Blog

How we improved our core web vitals by migrating to Gatsby

By migrating the architecture of this website to Gatsby, we were able to double key core web vitals, increase our accessibility rating by 50%, and boost our SEO scores from 80 to 100

What is Gatsby?

Gatsby is an open-source framework that combines functionality from React, GraphQL and Webpack into a single tool for building static websites and apps. Owing to the fast performance of the sites it powers, impressive out-of-the-box features like code splitting, and friendly developer experience, Gatsby is fast becoming a staple of modern web development.

What is data engineering?

The quantity and complexity of the data that companies deal with is constantly increasing. While Data Scientists analyze and generate actionable insights from data, they cannot do this effectively with data that suffers from poor quality. Data Engineering roles exist in companies to build data pipelines, transform data into useful formats and structures, and ensure quality and completeness in data sets.

Python and SQL: Complementary tools for complex challenges in data science

While Data Scientists today have an ever-expanding list of toolkits, languages, libraries and platforms at their disposal, two mainstays––Python and SQL––are likely to remain staples of data analysis for years to come. Here, we’ll look at the role these languages play in the rapidly evolving field of Data Science.

The value of a universal customer ID across your tech stack

Teams across industries are striving to create a 360-degree customer view. But if that view isn't seamlessly integrated with the tools and systems throughout the tech stack in real time, growth teams aren't able to use it to drive results. Learn more about how you can implement a universal ID and make it available across the stack.

Relational vs. Non-Relational Databases

What are the key differences between these two main categories of databases, and how do you select the right type of database for different use cases?

Data enrichment and machine learning: Maximizing the value of your data insights

Data enrichment and machine learning are two techniques that can enhance the ability of your customer data to drive personalized experiences. While there is some overlap in the end goal of both approaches to enhancing data value, there are significant differences in the time, resources, and overhead they each require.

How to stop endless data shipping cycles

Engineers should ship products, not data. Product managers and marketers should experiment with data, increase personalization, and improve experiences. With a permanent data infrastructure, these goals are not mutually exclusive.

Capture page navigation events in a React Application

In a single-page application, understanding which pages your customers visit and the journeys they take through your website can be challenging. Here, we’ll look at a scalable and maintainable strategy for tracking page navigation events in a React application.

Track User Events in Single-Page Applications

Owing to their fast load times and smooth user experiences, Single-Page Applications (SPAs) are now an extremely popular design pattern for developing websites. While building your site as an SPA offers clear advantages for your customers, it places challenges in the way of collecting robust analytics on user behavior.

APIs vs. Webhooks: What’s the difference?

An API (Application Programming Interface) enables two-way communication between software applications driven by requests. A webhook is a lightweight API that powers one-way data sharing triggered by events. Together, they enable applications to share data and functionality, and turn the web into something greater than the sum of its parts.

What is data orchestration

Data orchestration is an automated process in which a software solution combines, cleanses, and organizes data from multiple sources, then directs it to downstream services where various internal teams can put it to use. The purpose of data orchestration is to help a company make its data as useful and versatile as possible.