Tag

Big Data

Data strategy

Why you should replace your analytics tracking code with a Customer Data Platform

Analytics tracking tools have become the standard for collecting user events and understand engagement. But in a rapidly evolving market environment, sometimes "standard" isn't enough. Learn more about how you can upgrade your data pipeline with a Customer Data Platform.

Joey Colvin – January 28, 2021
real-time-data-processing

Data strategy

Why real-time data processing matters

Business-critical systems shouldn't depend on slow data pipelines. Learn more about real-time data processing and how implementing it strategically can increase efficiency and accelerate growth.

Joey Colvin – January 08, 2021
cdp machine learning

Data strategy

How to harness the power of a CDP for machine learning: Part 3

Learn how you can activate machine learning insights across analytics and customer engagement platforms in part three of this three-part series.

Kale Bogdanovs – December 16, 2020
cdp machine learning

Data strategy

How to harness the power of a CDP for machine learning: Part 2

Get a step-by-step guide to activating ML insights with mParticle and Amazon Personalize in part two of this three-part series.

Kale Bogdanovs – December 16, 2020
cdp machine learning

Data strategy

How to harness a CDP for machine learning: Part 1

Learn how an infrastructural Customer Data Platform can help you overcome common machine learning challenges in part one of this three-part series.

Kale Bogdanovs – December 16, 2020
snowflake-apache-airflow-machine-learning

Data engineering

Generate in-warehouse predictive audiences

Learn how Jayant Subramanian, data science intern, developed a proof-of-concept machine learning pipeline for predicting user behaviors from data pre-processing to model training and beyond using Snowflake and Apache Airflow.

Jayant Subramanian – January 07, 2021

Melissa Benua on CI/CD and Quality Engineering

Melissa Benua, Engineering Manager of mParticle dives into Continuous Integration / Continuous Delivery and discusses some industry best practices and why Quality is going to become everyone's responsibility.

November 25, 2019
looker partners

Integrations

Connect your Looker Data Actions to mParticle

Take action on your Looker insights by connecting data to mParticle with Looker Data Actions.

Kale Bogdanovs – November 05, 2019

Release notes

Data is a team sport: Q4 feature announcements

Bad news for the rogue product manager, the lone wolf data scientist, the intransigent head of infosec, and the obstinate engineering manager: Data is a team sport. Learn about the forthcoming releases designed to help your whole team do more with more of your data.

Craig Kelly – October 09, 2019
event driven architectures

Integrations

Real-time event processing with Kafka

Learn how mParticle's Kafka integration can help you stream customer data to systems and applications with event data forwarding, advanced filtering and compliance, distributed event notification, and event sourcing.

Kale Bogdanovs – September 30, 2019
Data warehousing snowflake

Integrations

Load data to Snowflake data warehouse

Learn how mParticle's Snowflake integration can help you warehouse your customer data more efficiently and securely at scale with automated data exports, advanced filtering and compliance, and easier querying.

Craig Kelly – April 29, 2019

Media Coverage

mParticle launches Data Master to help users improve data quality

In this post, Destination CRM notes the launch of mParticle's Data Master, which is intended to help users audit their respective data pipeline.

January 31, 2019
Marketing technologists

CX

Top Marketing Technologists to Watch in 2019?

Nominate a marketing technologist for our upcoming report, "19 Marketing Technologists to Watch in 2019."

Joey Colvin – February 01, 2019

Media Coverage

Beet TV: mParticle’s Katz on unifying data

mParticle CEO & Cofounder Michael Katz explains how a CDP can help brands break through the challenges associated with multi-touchpoint data ingestion and disconnected data systems by creating interoperability between all of the systems that they are using across the business.

September 13, 2018
integrated data layer

Data strategy

How to plan your integrated data layer

Learn how to develop an integrated data layer that aligns with your business and techical goals and provides you with a centralized source of clean customer data.

Andy Wong – August 28, 2018
The Customer Data Platform magic quadrant vendor landscape

CDP

The Customer Data Platform vendor landscape

The customer data platform vendor landscape is confusing, but can be segmented along three dimensions: business model, data sources, and customer type. This post explains each one, so you can separate signal from noise and identify the right CDP for your business.

David Spitz – August 03, 2018
The fifth pillar of big data

Data strategy

Validity: The fifth V of Big Data

The Four V's of Big Data have been an industry standard since their introduction, but the increasing concerns about privacy recently have led to the need of a fifth V: Validity.

Tim Norris – May 16, 2018
mobile-financial-services

Mobile growth

Power your mobile financial services strategy

With the rise of mobile financial services, traditional financial companies have to change the way they approach modern customers or face failure.

Adam Blake – March 08, 2018
How to design high throughput and low latency NoSQL deployments

Data engineering

ScyllaDB Migration: How to design high throughput and low latency NoSQL deployments

Yuan Ren, Head of Data Science at mParticle, discusses our ScyllaDB migration and how to process 50 billion monthly messages via NoSQL deployments.

Yuan Ren – August 24, 2017

Data engineering

Hyperloglog Algorithm: A must-know for data scientists

Hyperloglog (HLL), a powerful streaming algorithm, helps mParticle deliver real-time analytics products. Learn why it's a must-know for data scientists.

Yuan Ren – October 23, 2014

Data engineering

App development: Planning for the long term

Long-term thinking is valuable when trying to meet any goal, and app development is no exception. However, long-term can be as short as a few weeks.

Rishi Sethi – December 16, 2014