| 2-6. Data Fabrics in Action: Industry Focus
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Five potential industries that Data Fabric technology affects.
Almost every industry can benefit from data fabrics, allowing them to focus on and improve their own organization’s business rather than worrying about the day-to-day management of their data. |
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| - Banking Industry - Data fabrics enable seamless integration of banking data, providing banks with a comprehensive view of customer transactions and banking operations. This allows for personalized banking experiences, enhanced customer satisfaction and loyalty. Real-time processing and analytics facilitated by data fabrics enable transaction monitoring, fraud detection, compliance streamlining, and risk mitigation. Additionally, customers gain real-time access to view credit card transactions and pay bills online, enhancing satisfaction and reducing labor costs associated with manual customer assistance.
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| - Healthcare Industry - Implementing a data fabric in healthcare organizations enhances patient care by providing comprehensive views of patient data from various sources. This enables timely diagnosis and personalized care by doctors. Data fabrics improve the Revenue Cycle Mgmt. process by facilitating online patient activities such as appt. booking, pre-authorizations, online paperwork, test result access, & bill payment. As healthcare providers can focus more on patient care, the administrative burden is reduced, leading to increased efficiency and customer satisfaction.
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| - Energy / Utilities Industries - Companies in the energy and utilities industry deal with extensive data from smart meters, power grids, sensors, and environmental monitoring. Therefore, data fabrics are essential at integrating the data and facilitating real-time monitoring of energy generation, distribution, and consumption, allowing operators to optimize performance and respond promptly to any issues or disruptions. Furthermore, data fabrics can integrate renewable energy sources by aggregating data from various renewable generation systems, weather conditions, and grid capacity, which can help to optimize energy production and reduce waste.
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| - Logistics Industry – Data fabric technology plays a crucial role in the logistics industry by integrating data from various sources involved in transportation, storage, and distribution processes. It provides a unified view of data from suppliers, carriers, customers, and different systems like TMS, WMS, and IoT sensors. With data fabric, logistics businesses can analyze inventory levels, optimize the balance between customer demand and supplier performance, and reduce excessive inventory costs. It also helps identify efficient transportation routes, improve delivery timelines, and lower expenses.
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| - Retail & E-commerce – By leveraging the capabilities of a data fabric, retailers and e-commerce businesses can improve customer engagement, optimize operations, enhance supply chain efficiency, and drive revenue growth. A data fabric also helps retailers optimize inventory management by integrating data from multiple sources, such as sales data, supply chain information, and demand forecasts. Retailers can analyze this data to improve demand forecasting accuracy, ensure optimal stock levels, reduce stock outages, and minimize overstock situations. This leads to improved inventory turnover, increased sales, and reduced carrying costs, saving businesses money.
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Data fabrics leverage AI and machine learning to reduce the data management workload by automating tasks such as data integration, data preparation, data cleaning, and cataloging of new data sources.
Statistical data from McKinsey & Company on Data Accessibility and its impact on Revenue Growth [2]
Data fabrics utilize metadata, machine learning, and automation to seamlessly connect and enable discovery and utilization of the data for the entire workforce irrespective of the employee’s technical know-how.
Known as data democratization, all employees are empowered to work closely with critical data necessary for them to complete their jobs more effectively and efficiently.
Data fabrics support advanced analytical techniques, including statistical analysis, machine learning, and predictive modeling, which enables organizations to gain data-driven insights.
With data fabric’s predictive abilities, businesses can better understand upcoming market trends or forecast demand and supply trends in their industry.
According to Statista, the market for DaaS is projected to reach $10.7B in 2023, highlighting its growing importance in the industry. [5]
Five potential industries that Data Fabric technology affects.
Almost every industry can benefit from data fabrics, allowing them to focus on and improve their own organization’s business rather than worrying about the day-to-day management of their data.
3-1. Data Fabrics Support Governance and Regulation
It involves defining a strategy, setting data management policies aligned with business objectives, and overseeing the process through data governance teams and data stewards.
As businesses face new data privacy regulations, implementing measures to protect data and ensure compliance with relevant data protection regulations, such as GDPR, PIPEDA, and PIPL, becomes vital for companies.
Analysts predict that by the end of 2023, approximately 65% of the world's population will be covered by such regulations, emphasizing the importance of governance globally.
Data governance ensures regulatory compliance, improves accessibility to essential data, reduces management costs, and enhances data quality.
By leveraging data fabrics, organizations enhance the decision-making process, leading to increased revenue and business success.
This establishes transparency, accountability, and supports data governance.
Data lineage helps identify data sources, detect errors, and navigate complex scenarios such as mergers or acquisitions with different data structures.
Data virtualization solutions improve a businesses’ data governance and security as it integrates data access through a virtual data layer that provides a unified and consistent view of the data ensuring data accuracy, enforcing security, and facilitating data provisioning.
This process eliminates the need for physical data replication or ETL (Extract, Transform, Load), which can introduce data quality issues and make data governance challenging.
As data virtualization acts as a single-entry point layer between the data sources and the end consumers, this provides a point of control for monitoring and enforcing who, how, and when users can access the data.
As governmental regulations require businesses to follow certain privacy and confidentiality rules, data virtualization’s unified access layer becomes an important tool for data governance programs that need to comply with both government and industry regulations.
Businesses can establish data access controls, mask sensitive information, and complete auditing and tracking of the data’s movement within the data fabric.
With the ability to process and analyze real-time information, it would be prudent for all organizations to consider implementing data fabrics to leverage their enterprise’s data effectively and gain a competitive edge.
https://www.forbes.com/sites/ bernardmarr/2022/10/31/the-top-5-data-science-and-analytics-trends-in-2023/?sh=3a194c6c5c41
https://visme.co/blog/data-visualization-statistics/