IDC Report Highlights Cloud Data Management Challenges

Digital-first cloud data management is the future. A survey by the International Data Corporation (IDC) found that “90% of European organizations consider it crucial to have a digital-first strategy to achieve business value from more of their data.” However, only “32% of data available to enterprises is put to work.” This leaves a concerning 68% of enterprise data completely unleveraged. It’s no secret that most organizations are migrating sensitive data to the cloud, but preparing data management frameworks and practices for this future is not always simple or easy.

A new InfoBrief from IDC surveyed a variety of European data professionals to assess the most prevalent challenges facing modern cloud data management. By examining these challenges and understanding how they affect optimal data use, we can look toward solutions for effective cloud data management.

The “Aspiration Gap” in Cloud Data Management

Before examining these challenges in detail, it’s important to understand the difference between common data use expectations and the somewhat sobering realities. When asked about data-related aspirations, 83% of IDC’s survey respondents emphasized their organization’s desire to become data-driven. However, only 30% reported widespread data use in their organization’s decision-making processes.

This significant disparity between the desire to be data-driven and the number of actual data-focused practices is what IDC identifies as the “aspiration gap.” Organizations intend to operationalize and enhance their cloud data practices, but do not seem to be taking the necessary steps to do so. Further emphasizing this gap, only 20% of IDC’s respondents claimed “better insights from data” as the business outcome of their IT modernization and cloud migration strategy. This comes in spite of the fact that “becoming data-driven” was an objective of more than 75% of cloud adoption projects.

Each of these findings demonstrates the toll that the “aspiration gap” takes on the likelihood of organizations fulfilling their cloud data goals. It’s clear that teams want to derive higher-impact insights from their cloud data, but there are challenges stopping them from reaching their full potential.

Top Challenges for Cloud Data Management

Recognizing the “aspiration gap” is one thing, but digging deeper into its root causes is the first step towards optimizing cloud data management and analysis. The three most common challenges the IDC report identified are:

Data Access and Governance

When asked why data collected by their organizations is not translated into actionable business insights, respondents’ top response was issues with data governance and data access. In total, about 95% feel that access and governance difficulties are either a “Minor Challenge,” “Challenge,” or “Major Challenge” affecting their business success. What’s more, 62% of those surveyed claimed a lack of proper data access governance as a limiting factor in achieving business objectives. The impact that poor data governance can have on the success of a business is not to be underestimated.

Respondents ranked both access and governance in the “Most Challenging Cloud Data Management Areas” as well, with 28% highlighting identity and access management and 23% finding trouble with governance. This was by far the most prevalent issue, and therefore the biggest bottleneck to optimizing cloud data management.

If cloud data is not managed properly, the ramifications can spread much further than just business objectives. Issues with controlling data access can have a detrimental effect on security and privacy, giving bad actors a better chance at accessing sensitive information. They can also lead to legal troubles, as data that isn’t governed effectively likely isn’t compliant with data privacy regulations like GDPR. Organizations can collect and store petabytes of data, but it won’t be an asset to the business if it can’t be accessed efficiently while being monitored for secure governance and compliance.

Dispersed Data Resources

Second on the list of common challenges to data-driven business insights is the abundance of siloed and fragmented data resources. In each of these scenarios, data is taken from a common repository and stored instead in a diverse array of locations within the data environment. This can make cloud data management extremely difficult.

Data silos occur when raw data is stored and controlled in an isolated location in the data ecosystem. These remote silos, likely limited to single departments or lines of business, are unable to actively communicate with other similar parts of the data stack. Data fragmentation is a similar phenomenon, in which data is broken up (intentionally or unintentionally) and stored in various locations across the data ecosystem. Consequently, the data is only accessible by a limited group, which hinders data sharing and holistic collaboration.

Both data fragmentation and data silos stunt accessibility and create a difficult environment for data governance and compliance. When asked what capabilities are essential for data use and resilience in the cloud, survey respondents highlighted the importance of data integrity and quality (28%) and data mobility (24%). If data is siloed or fragmented, it becomes exponentially more difficult to guarantee quality and mobility. It also becomes harder to enforce data access policies and secure the data from leak, breach, or worse. This often leads to hesitancy or inability to leverage all of the useful data within the group’s cloud data environment.

Locating Data in a Lacking Infrastructure

The third most prevalent challenge might be the most straightforward–respondents feel that lack of visibility can make data hard to locate. As more data and more users are added to data ecosystems, visibility can quickly become a nightmare without effective cloud data management. IDC reports that “46% of people don’t have enough data and information available to make decisions.” Without the ability to locate leverageable data, users won’t be able to discern timely and relevant insights.

IDC defines effective data stewards as those who are “identifying their weaknesses and investing in purpose-built platforms to meet their specific shortcomings and build a resilient data-ready architecture.” Those who remain unaware of cloud data management shortcomings or are not actively working to address them are referred to as “data laggards.” According to survey data, data stewards are found to be three times more successful at accessing, contextualizing, and visualizing relevant data in a timely manner.

This is why it’s important to create a resilient, scalable data infrastructure early in cloud data migration processes. Stewards take action to invest in data management, compliance, access, on top of visualization and analytics architectures. By proactively designing in tools that facilitate data discovery and accessibility, cloud data management frameworks become inherently more useful and effective for all stakeholders.

How to Optimize Cloud Data Management

How can data platform teams overcome ineffective data access and governance methods, siloed data, and an overall lack of visibility blocking organizations from meeting their data aspirations, and optimize modern cloud data management?

IDC’s research concluded that a “data control plane with embedded governance and data security, including access controls, can usher in a new operational culture that is fit for the new data-driven era.” Implementing a data access platform that can discover, secure, and monitor your organization’s increasing amounts of data can overcome each of these challenges with no fuss. Dynamic attribute-based access controls and automated audit logs can clear up issues with access and governance, universal platform-agnostic policies ensure enforcement and access wherever data is stored, and scalability will ensure that new users are seamlessly provided the appropriate access and visibility. Operationalizing a data access platform will optimize cloud data management and eliminate the “aspiration gap” stifling your data’s success.

While we highlighted some of IDC’s survey findings, there’s much more in-depth information about overcoming cloud data management challenges in the full IDC InfoBrief. For a look at how simple data access can be with Immuta, try our self-guided walkthrough demo!

Learn more about facing cloud data management challenges

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