The do’s and don’ts of dark data management

As businesses become more and more data-driven, the importance of managing all that data becomes increasingly clear. But not all of that data is easy to manage. Data that is not being used, or “dark data,” can be challenging to track and understand. And because it’s not very useful on its own, it often gets ignored or forgotten.

But with the right tools and strategies, dark data can be harnessed and used to your advantage. Your dark data has a lot of potential, from customer insights to marketing opportunities.

If your business is going to make the most of its data, you need to learn how to manage dark data effectively.

Defining dark data

Before we get into dark data management do’s and don’ts, let’s take a step back and define what dark data is.

Dark data is simply any data that your business collects but doesn’t use. It’s often unstructured and difficult to manage.

This can include customer surveys, website logs, and social media data, or any other type of data. Basically, if your business is collecting it and not doing anything with it, it’s dark data.

Why manage dark data?

So why bother managing dark data at all? After all, it’s not very useful on its own, right? Wrong.

While dark data might not be as immediately useful, it can still be extremely valuable to your business if it is cleaned and analyzed:

1. Dark data can give you insights into your customers: Dark data can reveal a lot about your customers, from their needs and wants to their pain points. By understanding your customers better, you can provide them with a better experience overall.

2. Dark data can help you find new marketing opportunities: By analyzing dark data, you might be able to discover new groups of customers to target with your marketing efforts.

3. Dark data can improve your decision-making: When combined with other data sets, dark data can provide a more complete picture that can help you make better decisions about your business.

4. Dark data can help you save money: By understanding what dark data is and how to use it, you can avoid wasting money on storing data that you’ll never use.

5. Dark data can be used to solve business problems: In many cases, dark data can be used to solve specific business problems. For example, dark data can help you identify the root causes of customer churn if you’re trying to improve customer retention.

With all of these potential benefits, it’s clear that dark data management is something your business should be doing. Now let’s take a look at some specific do’s and don’ts to keep in mind.

The do’s of dark data management

Knowing the best practices for dark data management is half the battle. To help you get started, here are five things you should do when managing dark data:

1. Track where your dark data comes from.

It’s important to keep track of where your dark data is coming from. Data can come from places like social media, surveys, customer service interactions, website logs, and more.

Sourcing dark data can be as simple as setting up a system to track it. You could use a BI tool to identify which sources your data comes from.

2. Tag and categorize your dark data.

Tagging and categorizing your dark data will make managing and finding the most valuable bits of information easier.

There are a few different ways you can do this. One option is to use keywords to tag different types of data. For example, you might tag all customer survey data with the keyword “customer feedback.”

Another option is to use data categorization. This is where you put data into different categories based on its type or content.

3. Clean and organize your dark data.

Dark data can be messy and unorganized. So it’s essential to take the time to clean it up before you start using it. If you let mountains of unorganized data pile up, you’ll never be able to find the valuable insights hidden within.

You can clean and organize your dark data in a few different ways. One option is to use data cleaning tools to remove errors and tweak formatting. Another option is to use data wrangling techniques to restructure and reorganize your data.

This process will vary depending on the type of data you’re dealing with. But in general, you’ll want to remove any duplicate data, format the data so it’s consistent, and structure the data appropriately.

Cleaning your dark data can be complicated and time-consuming. But it’s worth doing if you want to get the most out of your dark data.

4. Use the right tools for the job.

There are a variety of different tools you can use to manage dark data.

Some tools are great for small data sets but are not built to handle large data sets. Other tools, like enterprise-level BI tools, are designed for big data but still work for smaller data sets.

By knowing the amount of data you have, you can better prepare to select the appropriate tool.

5. Keep your dark data secure.

Since dark data can contain sensitive information, it’s essential to keep it secure. There are a few different ways you can do this:

• Encrypting your dark data will make it unreadable if it’s stolen or accessed without permission.
• Restricting access to your dark data will ensure that only authorized users can view or edit it.
• Backing up your dark data will protect it from accidental deletion or corruption.

The don’ts of dark data management

In addition to following the do’s, you should avoid a few things when managing dark data. Here are five things you should not do when dealing with dark data:

1. Don’t try to manage dark data manually.

Managing dark data manually is a recipe for disaster. It’s simply too time-consuming and error-prone. Many companies try to manually work through their dark data sets, only to give up in frustration.

Instead, use automated tools to help you manage your dark data. There are a variety of different tools available, so find one that fits your needs. Diving into dark data can be overwhelming, but the right tools will make it much easier.

2. Don’t forget about dark data.

Dark data is easy to forget about because it’s not always obvious how to use it. But forgetting about dark data can be a mistake. For example, you might have dark data containing valuable insights you’re unaware of.

It’s important to keep track of your dark data and revisit it on a regular basis. This will help you stay up to date on what’s going on with your dark data and ensure that you’re getting the most out of it.

3. Don’t risk violating privacy laws.

Dark data can contain sensitive information, so it’s essential to be careful when handling it. If you’re not careful, you could violate privacy laws and end up in hot water.

To avoid this, make sure you understand the privacy laws that apply to your data. And take steps to protect the data, such as encrypting it or restricting access to it. Doing research ahead of time will save you a lot of headaches later on.

4. Don’t let dark data become a liability.

Dark data can be a liability if it’s not managed properly. For example, if dark data contains sensitive information, it could be a liability if it’s leaked. Similarly, with so many hybrid workers today, if you don’t manage dark data correctly, it could be a liability if an employee accesses it from a personal device.

Make sure you have a plan for managing and securing your dark data. And make sure you keep your dark data secure. A proper data governance plan will help you do this.

5. Don’t make decisions without data.

Take the time to analyze your data and make informed decisions. Making decisions based on gut feelings is a recipe for disaster. But if you take the time to understand your data, you can make better decisions that will help you achieve your goals. Plus, you can avoid potential pitfalls that could trip you up.

Use dark data wisely

Dark data is a valuable asset, but only if it’s managed properly. Businesses that learn how to navigate dark data can use it to their advantage. But businesses that don’t manage dark data properly can end up in hot water.

So if you’re dealing with dark data, make sure you follow the do’s and avoid the don’ts. Doing so will help you get the most out of your dark data and avoid costly mistakes.