Data is what drives business today. The velocity at which it is being generated and the volume of data that is available to – and collected by – businesses are increasing and accelerating by the day. In fact, IDC’s research estimates that 463 exabytes of data will be generated every day by 2025.
Guide to Simplifying Data Management in a Hybrid Cloud
Hybrid cloud systems facilitate seamless collection and application of data in the organization with full transparency across the data lifecycle.
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Market understanding of Big Data and its applications has matured and organizations have come a long way from the days when data was proclaimed as the new oil.
“I wouldn’t say that data is the new oil but it is definitely the fuel that drives innovation within organizations,” claimed Matt Aslett, Research Director, Data Platforms & Analytics at 451 Research, in a talk titled The Future of Data Management in a Cloud-First World at the Cloud Next '18 conference.
Aslett is of the opinion that companies of all sizes from SMBs to enterprises are attempting to undergo a digital transformation in an effort to become more responsive to changing customer behavior; but they need to recognize that that data and analytics enable them to do that.
Which leads us to the question: How can companies efficiently collect data and harness its potential to streamline operations, serve customers better, and generate revenue?
The answer is efficient data management. Data management is the process of collecting, validating, storing, and accessing data and putting it to effective use across business functions.
What, Then, is Cloud Data Management?
A cloud data management system enables handling of traditional data management functions from the cloud. It is a viable alternative to data management using on-premise hardware and software.
In order to do this more efficiently and reliably across various platforms, data can be stored and accessed from private, public, or hybrid cloud systems. When data is stored in the cloud, the rules for data integrity and security change. The solution or model shifts from product-based to service-based, as resources are added on demand. The approaches and methods to manage data vary greatly and depend on components unique to the cloud system.
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Security and complexity of management are perceived to be the main challenges in cloud data management, but with an increasing number of companies moving critical data to the cloud, these are being overcome fast with greater benefits in speed of deployment, performance, costs, scalability, and flexibility.
Understand the Purpose of Data Collection
Most organizations simply focus on the volume of data that they collect, and miss out on critical steps in analysis or application of that data. It is important to know the sources that the data is coming from in order to improve accuracy and veracity. Next comes a reliable process to access this data and put it in the hands of decision makers at the right times.
With traditional methods, the question was how to collect data and where to store it. Cloud has removed this limitation. With plummeting prices and on-demand access, the new mantra is: Collect first, analyze later.
The cloud gives organizations the freedom to figure out what to do with the data they’ve collected later – and get real value in the process. “We have customers that have had 100x growth in real-time data that they were collecting in just 18 months, just because they started getting a lot of value out of the data sets,” said Sudhir Hasbe, Director of Product Management for Google Cloud Platform.
Know How Data is Used in the Organization
A hybrid, multicloud environment enables organizations to put in place a scalable platform for data management that helps them get value out of the data they collect. This involves experimenting with the forms and formats in which data is collected, stored, streamed, and accessed.
A study by 451 Research found that nearly 70% of enterprises run their workloads on a multicloud environment. At the outset, most enterprises ended up with multiple clouds purely by accident, as siloed departments with shadow IT infrastructure implemented their own cloud systems and data processes.
“A hybrid cloud is when companies strategically, deliberately use multiple clouds, specifically to support a single application or workload,” as per Aslett. Database and analytics are the most popular workloads that are being run in a hybrid cloud environment, as per the 451 Research.
“In a hybrid cloud scenario, most organizations will be on a multi-cloud or on-premises pattern. The focus will be on an open cloud and the ability to run workloads on in multiple clouds,” added Hasbe.
A cloud data management solution can unify data governance, security, and intelligence in a single control plane in what can be termed Data Management as a Service (DMaaS). This is a holistic approach to moving and accessing data across endpoints, infrastructure, and cloud apps.
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A single data model architecture simplifies the information lifecycle management in the organization without the need for hardware, dramatically lowering costs in the process.
Automate Data Migration, Archiving, and Disaster Recovery
A Forrester report found that people, and not technology, contributed to half of all cloud migration costs. Migrating data from apps, files, and workloads is a labor and resource intensive process, especially when using legacy systems. Further, human intervention makes it error prone. A cloud data management solution can help automate data migration, simplify deployment, synchronize workloads on a schedule, and save time in the process.
Moving of legacy data and applications to the cloud for archiving can also be automated, reducing costs and ensuring appropriate access and discovery on demand.
Finally, a hybrid cloud brings agility and pay-as-you-grow economics to availability and disaster recovery (DR) too. The fast provisioning and fractional IT consumption advantages of the public cloud are mixed with tightly enforced SLAs and security requirements of on-premise datacenters or private clouds. A highly resilient hybrid infrastructure combines compute, storage, and virtualization, with automated cross-hypervisor backup and data protection.
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With automated cloud provisioning, DR scenarios can be tested out at less cost with minimal effort and risk. Hybrid solutions make sure deployments with different configurations across multiple remote sites can use a centralized backup and DR strategy.
Consistency is the Key to Data Management
The hybrid cloud is transforming today’s IT infrastructure just as surely as data is transforming the nature of business. The ability to extract value from data efficiently will prove to be the differentiator between successful and average companies. This translates to the organizational capability to build and deploy a data model that works harmoniously with the cloud infrastructure and enables timely analysis of critical data.
With a comprehensive cloud data management strategy, leaders will have access to a single, centralized dashboard that provides a real-time view of the information being accessed and used across the organization. This will allow them to design and execute customer-focused projects without the risk of over-investing in IT resources.
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