How to Embrace the New Phase

Businesses are now starting to take a more data-intensive approach to business, one supported by a range of new technologies. Modern business is increasingly facing digital disruption as new competitors emerge and existing ones compete to adjust their strategies for the future. New technologies enable companies to gain a clearer understanding of customer behaviors and preferences, while providing the tools they need to respond more quickly.

Ronald van Loon is an HPE Partner and recently acquired Matt Maccaux, the Global CTO of Ezmeral Enterprise Software BU at Hewlett-Packard Enterprise, who provided meaningful insights into key shifts, key technologies and the right steps companies need to take to embrace a new phase in the company’s data and analysis landscape.

A significant amount of data is generated every day and data volumes are expected to increase significantly within the next 5 years. According to Statista, the amount of digital information generated in 2020 was estimated at 64.2 zettabytes – a number that will grow to 180 zettabytes by 2025.

With such an enormous flow of raw information, companies need solid technology platforms and infrastructures that are capable of handling it. This is where the concept of big data comes in, with tools like Hadoop under its open-source Apache license to help companies scale their activities.

Important trends

Companies are embarking on a new phase of digital transformation that focuses heavily on data centers as a critical asset and a driving force for competitive advantage. From this perspective, data is not just an extension to existing IT architectures, but rather as the central nervous system for new business areas, such as managing customer experiences or product innovation.

“As part of this digital transformation – organizations are taking a hard look at their traditional data sources, data streams and data processes and data utilization systems, ”Matt says about these new macro trends in digital transformation, where data real estate is really what is in focus for companies.

A few key trends in the field of digital transformation include:

  • Increasing emphasis on integrating analytics into the day-to-day running of businesses.
  • Increased focus on artificial intelligence.
  • The transition to cloud-native platforms and microservices.
  • The construction of a hybrid data architecture.

The shift to a more digital approach to business strategy has increased the demand for technologies that can help process, extract and manage large amounts of data.

Cloud-native environments

Cloud sets the pattern for this digital transformation. Cloud technologies, with their ability to support a large number of users across affordable geographic locations and time zones, also redefine how data is managed and processed. As a result, companies looking to achieve digital transformation need to develop solutions that are robust enough for continuous use by many people and can handle different types of data.

Cloud-native applications are part of an approach that includes a cloud-first and agile development strategy that results in more efficient solutions. Cloud-native applications run on the same infrastructure as any other type of software application and are inherently less complex to implement, manage, and upgrade. They have smaller resource footprints than their traditional counterparts thanks to microservice architectures with components that can either be centrifuged or closed depending on need.

Cloud also provides flexibility that allows companies to run multiple data centers rather than one large, central facility, known as multi-cloud. In addition, cloud platforms enable organizations to easily copy their actual workload to the cloud for disaster recovery purposes.

Cloud platforms also support various advanced analysis tools for data management and processing, such as business intelligence and self-learning for self-service. Artificial intelligence is another area where cloud technologies have a significant impact by offering more flexible, cost-effective ways to deliver AI solutions.

Data center speed to bring cloud principles forward

Traditionally, cloud-native principles could not be fully achieved by systems due to lack of computing power and speed from data centers, resulting in companies relying on more traditional hardware systems. However, that is changing with the speed of data centers, which have evolved to handle huge amounts of high-speed information.

The emergence of fast and efficient microservice frameworks is another important trend that enables cloud-native principles. Microservices, as the name suggests, are standalone devices that do one thing well. Each microservice has a specific function that can be updated and replaced without disturbing the overall functionality of the system.

Micro-service architectures allow companies to respond quickly to changing business needs with smaller development teams. It is estimated that companies like Netflix have saved significant amounts in annual infrastructure costs by implementing microservice-based architectures.

Micro-service architecture also allows for increased flexibility in implementation. Instead of having a large and expensive system that is around the clock, companies can now optimize the value they get from their data by ensuring that it is only available during business hours when people are likely to use it.


The most important cloud principle now being unlocked due to the higher availability of computing power is the concept of containerization. Containers allow a single logical unit to run on many different machines. Because the container is independent of other systems, it can be easily moved between data centers and managed using cloud-native tools.

Key technologies for data and analysis recording

The following are the key data and analytics technologies that help companies achieve digital transformation:

One of the most important data and analysis technologies that will drive digital transformation is Kubernetes. This technology provides a way to effectively manage containers in cloud environments that can be scaled automatically based on demand. For example, if a company has many different projects running at the same time, it must ensure that each one has access to resources based on their needs – which can be achieved with Kubernetes.

Kubernetes plays an important role in helping companies deliver and support multiple applications with high availability. This technology helps companies provide reliable access to data for their users. Effective Kubernetes implementation involves ensuring that apps are highly accessible on bare metal resources and also implements self-healing and autoscaling features.

Another technology that is becoming more and more popular in the data and analytics field is Apache Spark. This framework provides rapid analysis of large amounts of unstructured data.

Spark comes with its own cluster manager, administration console and integrated tools to help companies collaborate across multiple users. It simplifies the ability of business analysts to combine their work with different projects.

Steps for cloud-native data management and real-time analytics

The only thing left, of course, is to put it all together. With the right combination of cloud-based computing power and new technologies, companies can overcome some of the challenges they face.

  • The first important consideration is to find as many open source solutions as possible to avoid lock-in.
  • The next step is to streamline business processes and data management so that employees spend less time on routine tasks and can redirect more of their efforts to strategic initiatives.
  • Finally, companies should choose cloud computing partners that offer real-time data features through a more collaborative approach rather than a full-stack approach.

By using this tactic, companies can effectively manage their data and analytics projects. Although each organization is different, the most important common premise is to manage large amounts of data efficiently.

Ready for the paradigm shift?

Digital transformation is an infinite process that is constantly changing. The key to getting started with digital transformation and to drive it forward is to have strong partners and the ability to build your own technical resources to ensure that you are able to manage all your data efficiently. By using cloud-native technologies and using open source projects, companies can more effectively manage data and analytics environments.

By Ronald van Loon

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