10 Best Practices for Data Management

To ensure that your data is secure, complete, and accurate, use this checklist to make sure you have what you need.

Introduction: Do you struggle with how to create, organize, and maintain data in your business? If so, then this article is for you! In this post, we’re going to provide you with 10 best practices for data management. These best practices are the result of our experience working with hundreds of clients who have struggled with the issue of how to organize and manage their data.

You’ve likely heard that data is a critical part of any modern marketing plan, but how much data do you really need? Here are 10 things you should know about data and data management.

1. Create a Vision and Mission Statement for Your Data

A Vision and Mission Statement for your data is exactly what the name says: it’s a vision of how you want your company to look in the future, as well as what you’re trying to achieve today. A Vision and Mission Statement for your data will also help you better visualize and explain the purpose and structure of the information you collect.

When you know what your organization is all about, it’s easy to understand the value of your data. You can then develop an easily-understood vision and mission statement to make the case for your data to your audience. For example, a university’s vision could be, “We will create a knowledge economy and help our students, faculty, staff, and alumni develop lifelong learning skills and gain employment in growing industries.” A marketing department’s mission might be, “We will make sure our clients’ customers know they are making a valuable investment by purchasing our products or services.”

2. Implement an Enterprise Content Management System (ECMS)

What is ECMS? An Enterprise Content Management System is software designed to help manage all types of content, from text documents and spreadsheets to videos, audio files, and even web pages. This content can then be accessed by any device (or person) anywhere in the world. ECMS tools are typically used by larger organizations—corporations, governments, and educational institutions.

ECMSs allows companies to centralize their data, which allows employees to search and find the information they need more easily. A content management system will also enable users to create, edit, share and collaborate on documents, spreadsheets, presentations, and other forms of information.

3. Design a Data Classification Scheme

The first step in designing a data classification scheme is to think about the various types of data you want to classify. Once you understand the purpose of the classification, you can choose the right set of characteristics that describe each class and assign them to your data. This exercise is crucial because it helps you define your data classes before you start analyzing them. You need to have these classes before you do any visualizations because the classes become the frame of reference for all your visualizations.

4. Define Data Policies

You need a standard operating procedure for data governance. Data can be shared with employees, partners, and suppliers. The company needs to understand what kind of data it collects and how it handles that data. Also, make sure that there are policies about when data can be deleted, shared and how that data is stored.

Data policies are a set of rules that guide how your company handles data that it collects from visitors. Data policies can be as simple as a statement like “we don’t share user data with anyone outside of our company” or as complex as “we only keep data collected from active users for six months and delete all the rest once the user stops being a customer.”

5. Secure Data

With data breaches, ransomware, and the increasing use of mobile devices, securing your company’s data can be a challenge. At a minimum, it’s important to implement a data loss prevention (DLP) strategy. This involves taking the following steps:

1. Establish a set of policies and procedures for user access to information resources
2. Ensure that employees are aware of what type of information is available on an organization’s network
3. Determine the appropriate level of authentication for user accounts
4. Use a multi-factor authentication approach, including tokens or biometrics
5. Use encryption software to protect email messages
6. Monitor network traffic for suspicious activity
7. Provide end-user training in securing company data
8. Review all employee laptops and mobile devices
9. Use the latest operating system to help prevent new vulnerabilities from being exploited
10. Perform regular backups of company data
11. Make sure that there are adequate levels of physical security measures
12. Perform regular penetration tests and vulnerability scans
13. Be vigilant in monitoring social media sites for possible threats
14. Use a DLP solution
15. Use a secure communications application (e.g., encrypted e-mail, secure instant messaging)
16. Use a strong password policy
17. Use a VPN or virtual private network (VPN) service
18. Conduct regular penetration testing of network infrastructure
19. Train employees on best practices for the use of mobile devices
20. Use mobile device management software to help protect the enterprise

6. Standardize Data

Every business that does any kind of data analytics must face the same challenge: There is no single standard for how to store and organize data. It’s a major pain point for everyone in the industry and one that many companies choose to ignore. The problem is that data can be stored in multiple formats, making it difficult to pull together the right pieces of information and that it’s not always obvious which format your company should use.

