into the Metric Lineage opens up the defined code which allows a user to see which sources of data the metric came from and, specifically, how it was defined, including the source table or query.
Instead of confusion, organizational misalignment, and repeated requests to understand a metric, the lineage instills confidence and transparency in the metric definition
Perhaps one of the most important facets of the Metrics Catalog lies within the approval and ownership features, which fosters a lifecycle management concept (much like a typical software code).
In MetricFlow, it's mandatory to assign an owner to the metric. The Catalog surfaces this ownership information so that a user always knows who to go to if they have an issue or would like to discuss a metric.
Also, the owner of the metric has required action to approve it at a defined cadence, which helps confirm the validity and freshness of the information. Consumers no longer have to worry or spend hours looking for the right person to determine if the metric they want to use is valid or accurate.
An example below in our UI shows a clear owner defined for a particular metric - the Finance team - as well as the date it was last changed and approved.
Ownership and approval are fundamental features to help ensure your metrics are properly governed over the course of their use.
Annotations and questions
Through our annotations and question features, Transform's Metric Catalog helps to bridge the gap between those that hold context and tribal knowledge on data, to those who are seeking information.
Many data analysts and business users alike have questions around data anomalies during analysis. They lose productivity by searching for the source of the anomaly when it may very well exist in a veteran analyst's head.
Transform lets you annotate metrics in the product so that anomalies and relationships to important events live right on the metric page. (As for that odd spike on October 11th, annotations tell us that there was a marketing campaign.)
Furthermore, both data consumers and producers can ask questions that all users can collaborate on, which helps teams continue to build organizational knowledge around a piece of data.
These features are crucial to improve productivity and organizational collaboration around metrics.
Dimensional analysis and charting
Many data consumers want to understand a metric value as it applies to a particular attribute of the data. For example, perhaps a growth team member focused on Canada and France only cares about the global revenue metric as it applies to those two countries.
As opposed to reaching out to an analyst to write an arbitrary query for this data, Transform has lightweight visualizations in our Metrics Catalog. These charting features allow for simple dimensional slices on a metric value so that your end users can self-serve while simultaneously having confidence in their provided data:
These simple cuts of data can get both business users and analysts far in their analysis and open up doors to more insights.
The future of Transform's Metric Catalog
Transform's Metric Catalog serves as the key visual and exploration hub for all organization's metrics, and we would like to expand it to further show the unique context that we have on the behavior and patterns of your metrics.
The future of this interface includes adding important context around metric value changes that are important for you. This could include year-over-year and other time-based changes that can be surfaced through the interface or customizable notifications.
Also, we want to go deeper in providing users context around the relationship between metrics as well as the behavior of their values in relation to your events such as campaigns, experiments, and other common drivers.
At Transform, we believe that you need the set of key features that our Metrics Catalog provides to truly govern your metrics: lineage and definition of metrics, clear ownership, and an approval cadence, context sharing through annotations and metrics, and lightweight dimensional slicing of the data.
Our Metrics Catalog can help create a symbiotic relationship between your data teams and business users by enabling independent decisions with confidence and allowing analysts to focus on more high-value insights.