Why Do You Need a Data Supply Chain?
The amount of accessible data we have today is unprecedented in human history! As an organization, your focus is likely to be on how to make the most of this data.
Well, that’s where a data supply chain comes in.
What is a Data Supply Chain?
In simple terms, a data supply chain is a set of processes that convert raw data into actionable information. It revolves around the idea that data by itself is of no value to you, but it becomes a prized commodity when you collect, store, and analyze it, to get transformative insights that drive your business performance and revenue.
In this sense, data is just a component that goes through multiple stages to end up as an important insight. It’s pretty much like how a raw material goes through a manufacturing process to become a finished product that we can use.
In fact, data supply chain is defined as a set of processes that transforms the data that enters into the system into something of value that you can use, which is typically an insight or a behavioral pattern.
Broadly speaking, your organization needs four distinct processes to convert raw data into a useful product.
The first step is to identify your business goals. In other words, you should be clear on what you want to achieve by leveraging the data supply chain. This goal could be improved efficiency, better ROI, more understanding about your customers or just about anything else.
Without a set of defined goals, your data supply chain will be all over the place.
Get and Store Data
Once your goals are finalized, the next step is to get data from the right sources. Today, your data can come from social networks, websites, CRM systems and more. You’ll have to decide which are the right sources of information for you.
In addition, you’ll get data in real-time or in batches, so you need a safe and secure place to store this data.
Refine and Curate
With all your data in a single location, your next step is to refine it like adding metadata tags to make it searchable, going through it to ascertain its quality and so on. In a way, you’re preparing the stored data for analysis.
Once your data is ready, browse through it to identify patterns. It’s humanly not possible to go through vast amounts of data and identify patterns, so this is where you need technologies like big data, artificial intelligence and deep learning algorithms that’ll give you the best insights from your existing data.
Distribute and Manage
The final process in data supply chain is to distribute this actionable information to end-users. This distribution can be in the form of charts and reports and can be delivered on enterprise applications or mobile devices.
This distribution and management is completely up to you and you can decide how you to distribute and manage it.
All this sounds fairly simple, right?
In reality though, this process is highly complicated and comes with a lot of challenges.
Challenges of a Data Supply Chain
Data supply chain is anything but simple. Here are some challenges that come with it.
Data types and formats
All the data that you get from different sources will be of different data types and formats. For example, the video you get from a Facebook page is much different from the review of a user in Sacramento. So, how will you combine these different data types so they are in the same format for analysis?
Data is growing at an astronomical rate, so you need the right infrastructure to capture, store and analyze these vast amounts of data. Regardless of whether you choose a cloud or an in-house system, it is sure to entail some capital and operational costs.
The insights you generate are time-bound. This means, you don’t want to store all data forever. Instead, what you want is insights that are based within a certain period, say a few months or a few days, depending on your goals and business needs.
So, you need a set of tools that’ll keep churning out the insights you want based on the data that comes in, so the information you have on hand is the latest.
Big data is a relatively new technology, so hiring talent to develop your data solution may not be easy.
A good way to bypass this obstacle is to hire the services of a technology company like Alpen Technology Group, so you can reap the benefits without worrying about the headaches that come with data supply chains.