Blog

Harveer Singh leads Western Union’s digital transformation with data

Chief Data Architect Harveer Singh creates the data and tech roadmap that will help the iconic company emerge as a leader in fintech.

Developer Deep Dive: mParticle Sample Apps

Recently, a cross-functional squad of engineers, PMs and designers at mParticle assembled to produce a labor of love––sample applications. These sample apps help developers implement our SDK in Web, iOS, and Android environments and understand the value of mParticle. Here’s the nuts-and-bolts story behind what they built, the technical choices they made while building these apps, and what they learned along the way.

Implement a CDP with ease using mParticle's sample applications

Developers rarely look forward to integrating third-party systems into their projects. The learning curve to understand vendor platforms is time-consuming and diverts attention away from more interesting product initiatives. Our sample applications address this problem by helping developers understand how mParticle works on various platforms and providing production-quality, copy/paste-ready code to implement our CDP with ease.

How we cut AWS costs by 80% while usage increased 20%

How do you replace a tire while driving on the highway? This is what it felt like to re-architect the engine behind one of our most heavily used and relied upon products, the mParticle Audience Manager. Here's how we optimized this critical piece of our architecture and positioned it to play a key role in the next phase of our growth, all while customer adoption and usage steadily increased.

Data quality vital signs: Five methods for evaluating the health of your data

It’s simple: Bad data quality leads to bad business outcomes. What’s not so simple is knowing whether the data at your disposal is truly accurate and reliable. This article highlights metrics and processes you can use to quickly evaluate the health of your data, no matter where your company falls on the data maturity curve.

How to choose the right foundation for your data stack

If you’re relying on downstream activation tools to combine data events into profiles, don’t. You’ll end up with fragmented and redundant datasets across systems. Enriching each data point before it is forwarded downstream will prevent this problem, but not all customer data infrastructure solutions deliver this capability.

Clear costs: How we used data aggregation to understand our Cost of Goods Sold

Understanding our cost allocation on the level of individual customers and services is an important metric for us to track. However, the major cloud providers do not readily provide this information, so to obtain it, our data engineering had to get creative. This case study describes how we built a custom library that combines data housed in disparate sources to acquire the insights we needed.

Smartype Hubs: Keeping developers in sync with your Data Plan

Implementing tracking code based on an outdated version of your organization's data plan can result in time-consuming debugging, dirty data pipelines, and misguided decisions. mParticle's Smartype Hubs helps your engineering team avoid these problems by importing the latest version of your Data Plan into your codebase using Github Actions.

A simpler way to implement and maintain video analytics code

Video analytics are essential to maximizing the impact and value of video content. For technical teams, however, capturing this data can often be more challenging than collecting other user events. In this article, we’ll show how mParticle’s Media SDK simplifies this process for engineering teams, and provides data stakeholders with actionable user insights.

Prevent data quality issues with these six habits of highly effective data

Maintaining data quality across an organization can feel like a daunting task, especially when your data comes from a myriad of devices and sources. While there is no one magic solution, adopting these six habits will put your organization on the path to consistently reaping the benefits of high quality data.

How to use a CDP with your data warehouse

Data warehouses and CDPs are two pillars of the modern data stack. Recently, a perception has emerged that companies need to choose one system or the other as a “source of truth” for their data. This article poses a counter perspective, and demonstrates how when used together, a CDP and a data warehouse can form a dynamic duo at the core of your data infrastructure.

How to implement an mParticle data plan in an eCommerce app

This sample application allows you to see mParticle data events and attributes displayed in an eCommerce UI as you perform them, and experiment with implementing an mParticle data plan yourself.