The buzzwords “big data” have been around for a few years. Simply put, it refers to extremely large amounts of information. As this data grows in quantity, variety, and complexity, it's vital to manage it appropriately. Doing so lets you preserve its quality and integrity while also facilitating access and discovery.
This article will teach you about data management best practices and why you should care about them. Let's get this party started.
What Is Data Management?
Data management simply refers to the process of taking care of data throughout its life cycle.
It entails planning and developing systems to ensure proper gathering, storage, security, and retrieval of data. The goal of data management is to manage data quality and integrity while simultaneously enhancing access and discovery.
All steps of data processing—including collection, analysis, and long-term storage—require proper data management.
Importance of Data Management
Why is this such a big deal?
- Data management is critical in an organization because it looks after the data throughout its life cycle.
- Users can find and use correctly handled data easily. For example, they can find managed data in the right catalog or folder and anyone who wishes to access that data will know which particular folder to find it in.
- Managed data assists organizations in making informed decisions about how to build their businesses by providing insight—simply put, if managed correctly, the data can drive the business to make smart decisions.
- Managed data enhances trustworthiness. This means that all the data comes from the right source and there isn’t any unreliable data.
Now that you know the importance of data management, let's get into some specifics that can help you.
Naming Conventions and Organizing Folders
Name files and folders with descriptive and unique names (in other words, avoid having many files or folders with the same name). Make the names concise and reflective of the file's content, so that anyone who wants to access the file or folder can understand the name. Even if someone finds the file outside a particular folder, its name should define its content.
Look at the names of the two files below. Which one is more comprehensive?
- price_data_analysis_for_2022.txt
- price_2022.txt
We can see from the above files that price_data_anlysis_for_2022 is more understandable than the other example. The name of the file indicates what the file contains.
Having a descriptive naming convention is a key aspect of data management that you should always keep in mind. It allows for quick data access and discovery, and that makes life easier.
Best Practices for File Naming
Let's get into some specific tips that'll help you get into the habit of naming files in a helpful, useful way.
- Don't use special characters in file names (e.g. #, $). Those characters have special meanings for the file system. If you wish to know more about this you can click here.
- Use camel case when creating file names, (for instance, PriceTag.txt) and the underscore character (price_tag.txt) to aid readability.
- Be descriptive without going overboard - maintain readability by keeping file names short.
- Provide a version number in the file name. For example, price_sales_v2.csv tells the user accessing it that other versions of the files exist. Consider for instance, that there are four versions; user will know that v4 is the latest version and whenever the user wants to roll back, they can easily go back to find an earlier version name).
Best Practices for Folder Organization
Structure data in a specific way to make it easily available to whoever needs to access it. Some of the best practices include the following.
- Make sure folder names are consistent. That is, they should be related to the name of the files contained in them. That way, when someone else needs to access a file, they can instantly recognize where it is with just the folder name.
- Put your folders in appropriate locations that others can predict. Putting a folder in a directory where that others can predict is a bad idea. For example, putting a price sale folder in a music folder makes no sense.
Metadata
Metadata, or data about data, describes summary information, or characteristics of the data. Think of metadata as documentation that explains in detail what the data includes. It describes, explains, locates, or otherwise helps people find, use, and manage information resources. Examples include who created the data when and dates the data was modified.
Always include the following in metadata:
- Its creator or author
- The title of the project
- The creation date
- Rights for reuse (also referred to as a license): You should attach a license to the file, authorizing, for instance, whether it is freely available to everyone and whether users have permission to modify it, versus data that’s proprietary to your organization and with no permission for users to modify it.
- An overview of the columns and fields in the data files: You should explain what each field in a file means. For instance, you may have an excel file that contains column names that users accessing it find ambiguous. You should explain the names in your metadata.
Best Practices for Metadata
Just as with file names, you should make metadata best practices a regular habit.
- Include a description of the data file's content. As stated above, explain all column names in the file so the user accessing it can understand them.
- Describe the format of each data type in the file, for example, date formats and time formats.
- Define any parameters contained in the file, as well as the units of measure.
- Identify and explain any missing values in the data.
What's the benefit of these best practices for your team? Properly describing metadata gives anyone an overview of what the data comprises, removing the need for the person accessing it to waste time trying to figure it out.
Storing Backups
When you're dealing with data management, this is an important step to take into account. It's a step that makes data discovery and accessibility easy. You'll need solid storage and a backup strategy for as long as you’ll need to access the data.
There are a few backup storage options that you can use to keep your files safe. Some storage options have limited capacity and some can be expensive. But which you use depends on your organization’s preferences.
Here are some of the options.
- Network drive
- Cloud storage
- External storage devices (flash drive, external hard drive, and so on)
- Local storage (the storage on your computer)
Best Practices for Storing Backups
One of the best strategies when dealing with backups is using the 3-2-1 methodology.
3: Keep at least three copies of the data.
2: Store two copies locally, each on a separate medium.
1: Store at least one backup copy offsite.
You’ll find this approach incredibly effective, and it's one of the most widely used practices for keeping data safe.
Opt in for Quality Data Management Software
Using good data management software helps ensure that your information is well-maintained, and safe. Good software can extract, clean, transform, and integrate data from a variety of sources without compromising its integrity, making it easier to access and use.
There's a lot of data management software out there. An example is Panoply, an all-in-one cloud data platform that makes it easy for analysts to sync, store, and access their data. Panoply can help you achieve important business goals, including data integration, warehousing, and virtualization. You can sign up or check out their blog.
What's the benefit of this best practice to your team? Because Panoply is a cloud-based AI platform, the team won't have to spend as much time manually managing data. Panoply can improve the efficiency and speed with which the team completes their tasks.
Conclusion and Learning More
Data management has become crucial to our personal lives, as well as to the lives of enterprises. Individuals and organizations benefit from properly managed data since it allows them to obtain insights and make better decisions. Taking into account all of the aforementioned best practices makes your data more discoverable, accessible, and secure. If you want to integrate all of your data from numerous sources, save all of your raw data, and create all kinds of metrics from it, you can request a Panoply demo in order to get started. Thanks for reading.
This post was written by Ibrahim Ogunbiyi. Ibrahim is an entry-level IoT enthusiast and a machine learning engineer with skills in python, C++, data analysis, data visualization, and machine learning algorithms. He is also a technical author.
