At Infinite Lambda, we have extensive experience working on data projects from various industries. This allows us to recognise common challenges when it comes to the data infrastructure. In this blog post, we won’t try to address all of them but we will share a few of the best practices we have found to help deliver a successful project.
Agile methodology: iteration is key
One of the most common problems we see when building complex data platforms is that the deliverable does not meet the expectations of end users. This means that the team has to go back to square one, which is neither sustainable nor efficient. Here, regularly communicating with stakeholders and allowing room for interaction are key factors in ensuring efficiency, quality and, ultimately, happy data users.
Our experience shows that agile methodologies work well when building complex data architectures where we need to address the input of various stakeholders. We primarily work with the scrum framework, which we have applied with a high success rate as it allows for continuous learning and adjustment of fluctuating factors. Scrum enables the team to adapt to changes in conditions and user requirements. It also makes it easier to re-prioritise during the development process while maintaining high levels of engagements with both technical and non-technical stakeholders.
The small iterations in the agile approach provide two powerful levers: on the one hand, we are able to constantly learn and improve our domain knowledge. On the other hand, we manage to capture the customers’ real needs that tend to keep evolving after the initial discussions.
Being able to work with the data while building the infrastructure allows us to get a clear understanding of our customers and to help them refine their idea through a solution that they can interact with.
Industry and technology agnostic approach
Regardless of the industry, the technology division is constantly challenged by evolving technologies and controlling the total cost of ownership.
With a traditional setup, data is usually stored on-premise, which is connected to different applications, such as multiple enterprise resource planning (ERP) systems, that integrate the company’s data, and data analysis is performed via Excel. The problem here is that data is siloed and it does not always tell the whole story.
The emergence of cloud technologies and open source SaaS tools has empowered an architectural shift in the data infrastructure. The resulting modern data stack can be used for data management and analytics across industries.
At Infinite Lambda, in order to build a scalable and flexible platform, we place special focus on the choice of technologies and the principles they are built on. We start by defining the DevOps principles before moving on to the actual implementation of any data platform.
This allows us to forecast the data consumption trends, so we can select technologies that meet the criteria. This helps the organisation to curb technical and operational costs but also to reduce overheads.
We have seen how the finance sector has utilised open data infrastructures and all stakeholders have benefited from it. The sector has enhanced its service offerings, improved customer engagement and built new digital revenue channels. Conversely, the energy sector is lagging behind. If data became more accessible and easier to share through modern open source technologies there too, the energy industry could take advantage of more impactful analytics too.
In many industries, there is still a lack of data professionals that can lead on the data infrastructure modernisation strategy. For example, energy and data are two extremely rich topics that have the respective domain experts and yet pragmatic education that connects the two is difficult to come across.
Modern cloud technologies have contributed to making data more accessible to non-technical people. However, there are still many gaps that only data professionals can fill. The only way to truly democratise data is to make people feel confident when consuming their own data and making decisions based on it. This can only be achieved through intensive training on their data estate.
Having a strong domain in data and cloud engineering, we see it as our responsibility to share the knowledge we have acquired through experience. Hence, documentation and education play an important role in all of our projects.
Our philosophy is to teach while we build, so we conduct intensive training sessions. We continuously help our customers to upskill and become well versed in the technologies and the best practices on which their infrastructures are based.
We are also in the process of establishing academies because we believe in investing in talented people and helping them set out on their journeys in data. We want to actively attract more people to the data industry and tackle the shortage of data professionals.
About Infinite Lambda
Infinite Lambda is a fast-growing company with offices in vibrant and rapidly evolving cities in the UK, France, Slovakia, Hungary, Bulgaria and Vietnam.
We have extensive experience in delivering and developing data-intensive systems that help businesses derive easy-to-understand, actionable insights. We have completed tens of cloud and data platform projects across multiple industry verticals, empowering organisations to bring a healthy dose of cross-pollination of ideas.