5 questions public sector CIOs
should be asking about Data Fabric

It’s often said that ‘data is the new oil’, and that we live in a ‘data economy’, and though those phrases might seem a little overused, they’re true. There is data on just about everything we do, and information is the resource that modern organizations run on.

In the public sector, there are extra dimensions to your relationship with data. On one hand, it’s a valuable resource: one that gives you the information you need to improve your citizens’ experience, allocate budgets more effectively and empower your colleagues to make informed decisions. On the other, citizens are wary of how their data is used: issues with data quality and security can make utilizing data in the public sector complex. Then, there’s the issues of legacy technology, multiple data sources and the growing volumes of data that need to be handled every day.

Centralising, integrating, and governing data is essential to making sure you can a) take those beneficial data opportunities and b) avoid data errors – which is why Data Fabric has become such a point of interest for public sector CIOs in the last year. 

Before you take the leap into Data Fabric, here are the five biggest questions that public sector CIOs should be asking about Data Fabric.

  1. What is Data Fabric?
  2. Why do we need Data Fabric in our public sector organization?
  3. What would the benefits of Data Fabric be for my public sector organization?
  4. Would we need to rebuild our data ecosystem from scratch?
  5. Are there any barriers to Data Fabric implementation for public sector organisations like ours?

1. What is Data Fabric?

Think of Data Fabric as an ecosystem that integrates your data applications and standardizes your practices around data.

Data Fabric is an architecture for data management. It aims to unify behaviour and processes around data, and it uses layers of data tools that help an organization govern their management of metadata, master data, data integration, and data delivery.

Data Fabric is an approach, not a solution. It’s something that you create, not something you buy, but its typical components are:

  • Data Governance
  • Security + Access
  • Integration
  • Data Engineering
  • Data Lake + Data Warehouse
  • AI, including machine learning and large language models
  • Analytics + Visualisations

2. Why do we need Data Fabric in the public sector?

While any organization can benefit enormously from having a Data Fabric, the public sector has unique challenges that the approach can solve.

  • You’re accountable to more people and more organizations

In the private sector, the relationship is mainly between business and customer. Public sector organizations often have a complex web of responsibilities and relationships. You may be working with one or more government departments, with numerous other organizations (public and private), and of course there is your relationship with the citizen.

Your data flows in more directions, more people and bodies have a right to it, and it has a broad impact if it’s inaccurate.

  • Budgets are always tight

Every public sector organization operates with limited and in-demand resources. Data Fabric can ‘monetize’ data — that’s to say, it can help you use data to make better decisions that save money and increase revenue.

  • Data is often sensitive

Any organization should have as much control as possible over their data, and they want it to be as secure as possible. The public sector is often held to a higher standard on security, and the data you handle is very often very sensitive and/or personal.

3. What would the benefits of Data Fabric be for my public sector organization?

Unified behaviour and approaches to data mean that information is democratized. Data Fabric eliminates silos, so:

  • everyone can access the data they need
  • there are unified, consistently presented, accurate, and timely pools of data
  • the whole organization can make better decisions, faster, and backed by data

Data Fabric is also a strong preventative measure that protects you from human error or misguided decisions. Actions that stem from incomplete or inaccurate data could waste a great deal of your own budget, or other public money, or even compromise people’s safety.

4. Do we need to rebuild our data ecosystem from scratch?

It completely depends on the state of your data fabric now. Many organizations have a data fabric already, even if it’s a little patchy or there are holes in it. You may only need to make some ‘repairs’.

Many organizations can’t realistically replace their data fabrics, but that’s not a problem. It may only be a matter of adding some new capabilities and processes. Remember — Data Fabric is an approach, not a solution you can buy. Technology supports it, but the most important thing to the success of the project is that before it begins, you clearly define the desired outcomes.

You can start from first principles if you choose. While there’s no ‘off the shelf’ Data Fabric to buy, there are offerings that package some of the Data Fabric tools you need. These are often best for organizations without a lot of data technology already.

5. Are there any barriers to Data Fabric implementation?

There are some things that could prevent you from creating a strong Data Fabric. If you recognize any of these, you will need to address them before you can start implementing your fabric.

  • Lack of metadata

In a Data Fabric, data passes freely between applications, and it is readily available to all users. However, that data is without value if it lacks context and origin. If you don’t have the metadata to support that, you will not create a Data Fabric.

  • Poor quality data

If the data that you hold is not accurate, complete, and consistent, then you should measure and improve the quality of your data.

  • No Master Data Management (MDM)

If data fabric integrates data into everything you do, MDM ensures that the data you integrate is accurate and consistent. When the same data is used in various parts of the organisation, it’s vital to hold a Single Version of the Truth (SVT). Otherwise, corrupted or inaccurate data can easily spread. Then people will likely base their decisions on false data, which can be disastrous.

  • Lack of buy-in

Because data fabric is a process, it can’t survive without a healthy data culture. It is decentralized, so more power and responsibility sits with more members of staff. If those members of staff haven’t bought in enthusiastically, then the project is highly unlikely to succeed. You should understand your organization’s Data Maturity, and if that needs to improve, you should invest properly in managing that change.

The first step is to assess the alignment between data outcomes you need, and the potential that Data Fabric offers. Our guide can help; Democratize your data to extract its full value, an Agile Solutions guide to introducing this flexible data architecture.

Data Fabric Guide