This guide outlines how to implement data fabric solutions in your business, with the best practices and key strategies to follow.
Your business is fat with data. If you have data literacy and can use that data effectively, then it’s just the fuel your organization needs to rocket forward beyond your competition. If it’s sitting there in storage, however, it’s just bulking up your operations and making it difficult to get clear, actionable insights.
So, what do you do? You implement a data fabric solution.
Not sure what a data fabric is? No worries, as this guide will cover everything there is to know about data fabric solutions, as well as the best practices and strategies to successfully implement it into your enterprise:
Data fabric solutions: overview
Understanding the meaning of data fabric can be challenging, as there are many alternative terms, such as data management, that one might use instead. So, how does data fabric stand out from previous approaches?
Let’s break it down. Data fabric’s goal is to bring all your data, from wherever it may be, into one single silo or source of truth.
The goal is to then sort and structure that data so that it is primed and ready for advanced analytics and AI. Once you’ve implemented data fabric solutions in your enterprise, you’ll be able to better manage all of your data, faster, and even for less.
Currently, it’s estimated that 80% of all the data we have in the world is unstructured. Data fabric solutions are the first step in structuring this data, and then using it. Think of it as a comprehensive data management approach that works best for enterprise or international brands. Also read more about utilising a virtual data room (VDR).
Data fabric solutions: best practices and strategies
Every data management approach needs a strategy behind it, and the same holds true for your data fabric. If you don’t know what you need your data for, or even where all of your data is, then you are going to end up with a reactive strategy that feels more like putting out fires left, right, and center than making progress.
To help you be proactive and smart about implementing a data fabric solution, you should follow these best practices and strategies:
1. Start First with Understanding Your Business Requirements
Organizing data sounds like a solid plan, but once you start considering the sheer number of ways that you can organize it, things can start getting tricky. That’s why it’s so important to start working with your internal teams (notably marketing, sales, and operations) to help understand what their priorities are with data analytics, and what challenges they’ve faced in the past.
Identifying critical business questions in advance allows you to craft a roadmap that works with your business objectives, while also paving the road for improved data governance and even data analytics.
2. Take Stock of Your Current Data Landscape
The next important step is to fully understand where all of your data is. Conducting a full inventory of all your databases, data warehouses, ETL processes, and more can take time.
You will need to be particularly diligent when it comes to checking if there’s any outdated or unused software that has legacy data backed up in it, as that information is important for delivering predictions, but it’s also at the most risk of cybercrime. By having a full inventory, you can then subdivide the data ingestion process into steps without missing a beat.
3. Develop Your Data Fabric Architecture
Now that you have a clear strategy in place and know where all your information is located, it’s time to build an effective data fabric solution. This solution needs to easily handle data ingestion, storage, processing, analytics and governance.
This is a lot to ask, which is why it’s a good idea to head to specific data fabric solutions, rather than try to adjust your current data storage system to work as data fabric architecture.
4. Implement Data Governance
You’ll need to adjust your data governance and security from this point onwards. Start first by encrypting the connection between your other systems and your data fabric. This is known as encrypting in transit, and it means that hackers cannot make sense of data as it’s being transferred into your data fabric.
You’ll also want to implement user access controls as soon as possible and install firewalls to protect your data while you work on removing redundancies and compiling historic versions.
5. Use a Data Warehouse
A data warehouse is a tool within the data fabric umbrella, and it’s essential for when previous or historic versions of reports help your brand with analytics and trend tracking without cluttering up your interface.
A data warehouse, along with a full-scale metadata strategy, can help minimize the amount of repeated information while also prepping your system so it’s easier for every team to find the data they need, and for analytical and AI tools to understand your info, process, and use it.
6. Take Your Integration Step By Step
Working with incredibly large datasets, especially when that data may be spread out across physical locations, as can be the case with international brands, you want to work in segments.
Start first with the core data you need in your day-to-day operations. Only once it is fully integrated into your data fabric architecture and organized properly should you move on to your social media analytics information, for example.
Segmenting your approach this way allows you to keep on track with progress and improve monitoring.
7. Train Your Staff
If you want the integration process to go smoothly, you need trained professionals who understand what they are doing and how to do it on your side. You can do this by working with data fabric specialists or using the right tools and training internal staff.
Either way, providing the training, documentation, and ongoing support to whoever is in charge of the transition is going to limit mistakes and improve the end result.
Final notes
A well-organized, secure data fabric architecture is essential for the future of your business, but that doesn’t mean it’s a straightforward or fast process. Take the time to fully plot out your strategy, build your architecture, and train your staff so that the process goes smoothly.
