What is the Metrics Layer?

Businesses today rely on data to make informed decisions, and effective data management and analysis have become essential. One key component of modern data infrastructure is the metrics layer, which provides a centralized repository of key performance indicators (KPIs) and metrics that business users can access to get a real-time view of their operations and performance. In this blog post, we'll explore what a metrics layer is, how it can benefit your business, and how to build it and fit it into the modern data stack.

Why a Metrics Layer Is Essential?

Businesses face various challenges when it comes to managing and analyzing data. According to a blog post by a16z, these challenges include "complexity, inconsistency, and lack of accessibility" of data. Data is often siloed across different systems, making it difficult to get a comprehensive view of performance. In addition, business users may need more tools and expertise to access and analyze data effectively. These challenges can impede businesses' ability to take the right actions and achieve their goals.

A metrics layer can help address these challenges by providing a centralized repository of KPIs and metrics that business users can access in real time. By providing a unified view of metrics, business users are enabled to think systematically and take action quickly.

What Is a Metrics Layer?

At its core, a metrics layer is a centralized repository of KPIs and metrics that provides a real-time view of business performance. The metrics layer is typically integrated with other data management and analysis tools, such as data storage and data processing tools, to provide a comprehensive view of business operations.

A metrics layer can offer a range of benefits for businesses, including:

1. Self-Service Analytics: A metrics layer enables business users to access data quickly and easily, reducing their dependence on IT teams. It can streamline the data analysis process and make it easier for users to generate reports, explore data, and create insights.

2. Data Quality: A metrics layer can ensure that data is accurate and reliable, reducing errors and streamlining the data preparation process.

3. Unified View: A metrics layer provides a unified view of KPIs, combining data from multiple sources into a single view. It ensures businesses have a comprehensive view of their performance and can make informed decisions based on accurate data.

The Evolution of the Metrics Layer

While data analytics technology has existed for some time, traditional methods were often limited in their capabilities and needed more flexibility to adapt to changing business needs. According to a16z, emerging architectures for modern data infrastructure are enabling the development of more flexible and adaptable metrics layers that can better serve the needs of modern businesses.

As a component of modern data stack, metrics layers are designed to be more modular, allowing businesses to easily add or remove business metrics as their needs change. Others are designed to be more customizable, enabling businesses to tailor the metrics layer to their specific needs. For example, a large commercial banking company saved more than 50% time for end-to-end insight delivery by building a metrics layer on big data.

In addition, the rise of the metrics-driven decision making is driving the evolution of the metrics layer. As more organizations are in the progress of digital transformation, they are increasingly focusing on metrics as a way to drive decision-making and improve performance. As a result, metrics layers are evolving to better serve the business with more advanced features for tracking and analyzing KPIs.

How to Build a Metrics Layer in 3 Steps?

At Kyligence, we provide the leading metrics platform - Kyligence Zen, for businesses to eliminate BI report limitations and achieve metrics-driven decision-making. Kyligence Zen centralizes scattered metrics in BI to a unified metrics platform, saving you time and ensuring that all your metrics are managed and analyzed in one place.

Since we've discussed the importance of a metrics layer, let's take a look at how organizations can build their own metrics layer with Kyligence Zen in just three steps:

Step 1: Collect Your Data

Before you define the metrics, the first step is to collect and centralize your data. This involves gathering data from various sources, such as your website, social media channels, customer database, and other systems, and storing it in your cloud storage like AWS S3. And then, you can continue to use them on Kyligence Zen.

Step 2: Define Your Metrics

The second step is to define your metrics. Metrics are most important to your business, and can vary depending on your industry, goals, and operations. For example, if you're an e-commerce business, your metrics might include conversion rate, average order value, and customer lifetime value. Kyligence Zen offers a variety of metric types to meet the needs of complex business logic.

To learn more about building and defining metrics, you can also explore the Metrics Template Marketplace to find the right metrics templates related to your business.

Step 3: Explore Metrics in Excel

The final step is to consume your metrics with your most familiar analytics tools - Excel. Simply drag and drop to build a pivot table, and you can easily access the metrics from the central platform. By the way, as Excel Copilot is coming, you can also leverage AI capabilities to discover insights automatically on your metrics.

In conclusion, a metrics layer is a crucial component of modern data infrastructure that gives businesses with a real-time view of their performance and enables them to make informed decisions. With cutting-edge technology, Kyligence Zen empowers you to build the metrics layer for your organization, streamlining your decision-making process and aligning your team around your most important business goals.

Now Kyligence Zen provides a 14-day free trial to full features of a Metrics Platform. Please visit here to learn more.

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