“Enterprise data environments are outmatched by the demands on them.” This succinct observation in a recent Forbes article perfectly articulates where organizations are in their quest to better harness data for decision-making. For most organizations, outmatched pretty much sums it up. There are many reasons for this – acquisitions over time, legacy systems, lack of digital skills, underinvestment, increasing amounts of unstructured data – but regardless of the exact circumstances, most companies feel limited in their ability to make use of data.
While data struggles occur across departments, the CFO and the finance team can face additional challenges given the scrutiny they face around management, statutory and regulatory reporting. Additionally, the finance function frequently plays the role of data stewards within an organization – expected to provide seamless data access, views and analytics cross-departmentally. While data fabric offers benefits for organizations as a whole, this article will focus specifically on the value of a data fabric within the finance department.
Defining data fabric
Gartner defines data fabric as an emerging data management design that enables augmented data integration and sharing across heterogeneous data sources. Data fabrics have become more prevalent over the past few years as data formats, sources, and silos have exploded. Gartner identified data fabric as a top strategic technology trend in 2022 and predicts that by 2024, data fabric deployments will quadruple efficiency in data utilization, while cutting human-driven data management tasks in half.
More a method than a tool, data fabrics provide a centralized, single layer of interaction that can bring in data, regardless of location, in a way that doesn’t require that data to be copied or duplicated. Once there, a data fabric can be used to manage the lifecycle of that data, applying active metadata to enforce company governance, data privacy policies and compliance through role-based access controls. Finally, data fabrics can better expose data to users through search catalogs and allow them to leverage data in various business intelligence, machine learning or open-source tools.
Data Fabric and the CFO
For CFOs who look after complex data and finance IT landscapes, utilizing a data fabric provides business users easy access to data and increased performance and business agility while minimizing the total cost of finance – the ability to operate better, faster and at a lower cost. Let’s take a closer look at some of the benefit areas.
An empowered finance (and wider business) team
Data fabrics empower finance – and business users generally – to create data models and consume data without the need for coding experience.
Traditionally, an application has a predefined data model which requires finance and IT teams to bring in data points from other systems and match them to predetermined fields. This can sometimes feel like trying to get a square peg into a round hole and frequently slows progress as teams struggle to fit existing data into rigid data models. Using a data fabric, teams can flexibly create the data model within finance to accommodate the source format. As a user defines new data tables or entities within finance, the interface automatically adjusts and dynamically picks it up. This is called data cataloging and it’s a significant advantage of the data fabric approach, not just within finance, but throughout the technology industry. This allows data models to be created by finance subject matter experts rather than technical users, through the use of metadata. The environment is flexible and dynamic allowing interfaces and integrations to rapidly adapt to the definitions.
This allows data models to be created by finance subject matter experts rather than technical users, through the use of metadata. The environment is flexible and dynamic allowing interfaces and integrations to rapidly adapt to the definitions.
A data fabric approach also allows finance to be much more flexible in the database application that can be used to underpin a dataset. Finance can select the data storage tool that best fits the purpose. For example, the Aptitude Fynapse platform – which leverages a data fabric – uses a relational database tool for configuration data. For actual transactional data, it uses a more traditional column-based database. Using a data fabric approach allows us to make those selections to ensure we can access the best set of capabilities for the business and technical requirements as well as the best performance. In the future, if it becomes more cost effective to swap the database technologies – say due to a vendor cost increase – we can do that without impacting the rest of the application. This agility removes dependencies and broadens your ability to deliver the highest performance at the lowest cost.
A reduced cost of finance
One of the key benefits of data fabric is the ability to reduce the cost of the finance function through the elimination of redundant storage mechanisms. Given the current economic climate and with the rise of cloud computing, this is an important area for both IT and Finance leaders looking to create a lean infrastructure that still meets the needs of the business. The reduction in data ‘lifting and shifting’ also reduces the number of integrations and points of failure, reducing the need to bring in IT to solve issues that arise.
In addition to reducing the cost of storage and IT support, CFOs can reduce the cost of finance by eliminating multiple, siloed finance teams preparing, validating, adjusting and reconciling different datasets for their own purpose. A data fabric allows for this activity to be centralized, leading to a more cost-efficient finance department.
Decreased time to value
Gartner recently estimated that data fabrics have the ability to cut data management efforts by up to 70% and accelerate time to value. This has massive implications for finance departments. From limiting the need to build out point-to-point integrations between systems to the reduction of repetitive tasks like profiling datasets, discovering and aligning new data sources and addressing ongoing integration issues – finance can reduce time to value.
Access to a broader technology ecosystem
In addition to the integration capabilities with typical target and source systems, data fabrics enable extensions to be built on top of core applications, for example, the Aptitude Fynapse platform. As we know the concept of a technology ecosystem – where key providers, all focusing on a specific domain or product, seamlessly integrate to provide greater functionality to their clients – is becoming an important driver of business value. Using a data fabric can make it easier to integrate client or partner-developed IP or applications that utilize the same data set, providing confidence to end users that their data is accurate. At Aptitude, we know that there are sectors of the finance landscape outside of our strategic product focus, but the data fabric approach enables us to create partnerships that allow for additional tooling to sit on top of our application in order to provide a joint solution to clients.
Bringing the data fabric to life
Imagine a finance department as a mini data fabric environment. Fynapse acts as a finance management platform that both maintains its own data fabric and can interact with a larger data fabric ecosystem around it. Within finance, the data fabric architecture can support all modules, those provided by Aptitude as well as those provide by third parties. They are all pulling from the same trusted set of data without the need to move or duplicate data points. It’s a single point of access and a single storage point for all that data.
Data fabric is a strategic technology approach that can mean big benefits to CFOs and their teams as they work to ensure data is trusted, detailed and generating business insights. From increasing flexibility and performance to reducing the cost of finance, this is an important strategic technology that will unlock business value.