The Relationship Between Unstructured Data and Metadata
We have access to a large amount of Salesforce data. Working with the platform provides a lot of capabilities, and this creates a large set of data that can be used for various purposes.
But how do you know where to find this data? And how do you use it when you have it?
We all know the basic idea of Salesforce metadata—these structures house and identify the data stored in your Salesforce instance. But what about data that doesn’t fit so cleanly into an existing structure or system of organization?
This is what is referred to as unstructured data—information that either doesn’t fit into current organizational models or isn’t organized in any other pre-defined way.
This data, however, is just as useful as other informational sets that are structured into an organized framework. It can help with automation and provide useful insights into existing business practices.
Many businesses don’t place an adequate level of importance on their unstructured data.
This is because it exists in the background, in a way. It’s out of sight. It’s not easily found and compiled. Many businesses either don’t want to take the time to compile it or simply don’t see the benefits of doing so.
Adding structure to unstructured data might seem difficult, but it’s not impossible. Salesforce metadata plays a large role in this process.
So what benefits can come from the integration of unstructured data? And how does metadata affect this process?
What You’re Missing by Ignoring Unstructured Data
The best decisions are informed by complete and reliable data. In short, ignoring unstructured data reduces the amount of available information that can be used to drive informed decisions.
Unstructured data can come in the form of:
- PowerPoint presentations
- Geo-spatial data
- Media and entertainment data
- Surveillance data
- And more
Unstructured data is being created throughout the day. A continued failure to address unstructured data will only make the task increasingly difficult to complete.
Customer and business habits continue to increase their reliance on digital technology, which contributes the creation of more unstructured data.
The Internet of Things (IoT) refers to the items we use such as smartphones and digital assistants that are constantly updating information through sensors and software. This information is used to transfer data with other pieces of technology.
The global IoT market is expected to reach a value of 1256.1 billion dollars by 2025. This increase will directly translate to the creation of unstructured data.
Systems need to be put in place to utilize unstructured data before it grows to an unmanageable level. Information is power, especially when analyzing the current state of your Salesforce efforts. Not making use of this available data is akin to tying one arm behind your back.
You want to make use of every opportunity to gather and use information, and unstructured data is an untapped reservoir.
Challenges to Organizing Unstructured Data
By 2025, 80% of digital data will be unstructured. The continued rise of IoT will contribute to this unmanageable level of unstructured data.
The vast amount of unstructured data is one of the main challenges facing companies. The actual amount will depend on the type of company as well as how long they’ve been around. It can be anywhere from 10 files to hundreds of billions of items.
It can be difficult to wrap your mind around a number that big, let alone attempting to address each of these items.
Many of these files are shared between various individuals within a company, or even across multiple independent bodies. This introduces a necessity for governance and replication.
Establishing a framework for accountability is difficult when there is such a large bank of available data. Salesforce data replication faces the same challenge.
Other barriers to organizing unstructured data include:
- Lack of urgency
- Integration with existing data sets can be difficult
- Lack of applicable knowledge in current staff
- Insufficient tools
So why go through the work of addressing potentially billions of pieces of information?
The Benefits of Adding Structure to This Data
The ability to analyze data in a cost-effective way necessitates a functional structure. And as we said above, data that is currently unstructured can be integral to informing decisions by providing key insights.
Social media interactions, customer reviews, and more are great sources for these insights, but they are often unstructured and therefore difficult to utilize.
Creating a system that will add structure to this information will increase the accessibility of it and provide a rubric to organize future data that would have otherwise been unstructured.
This information can be used to improve customer experience. Insights into how they relate to your goods and services—as well as how they feel about these interactions—can be useful to refining your practices.
Unstructured data can also point to gaps in the current market and suggest how you can address them. Leaving this data unaddressed can result in missed opportunities and uninformed directions.
How Metadata Can Help
As we said earlier, salesforce metadata helps to house and structure your data. It is essential to categorizing and organizing various sets of information.
Unstructured data either lacks the assistance of metadata, or an available structure in which to organize the metadata.
Analyzing each piece of unstructured data can be automated if this metadata exists. This can organize the files by type, date, or a variety of other factors that make it easier to compile and analyze.
Adding metadata to unstructured data will be a bit more tedious. This should be done at the outset of the process. This can be done manually, but those with large data pools will find this to take an unrealistic amount of time.
This task can be outsourced to save on labor time and cost. The processes are largely repetitive. A rubric can be provided to inform the process of incorporating metadata to the unstructured files.
And once these files contain the appropriate metadata, they can be arranged and filed. Systems can be put in place to categorize similar data in the future so you can make use of the full potential of your data.