What is Data Management and why is it important?
Data has become one of the fundamental elements for organizations, as the ability to efficiently and securely manage massive data flows is key to lead to the correct valorization of information assets. Here it comes the need for a strategic corporate data management approach, considered as the collection, archiving and use of information within the limits of policies and regulations, aiming to guarantee their integrity, reliability and accessibility. To adopt effective data management strategies is crucial for the implementation of IT systems that run business applications and provide valuable information to support business decision-making processes.
Data Management is part of Data Architecture, thus the set of logics, processes and technologies necessary to collect, transform and distribute data at all levels within the organization that contributes to the definition of the Data Strategy, a detailed plan defining company’s priorities and goals regarding business data and information.
The main purposes of Data Management are:
- Business Centrality, allowing organizations to define data governance that supports the strategic unfolding of activities;
- Integrity, ensuring the quality, accuracy and reliability of company data, providing error control and prevention mechanisms;
- Accessibility and Security, guaranteeing access to data and ensuring secure distribution, minimizing the risk of privacy violation, loss or theft through the adoption of suitable security measures;
- Elasticity, ensuring scalability and flexibility capabilities that enable quick response to changing business needs;
- Collaboration, enabling more efficient cooperation between teams and workgroups with different business roles.
Data Management is a sector that’s proving to be increasingly important for companies that want to leverage data to create value, no wonder that new innovative architectures and approaches are being developed, such as the Data Fabric.
What is Data Fabric?
Every data-centric business needs an approach that overcomes the obstacles regarding time, space, different types of software and data locations. Data must be accessible to the users who need it, without being fragmented into several repositories or managed by different teams. The solution is called Data Fabric, a method to manage data specifically designed to address these challenges and help businesses thrive.
Data Fabric allows users to connect and manage all company data in real time and across different applications and systems. This factor is important, as it means having a single source of reliable information available to safely consult when needed, thus automating data management processes.
The American company Techtarget provides a definition of Data Fabric which refers to “an architecture and software offering a unified collection of data assets, databases and database architectures within an enterprise, that can be confined to an application, used to collect distributed data and extend to all enterprise data, serving as the implementation of general data virtualization principles”.
Data Fabric is therefore a solution that facilitates end-to-end data integration, several data pipelines and cloud-based data management environments through the use of intelligent and automated systems to ensure a unified and consistent user experience that supports collaboration between teams and helps companies in the strategic unfolding of any activity. Over the last few years, the development of Artificial Intelligence (AI), Internet of Things (IoT), Hybrid Cloud and Supercomputing caused a large growth of big data and generated an ever-increasing demand for data-based technologies. This made urgent for businesses of all sizes to unify data environments and foster Data Fabric as an essential and powerful data management solution.
Data Fabric vs. Data Mesh: what’s the difference?
Data Fabric and Data Mesh are two different architectural approaches for the management of data, even if both aim to improve their integration in environments in which multiple systems and applications coexist.
Data Mesh is a centralized data architecture that organizes data according to specific business functions – such as marketing, customer service, etc. – and conceives them as a product (Data as a Product, DaaP) with certain features, like availability, accessibility, reliability, interoperability and security. Instead, Data Fabric is a combination of software solutions that aim to create a centralized source of reliable data available to users in need of it.
Data Fabric is based on three key elements:
- Data Virtualization, that allows company to access data with considerable savings in time and costs;
- Distributed Data Architecture, that is adaptive, flexible and secure and unifies the different data sources dynamically accordingly with changing business needs;
- Automation, that allows companies to minimize costs and improve the quality of the management of available data with Artificial Intelligence and Machine Learning.
What are the advantages of Data Fabric?
As we have seen, Data Fabric architecture overcomes the limits of traditional enterprise data management offering many advantages to companies looking for better performances when it comes to effectively handle data for strategic purposes.
Here are the most important advantages of Data Fabric:
- It is based on centralized, automated and simplified data management process;
- It possesses a single, secure and efficient source of reliable information;
- It provides fast insights, real-time information and quick access to data;
- It is based on high scalability to better adapt resources to changing needs;
- It makes easy to access data providing security and mobile operability;
- It improves team collaboration by unifying all company data in one single place;
- It guides decision-making efficiency and accelerates digital transformation.
