Data decentralization and fragmentation has created a cloud-first hybrid system that calls for strong cross platform data management platforms
For cost-effective flexibility and agility, businesses have been embracing cloud migration. Most businesses aim to drive digital revenue growth with modernized analytics, databases, and data warehouses. However, according to the World Economic Forum, 70 percent of these cloud transformations failed to achieve their targets.
Experts suggest that true digital transformation rather than digital modernization is actually about enhancing customer experiences. With this in mind, businesses need a data-led AI-driven strategy.
A Unisphere Research study reported that 70 percent of database administrators are required to manage more than one data platform and several others work with three or more databases. With the exponential growth of data, data proliferation, decentralization, and fragmentation have become the fundamental elements of a cloud-first, hybrid system.
Businesses that don’t pay heed to the new normal of the hybrid environment will have to face complicated problems associated with fragmented data across several platforms. They might not be able to connect the right data with the intended customers. There are several benefits of cross-platform data management making them an inevitable requirement for organizations worldwide.
Being cloud-native at scale can beneficial. Single cloud-native platforms enable data, application, and API integration along with data management. Experts recommend the use of this strategic platform as it can help organizations be flexible and process data according to business demands. CMOs can also benefit from data ingestion at any latency to democratize data and provide business users with better real-time data insights.
Additionally, a cloud-native platform can derive data from any source and business or technical users. Data in the cloud, cloud-to-on premises environments or on-premises to on-premises environments can easily be accessed and governed despite remote locations. As a result, transforming every data into insights on a massive scale can be beneficial. Some data intelligence and automation processes take months to derive insights from the petabytes of data that organizations procure. Experts recommend having a metadata system driven by AI and ML to help enterprises make smarter business decisions.
Using insights at scale, companies can make them increasingly accessible to users across the business. Executive leaders can maximize their agility with a low-code or no-code data management approach. It allows customers to navigate from idea to implementation without business costs associated with the development and maintenance of code. With timely, trusted, and actionable data, brands can easily transform business initiatives from customer experience to financial transformation and supply chain management.
While data security is still the topmost priority of organizations worldwide, security leaders are scrambling to innovate better solutions. Meanwhile, industry executives continue to seek the best available solutions and enforce governance and existing data laws. With cross-platform data management, CMOs strive to ensure trust with consistent enterprise-wide data quality and limit privacy risks by regulatory compliance.
Experts strongly recommend companies innovate data solutions and build a cloud dedicated to data management for businesses to not only stay ahead of competitors but thrive in the changing new business ecosystem.