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Data Management in times like these

Atualizado: 4 de jan. de 2022

The Covid-19 global pandemic is having a big impact on our lives and businesses. At this time, companies cannot rely on historical data for correct predictions, yesterday's models are not prepared for today's data, and is challenging data strategists.

In times like these of increasing uncertainty, businesses still need to analyze numbers and trends, gain insights and make decisions. Actually, they need to make quicker and better decisions with a higher level of risk, which demands more quality data and faster.

Many organisations have been accessing data, based on highly structured warehouses and more fluid lakes, which depends on a physical infrastructure with a powerful local or remote storage, secure networking and powerful workstations with multiple, large visual displays for data scientists. But, today, due to coronavirus, (many of us are still) are working remotely and that changes everything. The heavy-lifting processes are now widely distributed, we are working with largely unsecured home offices on public networks, with lower network capacity and poorer hardware.

A cloud-centric data strategy business is now in a stronger position, with a highly distributed and widely accessible from office or home.

The focus for digital transformation very soon will be a matter of basic survival. We already saw in the last month analytics turn its models away from predicting customer satisfaction or upselling to optimizing production, overcoming logistics and distribution.

Real-time data may be limited to areas with real-world impact and value, instead of instant gratification of consumer desires.

Another implication is about privacy, where some concerns may have to be put aside in favour of disease tracking and patient management needs.

Other implications are still emerging because this is not a sprint is a marathon, but with no doubt is a good time to reassess your data strategies.

by Tânia Espinheira

Design & Marketing Manager @Passio Consulting

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