Figure 1: Data fabric is less searched in terms of data integration.1
22% of data analysts’ time is spent on data preparation.2 The main reason is that data from various sources needs to be integrated. The solution could be a data fabric, which is an interconnected architecture integrating data from various sources. It provides organizations with a centralized and easily accessible data repository. Other benefits of data fabric architecture include:
Despite the benefits, data fabric is not widely known. Only half of the people who look for data integration solutions consider data fabric (Figure 1). In this article, we discuss the 8 benefits of implementing a data fabric solution in 13 industries in detail to help business leaders better understand the technology.
Data Fabric Benefits
1. Improved data quality
A data fabric architecture can greatly enhance data consumption and the quality of enterprise data. By breaking down data silos and creating a centralized repository for data storage, business intelligence can avoid the pitfalls of outdated or inconsistent data. This can positively improve the data:
2. Increased operational efficiency
Figure 2. Interest in operational efficiency is increasing.
A data fabric enables organizations to run much more efficiently. With data integration, data from different sources can be stored in one place. This can assist data engineers in automating manual tasks and streamlining business operations.
3. Better data management & increased data agility
Figure 3. Data management components.3
When a company implements a data fabric solution, it not only improves operational efficiency but also helps them set up better data management practices. By integrating and enriching data from different sources in a central data repository, businesses can ensure the data is prepared and managed following industry standards.
Using data virtualization and federations are some exemplary methods of data integration that are provided by data fabric. With such methods, real-time data analysis can become more streamlined, and roles and responsibilities for managing and maintaining data can be set up clearly.
Finally, a centralized data repository provided by a data fabric solution can enable enterprises to react to changing business requirements easily. A data fabric architecture can provide this centralized repository. This increased agility can enable firms to stay ahead of the competition in dynamically changing business environments.
4. Easier switch from data warehousing to a data lake
You can save time when you use data fabric architecture to switch to data lakes. Data fabric can store and analyze a vast amount of structured and unstructured data from different sources, allowing them to gain previously unavailable insights.
Organizations, such as those in the finance industry, can switch from traditional data warehousing to data lakes. Data lakes can be more flexible than data warehouses and can handle a lot of unstructured data, such as:
Data warehouses can be structured and can rely on a single source of truth. This can result in data integration issues with new data sources. Data lakes can store data in its native format, making it easier to add new data sources and analyze the data differently.
5. Improved data integration and accessibility
A data fabric solution can improve data delivery because firms can access their company data from a centralized source. Integrating data can eliminate the need to unnecessarily switch between several systems and streamline the data access procedure. Furthermore, a data fabric solution can make it simple for data scientists to build data pipelines for data preparation and machine learning.
6. Enhanced data analytics
Figure 4. Interest in data analytics has grown significantly.4
A data fabric solution can increase an organization’s analytics capabilities by offering a centralized data repository. This enables quick access to the relevant data for in-depth research and the creation of useful insights. This can lead to better decision-making, stimulate innovation, and create a competitive advantage.
7. Enhanced data security
Implementing a data fabric solution can improve an organization’s data security by offering a consolidated data repository, allowing for improved access control and sensitive information protection. This can assist business users in adhering to industry rules and avoiding costly data breaches, resulting in increased data security.
The following sectors / industries can especially benefit from data fabric:
Benefits of data fabric for specific industries
1. Agriculture and farming
Agriculture and farming enterprises can use data fabric to collect and integrate data from many sources into a single repository. These data sources can include:
- Weather forecasts
- Soil samples
- Plant growth patterns
This can help farmers make data-driven decisions about crop selection, planting times, and fertilizer use, resulting in increased yields and improved efficiency.
Banks can analyze client data to discover their financial requirements and preferences and offer tailored financial goods and services. To achieve this aim, banks can employ data fabric analytical skills to integrate data from diverse sources to improve risk management and customer services, such as:
Improved data security in banking
Banks can monitor data access and detect unwanted data access attempts using data fabric security features. This is because banks must safeguard sensitive consumer information such as:
- Bank records
- Credit card information
- Personally identifiable information (PII)
In this regard, data fabric security capabilities can assist banks in meeting industry rules such as the Payment Card Industry Data Security Standard (PCI DSS) and protecting sensitive data from assaults.
A data fabric solution can be used by an educational institution to combine and analyze data from many sources, such as:
- Student data
- Curriculum data
- Learning data
With the use of data fabric:
- Schools can easily track and analyze the performance of their students and teachers using a single data repository and make data-driven decisions to improve teaching and learning results.
- Universities can access and analyze data from their partners and stakeholders and leverage data virtualization and federations to boost collaboration and optimize the curriculum.
- Both schools and universities can define roles and duties for data management and maintenance. This can be beneficial in ensuring data quality and consistency while complying with industry standards and regulations.
An energy company can use data fabric technology to integrate data from sensors in its renewable energy systems to optimize power generation based on weather forecasts, energy demand, and other factors. This can help the company reduce energy waste and improve efficiency.
Managing data in the energy industry can be difficult, and this is where data fabric comes in. Energy companies have vast amounts of data generated from:
- Sensors in oil and gas fields
- Power grids
- Renewable energy systems
Data fabric technology can help these companies integrate this data to optimize energy production and improve safety.
Enhanced data agility in energy
Banks and other financial institutions can improve data consumption and quality using a data fabric. This means that their data will be more accurate and reliable.
A data management platform can help the finance industry ensure that all customer data is up-to-date and consistent across all departments. This can make things better for the customer and help avoid legal and compliance problems.
In finance, data fabric solutions can combine financial data from sources like trading platforms and CRM systems to provide a complete picture of how finances work. This can help with risk management, compliance, and making decisions based on more information.
