The data collected and processed by organisations is no longer just used to reactively support business decisions. Companies are increasingly focused on turning their data into actionable insights for various reasons, such as becoming more competitive by reducing operational costs, generating more revenue by having differentiated offers or improving customer experience, and reducing churn.
“Understanding customer usage and behaviour provides a unique knowledge which can be applied to develop new services and improve the customer experience.” Nuno Sanches Vodafone Group Head of Fixed Product Development, in Vodafone TV Analytics Case Study.
In recent years, we have seen a revolution in the analytics space, with organisations moving from centralised data management to a nearly fully decentralised approach. This change aims to empower different business domains to become more agile and independent. As a result, many organisations have transitioned from a single-vendor analytics platform to a multi-vendor approach, leveraging the strengths of each vendor for different phases of their data management chain (e.g., ingestion, processing, storage and serving). In some cases, we can select tools and vendors at the use case level (e.g., LLM models and other AI services).
Today, the challenges associated with analytics platforms can be summarised in one question: is my organisation and data platform ready for AI/GenAI?
Are we able to join and correlate data from different domains, despite silos? (e.g., network data with customer data)
Is my data of sufficient quality to support AI and automation models, and generate confidence in the results?
Can we extract more insights from data repositories without compromising privacy and security regulations?
How can we deliver data-driven business cases faster?
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Celfocus aims to build the foundations of a data-driven organisation by making data easy to ingest, consume, share, manage, and use across various use cases. The data ecosystem includes all components — applications, code, and infrastructure — used to collect, process, and store data in platforms like Data Lakes, Data Warehouses, and Lakehouses.
The answers to the challenges mentioned above can vary, and this is where Celfocus positions itself: as a partner that, through a collaborative approach and a co-creation model, supports organisations on their path to becoming data-driven.
“Besides having recognised technical know-how, Celfocus’s approach and pragmatism were fully in line with Hiscox’s expectations. We also discovered many organisational similarities between Hiscox and Celfocus. All this significantly influenced the decision to choose Celfocus as our partner in the first place, but it’s also something we affirm today.” Bernardo Gomes Head of Data at Hiscox Europe in Hiscox Cloud Data Ecosystem Case Study.
To this end, Celfocus focuses not only on providing the technical capabilities necessary to face these challenges, but also on actively contributing to a cultural change within organisations. To fully leverage data-driven decision-making, automation, and AI, organisations will need to adapt accordingly.
Following a composable architecture, the business case influences the selection of the data ecosystems components, considering business agility, scalability and cost optimisation.
At Celfocus, we prioritise decentralised data access over a central data management approach, ensuring that we put in place the right data service mechanism that allows access to data in the expected format and performance at the first stage. We help customers implement diverse interfaces like sandboxes, semantic layers, automation, and data-as-a-service, enabling data to be used programmatically, for automated actions, or for monetisation.
Just as important as how we serve data is how we govern it. The democratisation of data is important and requires several capabilities to be successful:
Celfocus accelerates project implementation by combining best practices and previous experiences through Celfocus’ frameworks and DataOps approach as a distinctive value proposition.
Frameworks and Accelerators - these frameworks act as accelerators, allowing projects to be delivered with greater quality and speed. These frameworks cover:
Evaluate processes, tools, and roles. Identify architectural approaches to correlate domain-driven analytics platforms and support digital channels and marketing campaigns (e.g., data mesh principles, data fabric).
Develop composable solutions focused on generating impact quickly, efficiently, and scalability. Deploy on-prem or in the cloud, promoting open formats and reducing lock-in.
Improve customer experience and meet customer expectations by implementing streaming processing, CDC, and event-driven architectures.
