Data fabric is the new hot phrase that promises to solve all of your data-related woes, but what is it, and how can you best use it to finally launch your business into the future? The important thing to remember is that investing in a data fabric solution doesn’t mean buying a single tool and calling it a day. It’s a full-scale restructuring that requires you to think deeply about your data, how you organize it, and, most importantly, what you do with it.
You can absolutely build a robust data fabric solution for your business, but to do so effectively (and in the least amount of time), you’ll want to use this guide:
What is a Data Fabric?
Data Fabric refers to a full-scale data architecture and dedicated software solution that works to centralize all of your data by collecting it, managing it, and then governing it so that users can gain key insights and actionable recommendations from their full data set.
Rather than a database, or a data warehouse (which is a database with historical versions of documents for record keeping, data fabric works like a rulebook). This means it creates a series of integration and governance laws over all your data sources, including your databases, data warehouses, or even cloud storage. These rules let you easily and even seamlessly access and manage your data across your entire organization, no matter where the data is located, or even what format it is in.
Who is Data Fabric For?
Building a data fabric requires a massive amount of data. This means it’s a better fit for large-scale operations, particularly if you operate in multiple locations (or even countries). This makes it ideal for businesses offering services like telecommunications all the way to those operating factories and supplying businesses on a worldwide stage.
Data fabric is, in particular, useful when your data is split up and spread out across systems, cloud accounts, software and even computers. This is because it’s an essential tool that helps you collect and organize your data into destinations like databases or, in more likely cases, data warehouses.
The Problem with Data Governance Today
Saying that your data should be central so that software tools can go in and organize it in such a way that you gain deeper insights into your business is a great idea, but unfortunately, very few businesses are ready.
In a 2019 study, Experian determined that 7 out of 10 businesses were struggling to unlock their data’s true potential. Worse, 95% of the companies polled saw the negative impacts caused by poor record keeping and poor data organization. Other key issues that businesses faced when it came to using their data more effectively included information overload, a lack of trust in the data they had, and incorrect data ownership.
How to Get Started Building a Robust Data Fabric Solution for Your Business
The most important step when it comes to building a data fabric solution is collecting and organizing your data. If all the information is there, with effective metadata, then you can use machine learning, AI, and other automation tools to work with that dataset in ways you only ever hoped for in the past.
But first, you need that data to be organized.
1. Conduct an Inventory
First things first, you need to conduct an inventory of all your data. Find every server, computer, and cloud storage system and take note of where your data is, where, and when. Some of the data will be located online, for example, in your Salesforce account; others will be found directly on your computers.
2. Build a Data Silo
Once you’ve found all the data, it’s time to build a data silo. This simply means a setup that unifies and centralizes your data. However, you never want to have all your data in one place and one place only. Have a backup set of servers, or use a single cloud-based storage solution to compile your data. This way, if there’s a breach or a fire at one of your server locations, none of the data will be lost permanently. The only goal when it comes to building a data silo is that all the information is in one depository, from there it can be backed up or stored as you see fit, depending on your cycber security strategy.
3. Establish Metadata Standards
Before you start moving all that data, it’s important to add metadata. Metadata, or data about data, will make it far easier for AI and other systems to understand the content it’s looking at and, therefore, will process it faster. When creating metadata, always remember to build a standard that can be used by teams across departments so there are no discrepancies in how data is labeled. Marking up data properly is the easiest, and most efficient way to use your data more efficiently in any system now and into the future.
4. Remove Redundant Data
Once the data is all together, it’s important to go through and find older versions of the same file or duplicates. This doesn’t mean removing historical reports, but instead removing half-finished drafts or notes from your data sets. By removing these redundant files, you can save on costs, improve the efficiency of your system, and keep your data fabric streamlined.
Using Your Data
Centralizing your data is just phase one. From there, you will need to invest in tools that use that data. This can be automation tools, machine learning software, governance software, and the like. There are simply too many tools out there today to recommend any single one, as the right option for your business will be unique to your industry, niche, and business cases.
Of course, you can also develop your own toolset if you have the budget. Either way, now that your data is organized, everything will be that much easier. Organizing and centralizing your data is, after all, the first step to building a robust data fabric.