At this stage, I’m going to try to standardize the data I collect. There are three reasons to do this: First, it’s a lot easier to look at trends when everything is consistent. Second, I want to make sure that all of my metrics are consistent with one another. The more metrics you have, the more opportunities for error. Finally, I want to start tracking the data that I can use for future blog posts.

7. Manage Data Access Control

Data access control (DAC) is a powerful tool in helping you control access to your data, and prevent people from abusing the data you share with them. As more and more organizations start to use data analytics to make decisions about business practices, the amount of data that’s available to them is growing. This increase in data means that it’s getting easier for employees to look at that data, which can lead to problems. A good way to help protect your company is to implement a robust data access control system.

To make sure your data is secure and accessible, you should have some method of granting access to others who need to be able to use it. The methods you use for granting access will vary depending on how your app is designed, but in general, there are two methods: public or private. In the case of the latter, users can share their data via the application (e.g., Twitter) and only those who share with them will be able to access their data.

8. Store Data on the Right Media

You need to collect and store data. This is a big part of analytics. If you’re not collecting data, you’re not going to be able to draw conclusions from it. But collecting data doesn’t end there. It needs to be organized, categorized, and analyzed. Without analysis, no one will ever understand the data that you have.

If you want to know which media are performing the best, store your data in the right place. This includes the right medium as well as the right time period to measure your data. A month’s worth of sales is not enough time to accurately represent what happened at a particular moment, says Tracy. A day’s worth of data is also not enough to represent how a product performed across the entire marketing funnel.

You can use media in the way you would normally use a database, but this time it’s your media, your data, your insight. The big challenge here is to understand the value of the insights you have and make sure the media are being used correctly.

9. Retrieve Data from the Right Source

When data is stored somewhere, you can access it. In other words, if you want to use the data that was collected at a certain time, you need to find where it was stored and then get it out. This is the first step of any kind of data retrieval.

The key to getting data is to get it from where it’s stored, and then access that data through the right source. This may seem like a simple concept, but it’s an often-overlooked piece of e-commerce strategy. If you don’t retrieve data from the right place, you won’t be able to present the right message to the right audience.

We often find ourselves in situations where we need to retrieve data from an external source. The first question to ask yourself when you encounter one of these challenges is, “How will I know if this data is accurate?” It’s a good idea to double-check the data you’re using before making any major decisions.

10. Preserve Data for the Long Haul

There’s a reason why some businesses are better at managing data than others. The reason is that they know how valuable it is to preserve data for the long haul. The goal here is not to build a new business, but rather to grow an already existing one. What is your customer data worth? How much value can you extract from that data? That’s the goal here—extracting as much value as possible from your customer data.

When you’re building your digital brand, it’s important to consider how data collection will play out in the long term. For example, when someone signs up for a newsletter or subscribes to your blog, you can use the email address to follow up with them and build a relationship with them over time. By collecting their data and allowing them to opt-in, you’re giving them the opportunity to be part of your future marketing plans.

1. Create a data strategy, then execute it.
2. Don’t forget to back up.
3. Test and refine your data models as you go.
4. Keep your data clean and free of errors.
5. Know where your data comes from and how it will be used.
6. Document and share all your source data.
7. Make sure you have enough storage space.
8. Keep your data safe from loss.
9. Monitor the performance of your databases.
10. Set up backup schedules for your data.

In conclusion, Data management is the act of processing and organizing data in a way that ensures its integrity, accessibility, security, and usability. If you need some guidelines on how to manage your data, check out my post about Best practices for data management.

In order to get the most value out of their data, businesses need to understand how to manage it effectively. Here are 10 tips to help you on your way.