You May Not Need All That Tech to Make Best Use of Your Data

For organisations early in automation, choosing technology can be straightforward — selecting a data visualisation tool and building dashboards. However, enterprise-level automation requires developing a data tooling approach, thought through across people, process, and technology.

People

Before selecting tools, organisations must decide between democratising or centralising data, determining whether a centralised, fragmented, or replicated structure fits best. This choice defines whether the architecture favours end-user tools or specialised technologies, and whether to use a single controlled data platform or a more open structure like a data fabric. Early definition, appropriate hiring, and communication improve cross-functional collaboration and service delivery.

Process

Two angles matter here: understanding target business processes and how technology enables them ensures better alignment, while robust processes for data product usage and maintenance minimise disruption.

Technology

Beyond visualisation, organisations should consider technologies for data governance, data modelling, data profiling & querying, data lineage mapping, data preparation, data integration, configuration management, metadata management, reference & master data management, and data science, among others. Enterprise Architecture functions should guide tool selection; organisations lacking this capability should seek professional advice to avoid inflexible, expensive-to-redesign landscapes.