To improve their services and public safety, governments can leverage data fabric analytics skills to integrate data from diverse sources, such as:
- Citizen comments
- Public safety records
- Meteorological data
With integrated data, governments may more quickly spot trends and correlations. This can lead to stronger public safety regulations, more efficient public services, and higher citizen happiness.
Improved sensitive data management in the government
Governments can use data fabric security capabilities to encrypt sensitive data and monitor data access. Government agencies are required to safeguard a huge amount of sensitive data, including:
Implementing a data fabric solution can improve the security of this data by providing a centralized data repository. A central data repository can enable better access control and protection of sensitive information.
Also, with integrated data, governments can monitor data access and detect suspicious activities, such as attempted cyberattacks. As a result, data fabric security capabilities can help governments comply with industry regulations, such as the General Data Protection Regulation (GDPR).
Defense is one of the primary functions of most governments. Defense and military institutions must manage sensitive data, such as confidential mission details, intelligence, and classified papers. So military organizations can leverage data fabric security features to ensure that only authorized personnel have access to classified data. Data fabric security capabilities can assist these firms in improving access control and protecting critical information to lower the risk of data breaches.
A data fabric can improve the quality of healthcare by giving healthcare providers a more complete and accurate view of patient data. With a data fabric, doctors and nurses can look at a patient’s records in one place. This reduces the chance of mistakes and improves patient care. This can lead to a better quality of data and a more efficient and effective healthcare system.
Improved data access, quality, and integration in healthcare
A healthcare provider, for example, can use data fabric technology to combine patient health data from different sources, like:
- Wearable devices
- Electronic medical records
This can enable them to provide personalized treatment plans considering the patient’s unique medical history and current health status. Managing healthcare data can be complex because healthcare providers deal with massive amounts of data created by:
- Electronic medical records
- Medical imaging
- Patient-provided health data
Data fabric technology can aid in the seamless and effective integration of multiple data sources, giving healthcare providers a comprehensive view of:
- Patient health
- Treatment history and outcomes
This can lead to better patient care, better outcomes, and lower costs.
The insurance industry can be highly data-driven. Insurers can need access to vast amounts of data about their policyholders, including personal information, risk profiles, and claims histories. For example, Central Nacional Unimed (CNU), an insurance company, processes ~1.3 billion insurance bills monthly.
A data fabric architecture can provide a centralized data repository for better data management and to protect sensitive information. In particular, insurance firms can use a data fabric solution to:
- Combine and analyze all of this data, allowing them to make better risk and pricing decisions
- To identify fraudulent claims and improve their claims management processes
- To provide better compliance with complex regulations, such as HIPAA
Improved data agility
One of these benefits is better data agility, which lets businesses change their data architecture quickly to meet changing business needs without stopping their operations. A software development company, for example, could utilize data fabric to integrate data from numerous sources and acquire real-time insights into user behavior. They can then tweak their software quickly to improve the user experience and remain ahead of competitors.
Moreover, a data fabric solution can enable self-service data with APIs, which can streamline data access and share across different teams, leading to improved collaboration and productivity.
Enhanced data quality
Another advantage is increased data quality, which allows firms to better control and manage their data in accordance with industry standards. An IT services organization can use data fabric
to ensure that their data is appropriately prepared and maintained for their clients, resulting in enhanced customer satisfaction and trust.
Better data access
Furthermore, data fabric improves data access, allowing businesses to access relevant data for in-depth research and helpful insights rapidly. A cloud computing corporation, for example, can utilize data fabric to construct a central repository of consumer usage data, allowing them to discover trends and provide customized services to customers quickly.
Improved data integration
Data fabric can facilitate data integration by providing multiple approaches, such as data virtualization and federations. This can help an IT consulting company streamline its data analysis and keep track of who is responsible for what in terms of data maintenance.
Data fabric solutions can integrate supply chain data for logistics. Logistics firms can access and handle data from multiple sources, such as:
To give a single view of all operations, a data fabric solution can combine data from different sources, such as:
- Transportation management systems (TMS)
- Warehouse management systems (WMS)
- Customer relationship management (CRM) systems
This can help businesses make decisions in real-time:
- Leading to faster delivery
- Lower costs
- Reduce logistics emissions
- Streamline supply chain operations
A manufacturing company can utilize data fabric technology to combine data from sensors in its production line to monitor machine performance and discover possible issues before they create downtime or faults.
Data fabric technology can provide a centralized view of the manufacturing process, enabling companies to identify bottlenecks, predict equipment failure, and improve quality control.
To do this, manufacturing companies can need to integrate data from various sources to optimize their operations, such as:
- Supply chains
- Quality control systems
Improved data quality in manufacturing
Data fabrics can combine production data from different systems into a single repository for the manufacturing industry. This can automate tasks that used to be done by hand, like entering data and making sure it all matches up. This can make the data more accurate and reliable. It can also make the company’s operations run more smoothly, saving time and money in the production process.
Improved data agility in manufacturing
A manufacturer can improve its agility by using data fabric solutions to adapt swiftly to changes in production requirements, such as:
In the retail industry, a data fabric can be used to track better:
With more accurate and timely data, retailers can improve their data management. This can result in better product development, marketing, and inventory management decisions.
Improved data governance in retail
Also, a data fabric can help improve data governance in the retail industry by giving different data sources a central place to store their data. Retailers can make sure that their data is accurate and up-to-date by combining data from sources, like:
This can help retailers make better decisions about managing their stock, making new products, and their marketing strategies, which can lead to better business results in the long run.
If you have further questions on data fabric benefits, please contact us at:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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