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Data challenges in the world of digital transformation

Data > Insights > Decision > Action > Outcome > Value


It almost seems like an eternity when I told myself I'd steer clear of any more analytics tools. Those days data was stored on laptops or on a server under someone's desk. Manually cleaning data, checking for duplicates was such a chore as was the frustration with missing data Yet, my passion for data analysis kept me anchored. Thinking back, the challenge wasn't in the actual analysis, especially when our data sources were limited. But now, with the rise of specialized solutions, acquiring a holistic perspective, even in one department, is a herculean task.


Even after two decades of experience in Business Intelligence, I can safely say that those data challenges have not gone away in any organization. I see similar issues but in a different flavor.


1. Duplicate Data - Half a decade ago, a Marketing seminar had me believing that a 60% clean dataset was golden. Times have changed, and modern CRMs are adept at self-cleansing, identifying duplicates immediately. This is hardly a concern unless you're still wrestling with Excel sheets.


2. Missing Data - What many overlook is that a good majority of data is a results of processes, not vice versa. The absence of data often signals fractured processes or the lack of safeguards in systems to capture necessary data. Regrettably, once data is not captured, it's gone forever. The only recourse is to enhance processes or put checks and balances in place going forward.


3. Data Classification - Essentially, this means segmenting data. Due to the rapid adoption of specialized solutions, data often gets hoarded in data silos. Misclassifications can obscure patterns or insights in the data, leading to misguided executive decisions and reduced company valuation. This issue, in my opinion, has taken the lead in today's challenges with data management.


To bridge the chasm between data and its effect on company value, it's pivotal to have robust processes integrated within your systems. Equally crucial is to dismantle data silos, enabling a clear view of both the opportunities and pitfalls for your enterprise.


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