Getting The Most Of Your Data With Data Management Strategy
As consequence of doing business in 2018, more data is being generated than ever before. This can cause significant upheaval in network infrastructure and device management, as well as requiring a substantial investment of both time and money.
Larger organisations that already put it to good use report heightened productivity, better optimisation, and a considerable return on investment. The business case for smaller companies is becoming more compelling, but despite the positive advocation of a big data strategy, a considerable percentage have yet to commit fully. This often comes down to not having a workable management strategy in place, so how can you change this process?
Immersing your business into the world of big data can be a daunting task, especially if you’re opening yourself up to new data streams for the first time. To stop yourself feeling like a fish out of water, your first step should be to map out the requirements you expect from the data you’re collecting. You may require the information to make decisions about business expansion, or monitor your performance in a given territory. But, one thing’s for sure, you’ll need to be 100% happy with each decision. If you plan to use data to support these decisions, including this in yourdata management strategywill ensure you won’t miss out on any vital information.
In setting out each requirement, particularly those that demand a significant investment from your business, you’ll want to receive a positive return. However, something I’ve learned is that data analysis can actually tell you what you already know, and on some occasions the results aren’t always pretty, but it does make you face the brutal facts.
Some people tell you to go with your gut feeling, but from experience, when there is data that can backup a decision, it’s always best to do thing scientifically. And that’s about going out and aggregating structured and unstructured data from all possible relevant sources and placing in a data lake (a storage repository) that we can analyse. This yields not only the results we require, but also hidden patterns and new information that can help us in the future. On occasion, the data validates what our gut and experience told us, but every time having the right data on hand to back up the decisions and visualise the next steps becomes a vital part of the process.
Most companies will start with small-scale big data projects, with low initial outlays and a quick ROI, and typically you’d measure success as increased sales, profit or savings.
