Let’s get to the point about data management: Businesses need data, but accumulating too much can be detrimental. Data overcrowding can corrupt IT professionals, turning them into greedy hoarders. Being indigestible with excessive repeated, outdated or banal information, the so-called ROT data, is bad. Companies of the world! The Devil tempts you with Big Data! Something that, if too much, could be harmful! We tell you all about it in this article.

The five mistakes we make in data management

The Liturgical Department of Pandora FMS, because yes, we have a Liturgical Department, right next to the Communication Department, has counted these past weeks the most despicable and sinful faults within data management. We counted up to five sins. Relax, they are not normally committed by a single offender, they are usually mini-points accumulated, over time, by several members of a team. However, we are going to list these vices so that you can count the ones you carry on your own. The scale is this:

  • One fault committed: Sinner.
  • Two faults committed: Great sinner.
  • Three faults committed: Excessive sinner.
  • Four: On the doorway to hell.
  • Five: You will burn in hell as the Great Grimoire points its tridents at you. 

First offense:

You and your company have an ungovernable desire for data. You end up collecting an immensity of them in the hope of achieving the greatest possible advance. However, unfortunately, finding something worthwhile among such a wealth of information is like finding the broom in a student flat: a very difficult task.

Second offense:

Do you know when you have had the lunch of your life in the trendiest burger joint and despite being full, you order the dessert menu to see what cheese cake they have? Well, data excess, and the consumption of all the data you may swallow without a planned purpose, is comparable.  That’s right, without a narrow archiving process, a company’s eager urge to fagotize data ends up in a bundle of unnecessary, outdated, and useless data.

Third offense:

Greed overcomes you! And you start hoarding and hoarding, carried away by greed. In the end, this leads to spending money on more hardware, the most cutting-edge on the market, to process and store all that mass of data you accumulate. You do that instead of finding a reliable process to classify, archive, and remove junk data.

Fourth offense:

Due to the massive amount of data that you have, you are lazily and slowly carrying out your queries and your processes. Indeed, the more data you accumulate, you and your company, the more time it will take to process it and make, for example, backups.

Fifth offense:

A company can feel more secure and stable the more data it has, however, the truth is different, the more data it has, the higher the concern. Having the barrel of data completely full does not mean anything if in fact those data are not used correctly.

Recovery Point Objective (RPO) and Recovery Time Objective (RTO)

How many faults/sins have you accumulated from this list? Have you raised your hand many times yelling “Yes, I am guilty”? Well, before you burn in hell, I want to tell you that there is a plan to escape its cauldrons: find and set a recovery point objective (RPO) and a recovery time objective (RTO). Yes, sir, that’s the first step! The RPO defines a tolerable amount of data loss before a company cannot recover. And the RTO, on the other hand, marks the time that data professionals need to recover the data without getting the business in an irreparable state. To give you an idea, one of the ways to expand the RPO is to backup data logs. However, large amounts of data can make backup times too long, putting our company in a bind again. That is why there is no need to accumulate so much useless data.

Do not mistake a recovery plan with a backup plan. You should first create a recovery plan and then prepare your backup plan. The backup plan will nuance your RTO and RPO goals, while the recovery plan will address disaster recovery and high availability objectives.


Today in this blog we learned that data excess can be an indication of a failed business plan and we have exposed the five mistakes that usually cause the increase of this unnecessary data. From everything we have concluded that the best thing is to have a purpose to reach with that data and to have a manageable amount of it, thus allowing professionals to operate in a simpler way.

Money is not the answer, paying for new hardware always seems like the solution but sometimes it is just a sign that your company is not competent enough. Knowing about these problems and finding a solution can save time and money.

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