Big Data and AI Pipelines
At Cambium we’ve worked on many big data projects. They tend to follow these three stages:
Plumbing, Analytics, and Machine Learning.
You need a data pipeline to convert the various incoming data into standard formats, make sure it's saved properly, and move it around your infrastructure. Setting up this plumbing is the first step in any big data pipeline.
From expansive data lakes to pre-filtering your data sets, we're comfortable with the techniques necessary to set your project up for success without spending all of your money on unnecessary storage or compute.
The heart of any big data project is the analysis. With all your incoming data transformed and properly stored, you will want to build tools to allow you to visualize, correlate and explore your data, and set up alerting and reporting based on business KPIs and technical indicators. In this part of the project we work closely with you to make sure we are able to get the answers you need.
MACHINE LEARNING AND AI
Once we have a handle on the data we look at ways we can glean actionable insights by creating models and training systems. This is where the fun technologies come into play, things like recommendation engines, classifiers, and neural networks. These systems are designed to produce automated answers to questions based upon new and unseen data.
Models require maintenance, and we're firm believers in writing tools to help you maintain them. We specialize in constructing tools to help you manage your training data, as well as to make minor tweaks to the model based upon new business insights.