Tackling intelligent data management in the cloud

A circle of laptops connected to a cloud symbol - showing cloud connectivity
(Image credit: Shutterstock/Bluebay)

It is predicted that by 2025 there will have been 175 zettabytes of data generated, with machines already creating upwards of 40% of the world’s data annually. This exponential data growth is being driven by innovation, with many organizations widening their IoT networks and enhancing their cloud computing capabilities. The imminent arrival of 5G is set to be a major catalyst in this forecast, aided by an increasingly connected global population.

About the author

Greg Hanson is VP EMEA and LATAM at Informatica.

With this growth of data has come proliferation and fragmentation, which can significantly limit the value of the data insights extracted and used by companies. To truly achieve digital transformation and reap the rewards of effective data analytics, organizations require cloud solutions that enable them to seamlessly manage their ever-increasing volumes of information.

It is easy to lose sight of the fact that while there is only one cloud, there are multiple cloud providers. Organizations commonly choose to work with multiple cloud partners to ensure cloud sourcing resilience, but this also creates complexity in a world where data must flow freely and be readily available, yet it becomes fragmented across multiple cloud locations.

To help cut through the complexity and enable innovation, high quality data needs to be readily available and therefore a comprehensive cloud data management platform is an essential component. A platform which can access data from any cloud as well as on premise applications, can deliver data at any latency with elastic scalable processing and critically embeds quality to ensure the delivery of high quality, trusted data.

In this article, we will set the scene by exploring the concept of the intelligent data management cloud, before taking a closer look at the benefits of advanced data loading and ELT capabilities. Our aim is to highlight the solutions that are bringing clarity to the discombobulated cloud connectivity space and enabling future innovation.

Anyone, any platform, any cloud, any time

As it becomes increasingly important to harness data and put it to work, organizations are rapidly realizing the limitations of dispersed, fragmented data. Many organizations face a task of unifying data from across multiple platforms, clouds and siloed locations, but it must be achieved to unlock the opportunities of true digital transformation.

The solution required must be an end-to-end platform, capable of not only unifying data from various types of location, but also from different locations within the cloud itself. To effectively manage data regardless of where it is housed, AI and real-time data intelligence must be deployed to efficiently handle the process at scale.

Serving as a prime example, Informatica has led the cloud connectivity industry by designing and launching the first Intelligent Data Management Cloud, opening the doors to a range of important industry-firsts. One of the most important of these firsts has been the platform’s ability to enable data insights from vast data sets in minutes rather than months. This marks a significant step change in cloud connectivity capabilities, but also for the enterprise space more widely.

A powerful solution of this nature will also allow businesses to redefine the way in which every single business function operates, including customer experience, e-commerce, supply chain, manufacturing, analytics and data science. The upshot of this is that organizations can extract far greater benefits from their valuable data, empowering them to deliver new outcomes at an unprecedented rate.

It must be remembered that as heterogeneity of the cloud increases, from applications to analytics to infrastructure, it is still the data that matters most, not what surrounds it. Those who can connect the right data to the right consumers in a simple, secure way will be able to achieve true digital transformation.

Cloud-native at scale

By taking an API-driven approach that is based on micro-services, elastic and serverless processing can be achieved to enable scaling for all enterprise workloads. This can be achieved via solutions like the Intelligent Data Management Cloud, which bring all services together in a single cloud native platform for data integration, API integration and data management itself.

Ultimately, by becoming cloud-native at scale, organizations can simply throttle or scale up their processing requirements in line with business growth. Enterprises that take this approach will be able to access meaningful data-led insights regardless of latency and form, while simultaneously enhancing the democratization of data.

What we mean by democratization in this context is the ability to make digital information accessible to non-technical users in a seamless way, without IT intervention. This capability will ultimately empower various teams with high quality insights, ensuring that all business functions operate in a more data-driven way.

This approach can be enhanced further through cloud-native mass ingestion, enabling organizations to load and synchronize data to a multitude of applications. Examples of these include SAP, NetSuite, Zendesk, Salesforce, Microsoft Dynamics 365, Workday, Google Analytics and more.

Simplicity, productivity, scalability

An important factor in managing data across disparate systems, applications and clouds is adoption among Java developers and data scientists. Once given the ability to plug their codes into ELT pipelines, technical teams will be able to bring a string of important benefits to their data management process.

Simplicity is the primary benefit, with teams able to use preferred coding languages so as to write code and keep it on a single platform prior to deployment. Accelerated positivity is another key benefit derived from greater access and customization, with teams able to use the tools they are already familiar with for data management purposes.

The year of intelligent data management

The advanced capabilities discussed above are landmark breakthroughs in untangling cloud complexity, ones which will support and promote innovation in the future. Above all, 2021 will be remembered as the year of intelligent data management, specifically in terms of managing data across multiple applications, platforms and clouds in a way that has never before been possible. For the first time in history, organizations have the opportunity to load data from almost anywhere, and this will enable true digital transformation.

Greg Hanson

Greg Hanson is VP EMEA and LATAM at Informatica.