We all know what comes after that statement. The ark of the covenant is boarded up and wheeled into some massive warehouse filled with who-knows-what-else. That’s the end of Raiders of the Lost Ark. The ark is never to be seen again except in a few easter eggs in the 4th Indiana Jones movie.
We use that analogy quite a bit, but it fits. It fits for a data consulting firm whose mission is to bring out the best in data. For some, that means “unhiding” data and allowing it to serve its purpose.
Scientifically speaking, the ark was probably one of the greatest discoveries in history and the government just locked it away. No interest in learning its secrets whatsoever. It’s the same with data. Imagine if you come across some genuinely useful pieces of data. It could perhaps provide insights into a product or app you run. Or it could be extremely useful to your company. Then, you just hide it away. You store it. Maybe it’s stored for later usage. Maybe the higher-ups are just off the importance of data. Instead, they are more interested in technological improvements and throwing money at that instead. Oh hey, that sounds familiar, doesn’t it?
The point is, we should be reaching a point where our first priority should be unhiding all that data. That includes whether it is for use across your organization or general public use. New data is being made at an increasingly rapid rate. You’ll likely find a few pieces of info that are useful to you (especially if you made it yourself. So why hide it? We will now show you how to unhide data through the supply chain, a few tools and techniques that “unhide” data very well, and some general tips.
Data Supply Chain
We have all heard of supply chains in the context of manufacturing, for example, but what exactly is a data supply chain? It is something we’ve gone over in previous pieces before, but let’s offer a quick refresher. The data supply chain is a lifecycle for data that basically propagates and procures data on behalf of the corporation. It basically looks at data, the inputs and outputs of data across the company, across systems, across platforms, across organizations and really manages it as an asset. Arguably, step #1 of unhiding any kind of data is taking it out of hiding and treating it as an asset.
To further refresh people on the basics of the data supply chain, there are three parts to it. First, the supply side, where data is created and captured. Next, management and exchange, where you improve the data. Finally, the demand side, where you utilize, consume and leverage data. This is where data must be taken out of hiding. In today’s information driven world, there is a constant demand for data for various reasons. So, if you are a “holder” of data, you have a responsibility to utilize and leverage it. Or in this case, unhide it.
However, it is also very important to enrich and improve data before you unhide it. Hence the reason the management and exchange section of the supply chain exists in this context. And there are several tools that help you manage, exchange and leverage that very data. First, as a side note, a quick look at the data lifecycle and the steps involved
The Data Lifecycle
- Generation or capture: In this phase, data comes into an organization, usually through data entry, acquisition from an external source or signal reception, such as transmitted sensor data.
- Maintenance: In this phase, data is processed prior to its use. The data may be subjected to processes such as integration, scrubbing and extract-transform-load (ETL).
- Active use: In this phase, data is used to support the organization’s objectives and operations.
- Publication: In this phase, data isn’t necessarily made available to the broader public but is just sent outside the organization. Publication may or may not be part of the life cycle for a particular unit of data.
- Archiving: In this phase, data is removed from all active production environments. It is no longer processed, used or published but is stored in case it is needed again in the future.
- Purging: In this phase, every copy of data is deleted. Typically, this is performed on data that is already archived.
Regarding “unhiding” data, steps 2-4 arguably fit the most, especially in the context of the data supply chain. The maintenance phase is where data is processed prior to use. In other words, it is being enriched and improved so that it is ‘rightfully’ in demand from users. Afterwards, the “Active use” and “Publication” steps are where data is made available to inside and outside the organization. In other words, organizations unhide and then proceed to leverage their data for a variety of purposes. Now that we are through this refresher, let’s take a look at some of the tools and techniques that help unhide data.
First, we’ll go over a few tools that either helps unhide your data or create data that should not, under any circumstances, hide.
A CRM system helps businesses keep customer contact details up to date, track every customer interaction, and manage customer accounts. It helps businesses improve customer relationships and also Customer Lifetime Value (CLV). Arguably the most notable version of a CRM is Salesforce.
This is a fantastic tool for unhiding a very specific form of data. Depending on the type of CRM, it allows organizations to view detailed information on their customers, contracts and orders. The project write ups we put on our website? All of the content from those writeups comes from data unhidden thanks to the use of Salesforce.
A data catalog is a detailed inventory of all data assets in an organization, designed to help data professionals quickly find the most appropriate data for any analytical or business purpose. Data catalogs themselves already unhide data in the sense that they inventory all data assets in the organization. Data professionals within these organizations take it a step further. They leverage appropriate data for whatever required purpose. In other words, the very act of a data catalog is part of the maintenance and active use steps in the data lifecycle. Meanwhile, selecting and using the appropriate data from this catalog is the publication step in that same life cycle. It all comes full circle, doesn’t it?
Now, we’ll go over a few techniques that help in unhiding data.
Gamification is the use of game elements in non-game activities. Typically, employing gamification can enhance customer and employee engagement, boost sales, and cut costs. Some examples include the concepts of countdowns (having a limited time to complete a task), achievements (rewarding a proverbial ‘badge’ for activities), etc. You can typically find gamified elements in special events like sales or rewards programs that basically turn consumer activity into a game.
Of course, that’s what gamification does on the consumer side. Imagine how useful the data that actually results from these efforts could be. Imagine how much a company could learn from that data. It seems like a waste to just forget about it, right? Well, that’s because it would be a waste. Gamification, much like many other tools and techniques, can provide fantastic pieces of data that could prove useful to an organization. In other words, what’s the point of gamifying if you’re just going to hide what results?
Data Score and Maturity
Data maturity is the extent to which an organization utilizes the data they produce. The more they do with their data, the more data mature they are, and consequently the higher up on the maturity scale they are. Meanwhile, you compute data quality scores based on quality dimensions for each individual column in the data set. Then, you calculate a combined quality score for the entire data set. The combined score is an average of the scores for all columns.
In other words, unhiding and actually using data is good for organizations.
Don’t be like the government. Don’t board up your proverbial ark and wheel it away. The more you use data as an organization in today’s information-based age, the better off you’ll be. Furthermore, strive for quality data that can give you a decent data quality score. Know that you benefit from using your data, and know what quality data would most benefit you as a group.
Data enablement is an active means of data management that relies on defined and enforced data policies. It provides the real-time ability to deploy automated and active data validation, classification and management. This also comes with complete and visible data lineage and associated metadata. In other words, it’s just the management phase of the data supply chain, and the active use phase of the data lifecycle.
More importantly, by creating these defined and enforced data policies that help validate and classify your data, managing it better in the process, an organization is left more confident in unhiding that data. To look at it differently, do you show someone a finished product validated and ready, or something that is incomplete. The final draft of a story or the first draft? That is data enablement, and that is its importance as a trick in unhiding your data.
Unhide Your Data. If Done Right, It’s Very Cool
You’ve got the tools and tricks. However, which ones do you have at your disposal? Do you have access to a CRM? What about a data catalog that’s been building up data over who knows how long? What kind of techniques can you readily use? Does your organization benefit from using gamification techniques? Data enablement? There are many great usable tools and techniques. Now find which ones are right for you.