Ascent Data Engineering.

Data > Data Engineering Service Page_HERO

Data Engineering.

Prepare your most valuable asset for analysis & insight.

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How we help.

We prime your data to deliver intelligence and insight, helping you answer critical questions and make better business decisions. Here’s some of the typical customer challenges we see.

Data Engineering - Element - Data Value

Data value is locked into structured formats & can’t meet our evolving business requirements.

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Data Engineering - Element - Disparate Sources

Our data originates from disparate, unmanaged sources & represents a security risk.

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Data Engineering - Element - Manual Rep work

We have to do manual, repetitive processing to prepare our data for consumption.

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Data Engineering - Element - Timescales

We can’t make data available in the timescales required.

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Data Engineering - Element - Environment Limitations

Environment limitations result in non-optimal workflows & poor experiences for our users.

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Data Engineering - Element - Data Quality

Increasing concerns relating to data quality are eroding business confidence.

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Data Engineering - Element - Storage

Our storage/maintenance costs are increasing and are not aligned with value delivery.

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Data Engineering - Element - People Turnover

Data is becoming an increasing challenge to maintain due to staff turnover/skills gap.

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Diagram_Our resources and capability - Data Engineering

Our resources and capability.

The scale and skills of our talented teams (and where to find them).

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Data Preparation - Data Engineering

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Data Engineering - Data Preparation

Data preparation.

Data preparation is all about discovery and implementation planning for data transformation projects - followed by data cleaning, anomaly detection, quality optimsation, integration and migration activities. Our teams of experienced data engineers have worked in every scenario from start up to enterprise and know exactly how to optimise the accessibility and quality of your data, so it can reach its commercial potential more quickly.

A standardised approach to frameworks and reference architectures for migration and integration keeps things simple and efficient, so we can apply our expertise to the custom elements of your project.

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Data Platform - Data Engineering

Data Engineering - Data Platform

Data platform.

We help businesses structure and implement data transformation initiatives that are driven by their vision and objectives and aligned with their maturity.

Working closely with you, we design and build right-sized, cost-effective cloud data platforms on Azure that harness native services to make your data more standard, more secure and easier to govern.

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Value Proposition

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Data Pipeline - Data Engineering

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Data Engineering - Data Pipeline

Data pipeline.

Taking you from proof of concept to production, we design efficient, reliable pipelines that collect, move, transform, store and present data into analysis-ready structures.

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What it means to you table - Data Engineering

How we work and what it means to you.

How it work & what it means to you.

How we work.	What it means to you.
Azure native, automation-first data engineering approach using serverless technologies.	Optimised, lean development and operational costs.
Templated and standardised: reusable Azure component modules, templated architecture patterns & CI/CD pipelines.	Rapid mobilisation and deployment. Reusable functions and data processing pipelines enable fast ingestion of data.
Part of a broad, mature data offering that combines data architecture, engineering, consulting and data science with design thinking.	Direct route to building compelling business services on top of your modernisation investment.
End-user focussed: prioritisation of accessibility and usability through strong metadata-focussed approach.	Get to the answers, results and decision points that you need more quickly and effectively.
Engagement options: Projects and DataOps.	Onward service path out of transformative/ modernisation projects geared to deliver high volumes of smaller scale changes in BAU.

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IN ACTION

DATA - Data Engineering CaseStudy

Carlsberg Group

Moving intelligence to the cloud.

Heritage beer brand Carlsberg’s progressive approach to business and brewing has made them a world leader in the sector. Founded in 1874, Carlsberg now has more than 140 brands in its portfolio, which spans core, craft & speciality and alcohol-free brews.

Ascent’s Lisbon-based data engineering team were engaged to help Carlsberg undertake a critical migration from on-premise BI systems to the Azure Cloud, implementing batch and streaming data processes and replacing old SSIS packages with PySpark notebooks. The team also used Databricks to build machine learning models to predict churn and profitability.

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Our customers.

We love what we do and we get to work with some of the sharpest minds in the brightest businesses: from smart home devices, space exploration and beer to manufacturing, finance, ecology and logistics.

Creating compelling omnichannel experiences from bar to browser.

BREWDOG

Pouring beer