Data Engineering

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Data engineering is the central foundation for any advanced data project. Companies produce vast amounts of raw data, but it often lacks consistency in structure and formatting.

Data engineering takes these different sources and creates a consistent pipeline to enable the likes of AI, Data Science and Data Visualisation solutions.

Big Data can’t be handled manually. Automation is needed for the most efficient and optimised practices. An optimised pipeline can Extract, Transform and Load (ETL) all of your data, seamlessly moving from raw, unconnected data sets to formatted and structured data that’s automatically updated for real-time results.

Machine Learning

Big Data

Data Visualisation

Data Science

Dashboards

Analytics

01 Identify Data
Sources

Data engineering can help you identify potential data sources that are vital to achieving your business goals. Once we know where vital data lies, we can add it to the pipeline.

02 Expand Data
Acquisition

More data can reveal the larger picture. A custom pipeline is essential for achieving this in an efficient manner. We’ll ensure new data sources can be accessed and added with no complications.

03 Transform &
Format Data

Raw data is nearly impossible to analyse – especially from multiple sources. We’ll configure a unique ETL (extract, transform and load) pipeline to automate the entire process, from collection to storage.

04 Data
Storage

All data has to be stored somewhere. With growing volumes of historical data, data warehouses and lakes are vital for easily accessing data from your analytics. Paired with the Cloud, we can provide a storage solution that’s both accessible and cost optimised.

An automated process needs scalable servers able to spin up production when large volumes of data are processed, but don’t sit idle while not in use. Cloud infrastructure allows exactly that.

Data Workshop

A data workshop is the first stop for any data journey. Our Data Engineers and Architects will meet with you to discuss your data sources, needs and goals, as well as proposing a Minimum Viable Product (MVP) and roadmap for success.

Data Pipeline

The main MVP for most data engineering projects. A data pipeline is essential for transforming data from raw information to formatted structures ready for analysis.

Data Migration

Want to move your existing data sources into your new pipeline? We can help transform and integrate all your existing sources into the new pipeline.

Advanced Solutions

The data journey never stops – we can add new sources, create deeper insights or even start working on advanced solutions, from Machine Learning to Data Visualisation!

Get started with a workshop

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Data Engineering

Gather and structure your data for the best results & insights

Why Is Data Engineering Important?

Pipeline Automation

ETL

What Can Data Engineering Do For You?

Data Engineering & The Cloud

How To Get Started With Data Engineering?

Want to learn more?

Top 5 Reasons To Use Mesh Twin Learning in Your Smart Factory

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Digital Twin: The First Step To Industry 4.0

Let’s get started

Engineer your data into actionable potential.