What is Dormant Data?
The more data you have at your fingertips, the more potential for insights. But you can only get those insights if your team has the ability to leverage your data.
In this article, we'll talk about what dormant data is, the risks of underutilizing your data, and what tools you can use to help your team wake up your data.
What Is Dormant Data?
Dormant data (or dark data) is any data that a company generates and collects but then does not analyze or process for insights. Dormant data is often unstructured and unmanaged.
Many organizations have a surplus of data but a shortage of insights. Data isn't helpful if it's stashed away in a dark corner of a database or program, never to see the light of day.
IBM estimates that 80% of all data collected is dark data. This data is often part of regular business processes and is held onto for various reasons, including compliance.
This dormant data can live in many places, including a cloud or local storage system. You could also classify data used in operations and stored in their respective homes, such as design programs, project management software, and customer management software, to name a few.
Why Hold On To Dark or Dormant Data?
Data has no direct value in isolation, but it does have undiscovered potential if your team can capitalize on it.
“There’s an enormous amount of data that is being collected and created, and the world is just connecting even more. There are new, cheap open source systems and sensors available that collect data, make it available, and it yields amazing insights that we can use to become more efficient. We can work smarter. We can be better in the way we plan, design, conduct our business, [and] monitor and learn from our projects operations.”
Valbak Aardestrup - Vice President of business development and strategic programs at AEM member company Trackunit, during AEM’s most recent Product Safety & Compliance Seminar.
In Splunk's report, The State of Dark Data, more than 80% of respondents say that more than half their data is unused, but it is also potentially valuable. There is an existing rich pool of information waiting to be explored.
So why is this information so underutilized in the first place? Let's explore some reasons this data may not be tapped into.
4 Reasons Data Remains Dormant.
Data is most effective when everyone has the ability and skills to access this data for insights. However, organizations lack the internal culture and structure to facilitate data exploration. According to Splunk, some of the top barriers are lack of skills, resources, and coordination across departments. But there are reasons this type of culture and lack of collaboration exist, and it starts with operational barriers.
1. Technology & tools are too complicated.
Data pipelines are created to extract data from its source and process it for usable insights. To create a data pipeline, you need specialized tools. Conventional data pipelines are created manually, and require more than one specialized tool as well as coding experience, especially when connecting various sources.
If you don't have tools that your team can use to create a data pipeline and explore insights, data will continue to be dark and unexplored.
2. Data is something someone else does.
For most employees at organizations of any size, data is still something that someone more specialized does for them- like a dedicated data engineer, data analyst, or operations manager. This is due to the complexity of the tools used to create a data pipeline and perform the analysis.
According to Splunk, there is nearly universal belief (98%) that data skills are important to the jobs of tomorrow, and 83% agree that workers who continue to rely on others to explain what data means will fall behind in their careers in the future.
3. Data requires context to be meaningful.
Even if specialized tools and staff are available, data insights require context. Simply feeding data to an analyst doesn't mean they'll be able to use it or explore it with the correct context. While this staff may be very technical, they do not necessarily understand the key pieces of information their colleague or end user needs.
Additionally, individual departments will collect data for their specific reason and their particular requirements. Disconnection among departments can result in duplication of data or disconnected data.
4. Complicated data exploration creates workflow disruption.
If data is unstructured, then it needs context and collaboration. Yet, creating these insights with insufficient and inaccessible tools can result in workflow disruption. Teams may not find enough value in providing the necessary context and time because each insight is difficult to set up and collaborate on.
The Costs of Dormant Data
If getting to data can have so many barriers, why do organizations care about their dormant data?
Missing valuable business insights.
Unstructured, unused data is a pool of potential. Increasingly, organizations want confidence and insights with data-driven decision-making. By placing barriers to data, organizations create obstacles to success.
By tolerating dormant data or not setting up teams for success proactively, you risk slipping your culture into a compliant one that makes decisions based on the most readily available data instead of having the space to dig into meaningful insights.
Expense & environmental impact.
The costs of dark data include loading, updating, storing, and managing unused data in a data archive. The price of personnel time, storage space, and CPU cycles add up. Much of the data that is being stored is now subject to compliance regulations including EU’s General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) with more regulations expanding.
You're not only hurting your business, but you're also hurting the planet with dormant data. In fact, Veritas projected that dark data would waste up to 6.4m tons of carbon dioxide in 2020 alone.
How Toric Helps You Wake Up Your Data
To wake up data, organizations are employing new software to enable less technical employees to carry out data analysis without a data expert. This is where Toric comes in.
1. The no-code dataflow replaces complicated tech stacks.
Toric brings together your diverse toolsets and data into a single workspace, allowing your team to explore, extract, share, and automate what is relevant without writing a single line of code. It is a single tool that can perform every step of data analysis using a dataflow interface that sits on top of your data, but enables you to dig into and transform your data at any step of the data processing cycle.
2. Toric enables data access & collaboration.
Toric can connect to your data wherever it is. The interactive dataflow offers several ways to connect with data and designate data types. You can drag and drop data from your computer within the dataflow or link to your data using an integration.
All data is stored in the cloud.
As you load in your data, it's all stored in the cloud. Toric’s platform can act as a data lake, meaning you do not need to clean or process your data before uploading it to Toric.
Blend, clean, transform, and analyze your data in the same place.
A dataflow diagram is traditionally a representation of how your data connects in a series of steps and programs. In a no-code environment, you can explore data differently. This feature makes it easy to view various data sources and blend them instantly.
In this workspace, you interact with your data more flexibly through nodes. These nodes enable you to get a clear view of your data. You can perform individual functions, including data blending, cleanup, transformation, and analysis- even create visualizations- at any step.
3. Provide context during data exploration & in smart documents.
Instead of switching between applications, you can provide context to your data exploration while you build your dataflow using a data app panel. As you explore your data, you build elements of your data story that you can share instantly.
You don’t have to showcase the entire project and details. Instead, use the elements you create to build pages and provide the right context to stakeholders.
4. Automate and reuse dataflows.
Automate your workflow instead of disrupting it. In Toric, instead of taking time to set up workflows from scratch, you can reuse them. Dataflows live and sit on top of your data. It's easy to create a dataflow template and replace data for consistent data flows and reports with just a few clicks so you can spend more time exploring data insights. Try it for yourself using our templates.
Dark data is a wealth of information waiting to be explored. By using a no-code workspace, you break down barriers to engage the team in data exploration and move your organization to a true data-driven culture.