Data Fabric is a term that has been gaining traction in the business world in recent years. It refers to a collection of data management and integration technologies that are used to create a single, unified view of data across an organization. Data Fabrics can help organisations to improve their data quality, governance, and accessibility. They can also make it easier to use data for analytics and decision-making.
If you’ve been reading up on Data Fabric, you might have wondered: how is this different from what we already have?
Chances are, your organisation already has the foundations, or threads, of a ‘data fabric’ in place. Integration, analytics, data engineering, data governance, security, consumption, visualisation: as an enterprise or large organisation, your data ecosystem is probably mature enough to have many of these key functions. These layers of technologies, platforms and applications are, theoretically, a ‘data fabric’: however patchy it may be. What they aren’t is a complete Data Fabric.
There are two main types of Data Fabrics:
- Vendor-specific Data Fabrics: These are Data Fabrics that are built on top of a single vendor's platform. Microsoft's Azure Data Fabric is an example of a vendor-specific Data Fabric.
- Best-of-breed Data Fabrics: These are Data Fabrics that are built using a combination of different vendors' products. An example of a best-of-breed Data Fabric is the Agile Data Fabric.
So, what’s the difference? Why do you now need Data Fabric if you have something like it in place? We’ll answer the second question shortly, but let’s start with question one.
What’s the difference between the data fabric we have and the Data Fabric we need?
The real question you should be asking is: does our current ‘Data Fabric’ deliver tangible business benefits?
- Does it make data accessible?
- Are applications easy to use?
- Is every part of the data journey fully integrated?
- Is everything flexible and scalable?
- Does it democratise your business’s approach to data?
- Does it have all of the capabilities you want, and can it evolve as your needs change?
Your Data ecosystem
Your data ecosystem is comprised of a lot of different technologies, systems and integrations that perform different functions. Some will be used across the business, some will only be used by certain departments, and some will be reserved for IT teams and data scientists (which can be a bottleneck when it comes to making data-driven innovations and insights accessible).
These functions are all woven together, but they are scattered and often (because they have grown organically) disorganised. Certain capabilities work together, while others don’t. Some integrations are seamless, while others need manual input. Multiple data sources aren’t always connected, and there are silos throughout the business. It’s possibly littered with legacy software, too, mixed in with newer cloud-native platforms. If it were a blanket, it would be full of holes.
All of this makes it difficult to get the full value from your data. It’s harder to introduce new data projects, awkward to consume data and slow to get certain data-driven activities running.
With a Data Fabric, that lattice of different systems and technologies becomes more streamlined, fully integrated and able to deliver change quickly. It provides a unified experience, with clearly established layers that take your data from source to consumption seamlessly. It has the ability to transform how your organisation consumes data, democratising access to data to increase its value.
One of the big differences between your data fabric and a true Data Fabric is that the latter is a conscious implementation, not the result of organic growth or a series of short-term decisions. It’s carefully woven together, not tangled from years of adding and connecting new data solutions.
Does this mean Data Fabric is something I need to buy in?
Not necessarily. Data Fabric is an approach, not a product – although there are products you can buy that brings together applications and platforms from a single vendor into a Data Fabric – like Microsoft Data Fabric.
Yet you don’t have to take this approach. There are essentially two options to Data Fabric: introducing a single vendor Data Fabric, or implementing several ‘best of breed’ technologies in a Data Fabric architecture.
As we mentioned before, the threads of a functioning Data Fabric could already be in your organisation – you just need to rearrange them, close the gaps, and weave them all together into a Data Fabric that can enable you to monetise your data. You can read more about this in our guide to Data Fabric.
Why do I now need a Data Fabric?
This takes us back to our key question earlier: is your Data Fabric delivering the full value from your data?
It probably isn’t. That complex network of integrations isn’t making it easy for any part of your business to monetise data, even if you are getting results from your data. As your demands on data grow, and your vision for what you want to achieve with data becomes more ambitious, your patchy data fabric will begin to hold you back.
A Data Fabric, on the other hand, will provide you with a flexible, scalable and robust foundation that will enable a truly data-driven business.
The way organisations consume data is changing. Terms like ‘data culture’ and ‘data democratisation’ are fast changing from competitive advantages to things that every business needs if they want to compete with data, by making it accessible to the entire business. Data Fabric enables that by removing a lot of the technical complications around data and making them accessible. Meaning that your organisation is empowered to use data as an asset to add value to the business.
The benefits of Data Fabrics include:
- Improved data quality: Data Fabrics can help to improve data quality by providing a single, unified view of data across an organisation. This can help to reduce the amount of duplicate data and improve the accuracy of data analysis.
- Improved governance: Data Fabrics can help to improve data governance by providing a central repository for all data and by enforcing policies and procedures for data management. This can help to reduce the risk of data breaches and ensure that data is used in a compliant manner.
- Improved accessibility: Data Fabrics can help to improve data accessibility by making it easier to find and use data across an organisation. This can help to improve decision-making and innovation.
- Increased agility: Data Fabrics can help to increase agility by providing a platform for rapid data integration and analysis. This can help organisations to respond more quickly to changes in the market.
How do I implement a Data Fabric?
If you’re looking to introduce Data Fabric, the first thing to do is identify the business outcomes that you want to achieve and then identify the gap between your ‘target’ and your current ‘reality’.
- Look at what you have: you might have most of the aspects of a robust Data Fabric in place, or you might be missing critical components.
- Look at what you need: it might be clear what gaps you need to fill and what integrations need to be implemented for your Fabric to be complete. Are these gaps due to people, process, data or technology? This is what will make your Data Fabric complete.
- Look at what you want: you might have the elements of Data Fabric already, but decide you want to switch to one vendor, such as Microsoft Data Fabric. Or, you might want to introduce more ‘best of breed’ software into the weave of your Fabric. Just because a solution ticks a box, doesn’t mean it’s right for your long-term goal.
What to consider during implementation?
If you are considering implementing a Data Fabric, there are a few things you need to keep in mind. First, you need to understand your business needs and objectives. What are you trying to achieve by implementing a Data Fabric? Second, you need to assess your current data landscape. What data do you have? Where is it located? What is the quality of the data? Third, you need to select a Data Fabric that is right for your needs. There are a variety of Data Fabrics available, so it is important to choose one that meets your specific requirements. Fourth, you need to implement the Data Fabric. This can be a complex process, so it is important to have a plan in place. Fifth, you need to monitor and evaluate the Data Fabric. This will help you make sure that it meets your needs and objectives.
