Data engineering addresses the challenges of scattered, fragmented, obsolete, or incomplete data by integrating information from various sources into a single data platform or data lake. Data analytics of structured, integrated, and cross-checked data is a foundation for intelligent insights and accurate predictions. Contact us if you need more information on our data science engineering services.
The key to the success of a modern business is making sense of data. Our company provides data engineering services that bridge together scattered datasets and turn them into a unified, usable, accessible, and reliable source of truth. Reshape your business with advanced analytics, data-driven decision-making, and innovation enabled by the right data architecture and governance.
Why your organization needs data engineering services
Data engineering is essential for any business looking to save costs, adopt new technologies, and make informed decisions based on real-time insights. With professional data engineering services, you’ll maximize the value of the data, creating a solid foundation for your company’s data-driven future.
Our data engineering services
We offer data engineering as a service for businesses that strive to get the most value from their data. Our data engineering team will help you overcome any challenges related to data management and open up new opportunities for technological advancements and business growth.
Designing the right data architecture is central to the successful implementation of your data strategy. We’re well-qualified to analyze your data infrastructure and suggest improvements to better meet your business goals, create the architecture that covers the entire data flow, from collection to consumption, and give you a time and cost estimate for data platform development. We can also leverage cloud platforms to boost scalability and speed up data processing.
Data processing and integration
Data processing services aim to make the on-premises and cloud data that a business collects usable. Our data engineers will build ETL/ELT data pipelines that connect key data sources, clean your data from errors and duplicates, and move it to data lakes or warehouses to prepare it for analysis. Our team is always ready to tackle data engineering challenges without sacrificing data quality.
From data preparation to its use and disposal, we’ll make sure your data assets remain optimized, secure, and used to the fullest. With our data governance services, you’ll have all the policies, processes, tools, and metrics in place to maintain a high quality of data throughout its lifecycle.
Technologies we use for data engineering
We use Microsoft Azure data engineering solutions and services for data-related projects. Why? With Microsoft Azure, you get built-in encryption, scalable data storage, global cloud access, and easy recovery. It means you can manage large amounts of data with no hassle — anything your business may need is there.
Microsoft SQL Server
Microsoft SQL Server allows us to easily migrate data to the cloud with zero code changes and integrate cloud data with your apps. Our team can also leverage built-in AI to run advanced analytics and make your business intelligence-driven
Azure SQL and NoSQL databases
Azure SQL and NoSQL databases are fully managed, scalable, and secure. Whether you need to handle relational data in schema-dependent legacy systems or rapidly changing and indeterminate data in always-on apps, our specialists will help you speed up data collection and data analytics without sacrificing data quality.
Azure Data Lake Storage
Need a data engineering solution for massive amounts of non-relational data? Azure Data Lake Storage is a single storage platform that supports a wide range of ingestion, processing, and analytical tools.
Azure Data Factory
Azure Data Factory is a high-end solution to integrate, transform, and analyze data from big data sources, enterprise data warehouses, and SaaS apps. More than 90 built-in connectors guarantee that you won’t miss out on data crucial for your business.
Our data engineering expertise across industries
Why choose devspiration?
Experience in data engineering
Microsoft Certified Partner
Positive client feedback
Expertise in other data-related services
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СEO & Founder, Upendo Ventures
Before starting Upendo Ventures, I led the team at Hotcakes Commerce. At the time, it was a thriving commercial e-commerce platform built on top of the most popular ASP.NET CMS known as DNN. Hotcakes Commerce was rarely not seen in the top 3 selling extensions overall for DNN throughout its entirety as a commercial product. While it’s since been re-released as an open-source e-commerce solution, its popularity has not faded. This popularity is primarily due to the stability and high-quality features it’s boasted over the years. Many of these features were either built or started by the team at devspiration. With Hotcakes Commerce being at the core of what started Upendo Ventures and its continued success as one of our specialties, I can confidently say that the devspiration team has been a cornerstone of what sparked it all. I’d recommend them for all of your custom software needs. You can trust their attention to detail and expertise for all of your mission-critical software projects.
devspiration team helped us to develop a PDF parsing framework for our cloud based image inspection platform Azenzus. They accomplished this goal quickly and professionally. We enjoyed their proactivity, dedication and detail-oriented approach. Highly recommend devspiration as a trusted technology partner for other businesses.
devspiration partnered with our core development team and became an integral part of our engineering efforts on the first release of our SaaS product. They quickly adopted our in-house standards and culture, and provided cutting-edge development on new technologies that our team did not have expertise using at the time.
We are truly grateful how quickly they assimilated into our team and for the high level of attention and professionalism every team member provided.
1. What data-related challenges does data engineering solve?
2. What is a data warehouse, and how does my business benefit from it?
A data warehouse is a central repository that stores data in a queryable form for more easily managed services and data analysis. It combines structured and unstructured data from various sources. By moving data to a data warehouse, businesses improve access to it, which creates a foundation for business intelligence and data science applications.
3. What is an ETL pipeline, and why do you need it in a data science project?
ETL stands for Extract, Transform, and Load, and is a process for replicating data via a data pipeline. Data is first extracted from multiple sources and put into a staging area where it is transformed and cleaned to meet the format requirements. Finally, the cleaned data is loaded into a target data warehouse or database. Gathering data in one place through an ETL process is a necessary step before performing any data science task, including machine learning modeling.