How to handle data

Data is one of the most important things a company can own. Today every business creates and processes at least some data, and knowing how to handle it well is tricky.

Data is one of the most important things a company can own. Today every business creates and processes at least some data, and knowing how to handle it well is tricky. So today we'll look at the lifecycle of data and how to manage it.

So what's the cycle?

1.      Creating data

2.      Storing data

3.      Using data

4.      Sharing data

5.      Archiving data

6.      Deleting data

Each of these steps brings its own set of problems, and mishandling data at any stage of the cycle can lead to security issues and reduced operational efficiency — which, unsurprisingly, drives up the cost of doing business.

What are the biggest problems?

The biggest problems are the ones that can deprive you of your data, such as:

·         Ransomware attacks — As data volumes grow, it's common to prioritize newer, more valuable data over the "less valuable" stuff. That's mostly a good idea — except when "less valuable" data that you still actually use ends up improperly secured and not backed up. The simple rule is: if you use any data regularly, valuable or not, it should be backed up using the 3-2-1 rule!

·         Data corruption — Same as the previous point: BACK UP your data, because if you don't have it at least twice, you don't have it at all (and if you only have it twice, think about a third copy). Data corruption can happen at any moment. If you're using HDDs, one day they may simply die — or worse, get damaged and start scratching. Even SSDs won't save you, because they also fail after some time, often sooner than HDDs.

A slightly smaller problem that mainly hits efficiency:

·         Data volume — The trend of recent years is to collect data on basically everything that can be collected. On one hand, that's great — it can boost efficiency and satisfaction for both employees and customers, if you actually know what to do with such data and how to store it. I won't go into detail, but the main things are: pick a scalable storage method, build a system that lets you organize the data, and actually use it.