As businesses continue to grow and evolve, the role of data engineering services becomes increasingly important.
Helping to create reliable data pipelines, architect data sources, and implement enhanced automation workflows wherever possible, data engineers can help optimise the functionality and reliability of data throughout an enterprise.
In doing so, they can create consistent outputs and encourage a data-driven culture enterprise-wide by communicating the value of consistent results.
From small regional businesses seeking secure and consistent outcomes to large multi-tiered enterprises in search of increased functionality and efficiency, data engineering services can bring significant benefits. Read on to learn more.
Defining data engineering
At its core, data engineers design and create an infrastructure that transforms and transports data into a highly usable format for end users – be it key stakeholders or internal sales teams.
The role of a data engineer, however, does not end there. Enabling the flow of traffic between systems, data engineers make data functional, consistent, and of higher quality in the process. They work collaboratively with enterprises to understand both the long and short-term challenges to the business, and also the underlying architecture.
With this knowledge of business objective and current infrastructure, data engineers can build intelligent and advanced solutions that not only cater to current challenges but anticipate future risks that accompany ongoing growth and expansion. Common examples of data engineering services include:
- Extracting data from different data sources into a data lake or data warehouse
- Enabling the ability to consume data in real time
- Integrating multiple systems together such as order management and finance systems
Automating workflows
Automation is the perfect answer for enterprises in search of efficient and streamlined data flow. For internal teams, automated workflows can enable the seamless transfer of data into a wide array of systems, bringing several significant advantages with it in the process.
Reducing risk
Traditionally, the transfer of datasets between systems, or their initial input, may require lengthy and error-prone manual processes. However, with manual processes being replaced with automated workflows, teams can reduce the risk that accompanies legacy processes.
As a result, users across all levels of an enterprise can place more trust in data-driven insights, with enhanced consistency and accuracy.
Greater capacity and productivity
Another significant benefit of data engineering-enabled automation is in the capacity and resource it returns to internal teams. While users traditionally may have had to devote large portions of their time to inputting and transferring data, this is no longer necessary. For the core user, this gives back valuable time to focus on other important tasks, boosting overall efficiency for teams and the business as a whole.
Building sustainable architecture
As the scale and complexity of a business grows, so too does the number of potential risks and threats.
A specialist data engineer can design and implement solutions for a business’s architecture that can resolve not just the initial identified challenges, but support ongoing growth and scaling.
With additional data sources and formats naturally accompanying architecture growth, new unexpected challenges may arise, affecting processing time, and security. To mitigate this risk, it’s important to design intelligent solutions that can handle ongoing pressure, challenges, and demands.
Whenever we work with new clients, the first step that we embark on is to understand the individual complexities, risks, and challenges of underlying architecture for this very reason.
By successfully negotiating any possible risk and creating reliable foundations at the beginning of our involvement, we can integrate intelligent engineering services that won’t fall victim to possible disruption. For internal teams, and stakeholders, this provides cost-effective and scalable solutions, with long-term confidence in infrastructure secure.
Helping teams with capacity
Internal teams may struggle with capacity due to a number of reasons. Internal IT teams may possess the skills and capabilities to construct intelligent data engineering solutions, yet they may not have the necessary capacity to do so.
Through our services, we work with these internal teams to help alleviate pressure, designing and implementing these solutions while prioritising trust and communication throughout the entire process. This means that IT teams will be familiar with our solutions, and able to maintain and even further optimise them, long after our partnership has come to an end.
For internal teams that may not possess the knowledge necessary to maintain and upgrade systems in the long term, we also offer a fully managed, retained approach to data engineering services.
This approach enables us to provide ongoing and long-term support for your enterprise’s architecture. Meanwhile we will maintain and suggest further improvements to your infrastructure without decreasing the capacity of internal teams and users.
Committed to delivering trusted intelligence
Throughout our involvement across a wide range of solutions and services, we use a value-led methodology that provides measurable benefits for enterprises across a range of industries.
From implementing a data warehouse to facilitate centralised reporting, to building pipelines between previously isolated systems, our range of services are designed to elevate intelligence, and establish confidence in your data throughout all processes – enabling a more advanced approach to strategic decision-making.
To learn more about how our solutions can help reach your business objectives and support internal teams, contact us today.
