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Data-as-a-Service: A Winning Approach to Data Management

Data-as-a-Service: A Winning Approach to Data Management

Focusing on the concept of DaaS (Data-as-a-Service) allows you to better control your data environments and especially to access highly qualified data. In general, companies are looking to be more efficient and reduce costs to boost their profitability. As businesses approach the fall with a lot of skepticism, finding that cost/benefit balance is essential. According

Focusing on the concept of DaaS (Data-as-a-Service) allows you to better control your data environments and especially to access highly qualified data.

In general, companies are looking to be more efficient and reduce costs to boost their profitability. As businesses approach the fall with a lot of skepticism, finding that cost/benefit balance is essential. According to INSEE, health and economic constraints and uncertainties continue to have a significant impact, despite the 750 billion euros released by the European Union to support businesses. They must then rely on a rationalization of costs to get by, starting with those dedicated to IT infrastructures.

Efficiency and cost management: the winning combination

In recent years, the trend has been “always more” in IT – more data, more cloud, more applications, more infrastructures, and therefore more threats.

The main challenge for CIOs is to be able to cope with the flood of data despite the postponement of dedicated projects or the freezing of associated budgets:

do more with less.

In addition, thanks to the forced march towards telework generated by Covid, CIOs must be able to manage the acceleration of the digital transformation of companies as well as the development of cloud adoption.

As a result, companies are faced with the proliferation of data but also services and workloads. In addition to being stored in silos on various platforms, 50% of new data created can be considered as “dark data”, the value, or even the risk of which is not identifiable as it is by companies. As resources are not, or not very extensible (budgets, time, etc.), companies must seek to reduce unnecessary costs, especially generated by this type of data, in order to ensure long-term management of their business.

A single platform for intelligent data management

Most organizations store their data on servers equipped with a software layer designed to manage data access and viewing. As the number of software products and their interactions multiplies, we need a single, scalable platform to ensure cost control and greater efficiency. This same platform will optimize the standardization and centralization of data, essential for intelligent data management over the long term.

  • Finally, centralized data management will help companies:
  • reduce the risk and impact of transformation on services,
  • avoid the creation of silos related to the implementation of telework,
  • or reduce costs by taking advantage of supports hybrid or multi-cloud environments.

In terms of security, visibility into the data allows the company to judge their relevance and value, in order to isolate them on secure storage on which regular backups are planned if necessary. In addition, the most transparent possible implementation of additional services will limit the bottleneck phenomenon and therefore the impact on performance.

Leveraging standardization and automation to help focus on the essentials

Properly conducted data standardization will provide significant benefits to businesses. As new services were urgently deployed, data standardization provides a unique and accurate perspective on the environment by ensuring a seamless coexistence of over a thousand types of storage:

  • 60 cloud service providers,
  • 800 data sources,
  • and hundreds of operating systems available.

Finally, implementing automation will also be essential if the company wants to improve data management, reduce risks, or implement new services without a hitch.

In addition to technical and business benefits, the standardization and automation of data management induce a significant reduction in costs. By better understanding the environment, removing duplicates, or unused data, the business can make informed decisions, especially when it comes to storage.

For example, the least used data can be moved to less costly and energy-consuming storage. Managing and removing dark data will also help save money. But the most important thing here is to understand the storage architecture (both on-premises and in the cloud) in order to be able to implement the best possible strategy and avoid compatibility issues.

All these elements optimize the management of the costs of the companies, but above all reduce the risk and encourage the implementation of countermeasures when the companies have to face the attacks. Automatic failover of critical services and data recovery through integrated and offline backup systems are, for example, essential measures to be resilient.

In short: bet on dedicated platforms!

Typically, isolated data management products or services are not scalable enough to cope with their growth and complexity in complex environments. This is why a data management platform is the best solution:

it takes into account hybrid environments and is completely transparent at the infrastructure level. By allowing better control and increased efficiency in management, it ensures real visibility into the value of data and allows costs to be adjusted accordingly. In this way, any company will be able to take advantage of the data and even detect new competitive advantages, essential in time as uncertain as ours.

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