Cloud computing and big data: Three compelling market trends making a case for cloud data

Cloud enables organisations to store, consume and process data with both speed and scale in order to derive value for business actions.


Data and cloud are two critical elements of any digital transformation that no organisation aspiring to succeed can afford to ignore.

The benefits of cloud are no longer debated – it brings speed, agility and lowers total cost of operations for enterprises, without worrying about managing or maintaining IT infrastructure. But for organisations to innovate, we need another key ingredient – data.

Cloud enables organisations to store, consume and process data with both speed and scale in order to derive value for business actions. It allows the focus to shift to innovation with new business models and value-creation opportunities.

Let’s look at three of the compelling market trends that form the case for cloud and big data.

  • High generation and consumption of data: As per a study by Associated Chambers of Commerce and Industry of India-PwC, the compound annual growth rate (CAGR) of data consumption in India is 72.6 percent and will be a whopping 10,96,58,793 million MB in 2022. With 500 million internet users in the country, we are big on data consumption.
  • Increasing focus on edge computing and data centre deployments: IDC reports that more than 30 percent of organisations’ cloud deployments in India alone will include edge computing in the next four years so that data can be processed closer to the source for real-time decision making.
  • Adoption of new and emerging technologies like AI, ML, IoT is creating further demand for computational power as well as storage on the cloud.
 Cloud computing and big data: Three compelling market trends making a case for cloud data

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Cloud-native architecture when applied to data, breaks through the siloes of data extraction and modelling created by teams from different business units and makes it global and fluid, removing not just redundancy of data assets that is often customised to suit the needs of individual teams, but creating a data platform that threads across every architecture layer in the enterprise.

Based on a framework of microservices and DevOps, data platforms connect the infrastructure, data and applications in an organisation and facilitate the provision of ‘data as a service’, wherein, not only do internal stakeholders gain access to the data stored in various repositories via APIs but it opens the door for all the partners including external agencies that form part of the business ecosystem to participate and contribute to this data, thus encouraging innovative collaboration and monetisation of data.

As organisations grow in their business, it also addresses the need to scale up. Taking this a step further is the opportunity to generate meaningful insights using AI and data analytics. Data, therefore, becomes boundary-less and consumption becomes purpose-driven encouraging enterprises to bring self-service capabilities in addition to creating the pressure to maintaining high-levels of accuracy and security.

An enterprise must be conscious of its responsibilities when creating this cloud-enabled data platform:

Data security: Most cloud vendors offer services that are in compliance with federal data governance standards. However, while implementing data security on the cloud, it is essential for enterprises to take responsibility and ensure that it aligns with the enterprise-level security strategy and complies with the relevant international laws on data privacy and usage. With data becoming boundary-less, it is important for enterprises to take the responsibility of defining and identifying sensitive information, creating policies for their migration to the cloud, managing data integrity in a multi-cloud scenario, training and building a ‘security-aware’ cloud staff.

Data management: Shifting to the cloud often means an enterprise has to manage both data on the cloud and on-premise. In addition, it is often challenging to balance security needs with easy access to data. Besides access management, policies around data in storage, managing unstructured data, data in transit, data backup and recovery need to be addressed. Organisations must consider database management systems (DBMS) cloud services as most innovations are happening in the area. Gartner reports DBMS cloud services are already $10.4 billion of the $46.1 billion DBMS market in 2018.

Data storage: Strategising the storage needs of an enterprise is essential in order to minimise the cost of storage and maximise accessibility and security. Managing your own storage infrastructure can be expensive, cumbersome and time-consuming, while cloud is flexible, agile and can be scaled with ease, however, security on the cloud requires vigilance.

The responsibilities do not stop here. There is data governance and risk management. With data monetisation, there is data management for the marketplace, adding cognitive capabilities to explore potential opportunities in data, leveraging new technologies with a cloud-native data platform. There is a whole gamut of services that need to be managed when on the cloud. Particularly, in a multi-supplier cloud services environment streamlining resources to meet the technical and fiduciary requirements of the enterprise workload require expertise.

Partnering with a managed services provider who can ensure the smooth functioning of IT applications and enterprise operations while optimising cloud can make it easier for enterprises to manage complex data structures in a hybrid cloud ecosystem without compromising on security and compliance and at the same time ensuring maintenance of service level agreements. But most importantly, it leaves enterprises with the bandwidth to focus on innovation and growth instead of managing the nuts and bolts of a cloud platform.

The author is EVP and Head – Infosys Validation Solutions & Cloud, Infrastructure and Security, Infosys

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