Every company needs data for various reasons, but hoarding too much data can be a dangerous habit. An overload of data can turn the average IT pro into a hoarder and lead them to obtain too much redundant, outdated, and trivial information, also known as ROT. The lust for big data can be tempting, but it’s also more damaging than companies may think.
Five sins may be great threats to security: lust, gluttony, greed, slothfulness, and pride. These five sins aren’t all committed by one individual but can be accumulated over time by several different employees. Luckily, with a cultural shift, companies can steer clear of these issues. Let’s get into the five sins and how data experts can avoid them.
The Five Sins of Data Management
- Lust: With a strong desire for big data, companies end up collecting too much in hopes of a breakthrough. Unfortunately, finding something of importance in a large amount of data can quickly turn into a needle-in-the-haystack situation.
- Gluttony: Over-indulgence in data and consuming as much data as we can without purpose is comparable to eating after we’re full. Without an archiving process, a company’s hunger for more data usually results in a hoard of outdated and useless data.
- Greed: Hoarding can be inspired by greed. Unfortunately, this usually leads to purchasing more of the latest hardware to process and store the more data we consume, rather than finding a process to sort, archive, and delete data.
- Slothfulness: While slothfulness may be equated to laziness, in data management, slothfulness is representative of slow queries and processes due to mass amounts of data. The more data a company has, the longer it can take to process data and perform backups.
- Pride: Companies may have a sense of security with large amounts of data, but the truth is the more data accumulated, the more concern needed. Having a ton of data means nothing if it’s not used properly and will lead to a false sense of security and pride for many companies.
Set Your Intentions
Finding and mapping out a recovery point objective (RPO) and recovery time objective (RTO) should be your first step to avoiding these five sins. RPO marks a tolerable amount of a data loss before a company can’t recover, while RTO marks the time data experts need to recover data without the company being in a critical or irreparable state. Backing up your data logs can help extend your RPO, but large amounts of data can create longer backup times and fewer backups overall. Detailing objectives will give your team a plan for business continuity.
Plan for Recovery First
Don’t get your recovery plan confused with a backup plan. You should create your recovery plan first and build your backup plan after. Your backup plan will take care of your RTO and RPO goals, while your recovery plan will handle disaster recovery and high availability objectives. Think about your company’s requirements for disaster recovery and high availability, and remember
they aren’t the same thing.
Archive With Purpose
A surplus of data can be a clear indication of a failing archiving plan, or lack thereof. Lust, greed, and gluttony can cause an increase in unnecessary data hoarding and can lead to an archiving process with no real direction. Having a manageable amount of incoming and processed data allows data professionals to archive data more easily and with purpose.
Put Security First
While it may seem like an afterthought, security should be front of mind when it comes to protecting your data. Keeping only the necessary data for your company means the information on hand has more value and should be protected at all costs. Follow best security practices in all areas of your company, including safety procedures with employees and their everyday tasks. Data theft can happen in various forms—not just through hackers.
Decide Between Building and Buying
Believe it or not, money isn’t the solution for everything. Buying new hardware might seem like a good solution, but it also may be a sign your company isn’t digging deep enough into existing resources and other solutions. Learning the root of your data issues can save your company time and money that would normally be spent on fancy (yet unnecessary) hardware.
