Efficiently handle large volumes of data from diverse sources and manage dependencies by orchestrating and scheduling with Azure Data Factory.
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HERO_Data&AI > Data Engineering
Data Engineering.
Build cloud-native pipelines that accelerate analysis and drive faster delivery of business value.
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Prepare your most valuable asset for analysis and insight.
We help you engineer your data pipelines to exploit cloud-native services, with everything you need to ingest, curate and prepare your data for business use.
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Streamline complex workflow management.
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Improve data quality through curation and cleaning.
Keep business confidence in your data integrity and reliability high and unify disparate data sources with Databricks and Synapse.
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Optimise data for business consumption.
Use Synapse, Databricks and/or Snowflake to avoid manual, repetitive processing in modelling and preparing your data for end-users.
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Build pipelines more quickly with automation.
Leverage IaC and CI/CD in Azure DevOps to rapidly build and test high quality pipelines, eliminating manual coding and data formatting.
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IN ACTION
CASE-STUDY_Data Engineering
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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VALUE-PROP_#1- Data Engineering
VALUE-PROP_#1- Data Engineering
Data modelling.
Structure and connect your data optimally for business consumption.
Data modelling helps businesses use data effectively to meet individual, departmental and leadership information needs. However, businesses often struggle to organise and connect their data across different functions.
By building conceptual, logical and physical data models, we help you create a stronger understanding of how your data is best structured, and how your datasets connect together. We use Synapse, Databricks and/or Snowflake as standard to prepare your data for end-user engagement and consumption.
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VALUE-PROP_#2- Data Engineering
VALUE-PROP_#2- Data Engineering
Data ingest.
Layer additional insight into your ecosystem by ingesting data from new internal and external sources.
Effective data ingest is about cost-efficiently collecting and storing data imported from a wide variety of sources, types and schemas into a consistent format in the cloud.
We help you build real time and/or batch data pipelines to bring in data from various sources from public data and paid-for third party or internal systems using cloud-native tools. This allows you to build the analytical insights and AI/ML solutions needed to exploit your data to deliver maximum business value.
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VALUE-PROP_#3- Data Engineering
VALUE-PROP_#3-Data Engineering
Data quality, storage and curation.
Improve the value and usability of your data by increasing its quality, contextual relevance and accessibility.
Limitations in legacy environments and an inconsistent focus on data curation often result in sub-optimal workflows, poor user experiences and an erosion of confidence.
Our experienced engineers optimise the accessibility and quality of your data to rapidly reach its commercial potential. We use cloud-native services to deliver elastic scale, cleaning and modelling your data as efficiently as possible for your consumers.
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VALUE-PROP_#4- Data Engineering
VALUE-PROP_#4- Data Engineering
Analytics pipelines.
Build meaningful outgoing analytics pipelines from data stores that prepare data for analysis and decision-making.
Many organisations reduce data engineering to what they see as its primary function - consuming data into a warehouse from source systems - but this neglects an important part of the engineering lifecycle.
Our data engineers are equally experienced in both data ingestion engineering and analytics engineering: curating data on its way to a Machine Learning model, a Generative AI solution, or business intelligence dashboards to improve performance.
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Our customers.
Ascent works with over 150 businesses in the UK, Europe and North America. From global insurance, healthcare and retail to smart home devices, space exploration and cricket - we get to work with some of the sharpest minds in the brightest businesses.
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TILES_Other_Services_Data-and-AI_Explore Data Engineering_4tiles
Explore our other services.
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Legacy Modernisation
Decommission legacy platforms and modernise your data landscape with scalable, elastic cloud services.
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Data Visualisation
Turn raw data into immediate, actionable insight into your business performance.
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Data Products & Innovation
Make your data work harder for your business, delivering new consumer value, reducing costs and creating new revenue streams.
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Modern Data Platform
A modern, composable foundation for your data and analytics services, designed to deliver rapid ROI.
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FOOTER_Lets get started section - DATA
Let’s get started.
We help customers build new data-led business capabilities, services and products, delivering pivotal data and AI projects on the Azure cloud. Got a challenge in mind? We’re ready when you are.
Get In Touch
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