Data management is a major concern for enterprise organizations, and for good reason. IDC forecasts that by 2025, the global datasphere will grow to 163 zetabytes (ZB). Access to all this data will unlock unique user experiences and a new world of business opportunities for organizations. Data is becoming increasingly diverse, dynamic, and distributed across on-/off-premises, including public cloud. Hybrid cloud environments combine these platforms to increase the benefits of data collection and use, but they come with their own set of challenges. These hurdles prevent organizations from efficiently managing and deriving maximum value from all their data.
When working with Big Data, data quality, integration, security, compliance, protection, and location/resource optimization are top challenges that enterprises struggle with. Today, most organizations purchase and manage overlapping tools and employ manual processes to address these unique challenges. However, IDC has identified three service differentiators that seek to solve these challenges and directly impact productivity, risks, and costs. What innovative data services for hybrid cloud should organizations invest in? We explore three standout services:
- Data Quality and Validation
Sensitive industries are seeing significant increases in costs to eliminating data risks – or fines from improperly handling them. As a result, data quality is now often part of the hybrid cloud SLA during data handoff or transfer. All Big Data users face suitability and rule configurability challenges in ensuring that data is trustworthy. The old approach of data validation using manual coding and linear processing is not scalable for Big Data. Innovative machine learning algorithms can autonomously create and track data quality fingerprints to trap Big Data quality deviations with minimal intervention. These services complement existing validations and onboards new data sources very easily.These services should work over all major data sources and across locations (on-premises/public cloud). Organizations can use data quality and validation services to identify Big Data errors autonomously from multiple data sets. A truly innovative data quality and validation service can reduce 4-5 months of data validation project efforts to just a few hours’ worth of work. - Cost Optimization
Of the many new challenges created by increased public cloud usage, cost optimization is the number one priority for cloud adopters. Innovative cost optimization is machine learning driven, insightful, controlled, automated, and supports dynamic optimization of public cloud resources.The right services can provide full automation or semi-automation of cost optimization actions through machine learning or user policies using patented and patent pending technologies. Innovative providers will also support flexible deployment options — SaaS and enterprise. However, keep in mind that to avoid any regulatory or compliance concerns about sharing server credentials, the enterprise model should run all software directly in the organization’s environment as opposed to the service provider’s. - Application-Centric Data Management
The IT stack has evolved. Monolithic software architectures are transitioning to microservices, on-premises deployments are transitioning to hybrid/multicloud, and scale-up infrastructure is moving to elastic compute and storage. The modern IT stack needs a modern approach to data management. Innovative service providers are answering the need with application-centric cloud data management. Differentiators in data management will offer new or improved backup components, such as semantic deduplication, parallel data streaming for versioning and recovery. It will also be data aware, and support distributed metadata catalog. These data management services will need enterprise level security, including TLSISSL encryption (transfer protocol) between the provider and data sources, and should integrate with enterprise identity management tools (LDAP authorization).
Leading digital organizations are discovering that the cloud — with its power to deliver agility and flexibility — is indispensable for achieving their DX business objectives. For most organizations, this leads to hybrid IT in which data is generated and stored across a combination of on-premises, private cloud, and public cloud resources. This hybrid infrastructure causes a new set of Big Data management challenges for IT staff.
To address these Big Data management challenges, gain a competitive edge, and thrive in the DX era, organizations need to make investments in cloud while also adopting data services for hybrid cloud.
IDC’s cloud research provides customers with a complete understanding of their buyers and consumers of cloud products and services across the entire cloud ecosystem, not just hybrid cloud. Learn more about IDC’s industry-leading cloud expertise here.
