As per Gartner analysts, over 85% of companies will adopt a cloud-first strategy by 2025 and they won’t implement digital strategies without using cloud-native architectures and technologies. Thus, it will continue to gain rapid momentum in 2024 and beyond. Organizations can leverage the capabilities of data storage and processing in real-time via on cloud. Keeping up with the latest trends in master data management is paramount to handling today’s ever-changing dynamics of the data landscape.
Before delving into cloud master data management trends in 2024, let’s have a glimpse at the significant advantages organizations can get from cloud-based MDM.
We have already discussed what is master data management and explored PiLog’s cloud MDM tool in the previous article. Let’s have a glance at its benefits.
The following 6 trends show a transformative shift towards smarter, scalable, adaptable, flexible, and user-friendly cloud-based MDM solutions. They match with what today’s organizations require and fit with the ever-changing digital arena.
1.AI & ML Integration
The success of a cloud MDM solution relies on high-quality and consistent data. Artificial Intelligence (AI) automates mundane tasks that require human intervention. It can identify patterns and spot potential security risks and unusual activities within large amounts of data. Thus, it alerts businesses about an issue before it becomes a major problem, making master data management accurate and swift.
On the other hand, Machine Learning (ML), being a part of AI, learns from data and improves itself over time. ML algorithms can examine how data is used and tweak their methods to handle data better and make better decisions. If they notice a certain type of data mistake happens often, they can learn from that and act on it to avoid similar problems in the future.
In a nutshell, AI technology is used for the identification of anomalies, automating responses to potential threats, optimizing device management processes, identifying duplicate records, and ensuring data integrity and consistency while ML can adapt to new patterns and improve decision-making.
Together, AI and ML make cloud MDM tools more proactive and intelligent. They eliminate the need for manual oversight, minimize human error, and manage master data efficiently and securely.
2.Hybrid-Cloud MDM
Combining on-premise infrastructure with cloud services is called hybrid-cloud master data management. Organizations can get the best of both worlds- control and security from on-premise, accessibility and scalability from the cloud. They can store their critical data in their on-premise servers and the rest of the data on the cloud. Then, the hybrid-cloud approach allows them to integrate and manage both data seamlessly via a centralized platform. Thus, they can safeguard sensitive data while using cloud servers for scalability and flexibility.
Businesses don’t need to worry about managing IT infrastructure as hybrid-cloud MDM offers flexibility to manage devices across both environments, facilitating integration with existing infrastructure, scalability, and better control. The integration ensures all data stored locally and cloud is synchronized and updated. Thus, it reduces complexity and simplifies data management. This approach is ideal for sensitive data that needs strict security and it helps in addressing compliance and data residency concerns.
3.Blockchain for Data Integrity
Blockchain is making a significant difference in cloud master data management by improving data integrity. Once data is added to the blockchain, it’s permanent—no one can change or delete it without the whole network's approval. This technology is transforming how we maintain data quality and accuracy. With blockchain, our essential data remains secure and nearly impossible to alter without everyone’s consent.
Smart contracts make managing data easier by automatically applying rules, which helps reduce mistakes and keeps things consistent. With blockchain, organizations can easily track changes and check their data’s accuracy, thanks to its clear ledger. This transparency is really helpful for staying on top of regulatory requirements. As more businesses adopt cloud-based MDM systems, adding blockchain is becoming crucial for keeping data secure, transparent, and compliant.
Blockchain also changes how we handle lean data governance. Instead of having a single central authority, blockchain spreads data across many nodes. This setup makes it much harder for anyone to tamper with the data and makes the system more robust. The clear ledger makes it simpler to track and verify data, which helps companies ensure their information stays accurate and reliable.
In blockchain, each record of data changes is stored in a “block” and linked to the previous block, forming a chain. This chain is distributed across many computers, making it incredibly hard to tamper with any record without everyone noticing. So, if someone tries to alter the data, it’s immediately visible to everyone, and the change gets rejected. This transparency and immutability ensure that the data remains accurate and trustworthy.
4.Data Democratization & Self-Service
Data democratization and self-service are shaking up cloud master data management. With data democratization, everyone in a company gets straightforward access to the information they need. Storing data in the cloud and using intuitive tools means employees can quickly find what they're looking for without waiting for approvals. This boosts the speed of decision-making and cultivates a culture of openness and teamwork.
Self-service data analytics takes this a step further by allowing employees to handle their own data analysis. They can build their own reports and dashboards, which helps them get insights faster. This change not only makes the process smoother but also eases the load on IT teams, letting them tackle more strategic tasks.
These developments are fundamentally changing data quality management. By making data more accessible and giving people the tools to analyze it themselves, organizations can make quicker and smarter decisions. As cloud-based MDM systems become more popular, these trends will be vital for effective data governance and management.
5.IoT Integration
Integrating IoT with Cloud Master Data Management (MDM) is growing in importance as businesses aim to handle the large volumes of data produced by smart devices. These devices, such as sensors and machinery, constantly gather and send data. Bringing this data into a Cloud MDM tool allows companies to consolidate it in one location, making it easier to handle and understand, which improves control and consistency across different sources.
Bringing IoT data into the MDM cloud has clear benefits. Collecting data from different IoT devices in one system allows organizations to track it as it comes in, which improves accuracy and simplifies management. This approach keeps data organized and aligned with business objectives, preventing it from being scattered across multiple systems. Having reliable data is essential for making prompt and informed choices.
In addition, combining IoT data with lean data management in the cloud improves how businesses analyze and use their data. Centralizing the data allows companies to use various tools to examine it, recognize patterns, and make more informed decisions. This approach helps organizations react quickly to changes, increase efficiency, and support innovation. As IoT devices become more widespread, integrating their data into Cloud MDM systems is essential for making the most of the information and reaching business goals.
6.Personalization & Customer 360 Views
Last but not least, these trends redefine the way businesses interact with their customers. Personalization tailors interaction based on customers’ data, interactions, and preferences. It also tailors device management policies to align with the unique requirements of different users within an organization. Cloud-based Master Data Management (MDM) systems pull together data from various sources into one place. This makes it easy for businesses to see and use customer information right away. With this approach, companies can create more personalized marketing, suggest products that fit individual needs, and improve customer service based on current information.
On the other hand, the Customer 360 View means putting together all the information a company has about a customer from different interactions. Cloud MDM tools are good at bringing this information together, which helps clear up any mistakes and provides a clear picture of the customer. This complete view helps businesses make better choices and tailor their services to each customer, leading to a better experience and stronger loyalty.
Implementing Cloud master data management trends requires a strategic approach, taking into account the organization's specific objectives and goals. It frequently begins with a thorough assessment, followed by the implementation of applicable technology and the creation of a solid Master Data Management strategy that is linked with company objectives. So, reach a reliable and experienced master data management solution provider rather than regretting it later.
Along with Master Data Management, if you want to know more information about Lean Data Governance, Data Analytics, Data Harmonization, Data Quality Management, and how our various Master Data Record Management (MDRM) solutions can help your organization tackle its own data challenges, please check out our website.
