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Moving workload to hybrid cloud for better data management

By Nitin Jadhav
|
Jan 28, 2020
|
3 min read

Hybrid Data Warehousing for Scalability

Data, as we know, is the most prized asset for a business. With increased touchpoints for businesses, the data that comes in is often stored in siloes across the organization. Due to this, data science teams are unable to optimally run their analytics tools or deploy algorithms to derive actionable insights from the data sets. Today, most organizations use a combination of cloud services along with on-premise infrastructure to manage critical data. With the data protection norms setting in, organizations will have to implement a cloud strategy that aligns with the governance and storage requirements of India’s Personal Data Protection Bill 2019. A hybrid approach to the cloud will thus help businesses meet both their security and scalability requirements by deploying a blend of private and public cloud services in their IT infrastructure.

With the rise in data, the computing and processing demands of the cloud architecture needs to be elastic for data deployment models. Hybrid cloud will allow organizations to meet the on-demand data requirements and derive insights in real-time to meet the business objectives. It would also allow for seamless data management by ensuring the portability of workloads among the on-premise infrastructure and public cloud.

Securing Data in the Cloud

A lurking challenge for cloud-environments is the security of critical data. In a hybrid cloud, enterprises can disintegrate confidential and less critical information for storage purposes. By doing this, they can effectively put in place a disaster recovery mechanism that can replicate data in real-time and create data copies on multiple sites. The security requirements of a hybrid cloud environment can be addressed by deploying a single unified security environment across the organizational network.

Advantages of Hybrid Cloud

As customer experience takes the center stage in business decisions, a hybrid cloud management solution offers the agility required to mine heaps of unstructured customer data and run business analytics on them. Some retail brands are using hyper scalable cloud solutions to manage information overload during heavy-traffic period and optimise their sites to provide a personalised experience in real-time. A hybrid approach makes it easier for enterprises to integrate multiple tools and reduce latency for seamless customer experience.

Indian companies are stepping up their dependency on hybrid cloud and working towards moving their traditional data into data lakes. Hybrid cloud solutions not only provide flexibility to run applications of various scale but also create self-service data platforms by modernizing the IT infrastructure. With hybrid cloud, enterprises can align their workloads, either on-premise or on cloud, that aligns with data security, governance and business requirements of the organization.

With major players setting up their data centers in India, the hybrid cloud model will provide a balanced IT model to deploy an optimal cloud migration strategy. Organizations will be able to select the best infrastructure for different applications by leveraging the elasticity of a hyper specialised arrangement. The year 2019 saw major global players coming together to harness their cloud capabilities and India’s maturing start-up and SME ecosystem only paves the way for a considerable shift to integrated cloud solutions.

Source: https://www.dqindia.com/moving-workload-hybrid-cloud-better-data-management

Nitin Jadhav
Head - Solution Engineering

Enterprise tech is Nitin's oxygen. Over the past 18 years Nitin has worked extensively on multiple enterprise technologies including Cloud Computing, Data Centers, System Software Development, Network Designing and Application Support. He was earlier associated with organizations like Sify Technologies, Sprint RPG, Reliance Communications etc. and has worn various hats including pre-sales, product management and data center operations.

Future

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Moving workload to hybrid cloud for better data management

Moving workload to hybrid cloud for better data management

By Nitin Jadhav
|
Jan 28, 2020
|
3 min read
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