The use of multiple cloud platforms presents significant challenges for decision-makers in enterprise organizations in the UK and Ireland, according to a report titled “A Silver Lining from Every Cloud” by SAS, a leading provider of analytics and AI solutions. The report highlights the difficulties faced by businesses that rely on various public and private cloud providers to host their data and applications. The study involved over 200 key decision-makers in data, analytics, and cloud services from companies with more than 3,000 employees in the UK and Ireland.

The Complexity of Multi-Clouds:

According to the report by SAS, organizations in the UK and Ireland are operating across an average of three private clouds. Furthermore, approximately 42% of these organizations rely on at least two public cloud providers for critical business functions, analytics, and hosting important data. These statistics highlight the prevalence of multi-cloud environments in the region and emphasize the complexity involved in managing data across multiple cloud platforms.

Decision-makers provided various reasons for adopting multiple cloud platforms. Firstly, concerns about relying on a single vendor were a major factor, as organizations seek to avoid vendor lock-in and maintain flexibility in their cloud strategies. Additionally, compliance and regulatory requirements play a significant role in the adoption of multiple cloud providers, ensuring that organizations adhere to industry-specific regulations and data protection laws. Furthermore, the need to integrate fragmented systems resulting from acquisition strategies contributes to the growing number of cloud platforms used by businesses.

However, the proliferation of cloud platforms also brings about significant operational challenges when it comes to extracting insights from data. These challenges can be quantified with specific statistics:

1. Inconsistent Answers: The report reveals that 64% of decision-makers experience multiple answers to the same question depending on the cloud in which the data resides. This discrepancy in responses can create confusion and hinder effective decision-making processes.
2. High Costs: Managing multiple clouds incurs additional costs for organizations. 64% of respondents reported high costs associated with operating across multiple cloud platforms. These costs include licensing fees, data transfer expenses, and the need for specialized skills to manage diverse cloud environments.
3. Delays in Obtaining Insights: The complexities of managing data across multiple cloud platforms contribute to delays in extracting valuable insights. The report indicates that 60% of organizations face delays in obtaining insights due to the challenges posed by multi-cloud environments.
4. Concerns About Accuracy: Almost half (48%) of decision-makers expressed concerns about the accuracy of insights derived from data residing in multiple clouds. This highlights the potential doubts surrounding the reliability and consistency of analytical outputs obtained from multi-cloud environments.

By providing specific statistics on the challenges associated with multiple cloud platforms, decision-makers can gain a clearer understanding of the extent to which these challenges impact their organizations. These statistics serve as quantitative evidence supporting the need for comprehensive solutions and strategies to address the complexities of multi-cloud environments..

Challenges Faced by Organizations:

One of the main challenges identified is the inconsistency of answers obtained from different clouds. This means that depending on the cloud in which the data resides, businesses may receive different answers to the same question, leading to potential discrepancies in decision-making processes. This inconsistency was reported by 64% of decision-makers surveyed. Moreover, high costs associated with managing multiple clouds pose a significant burden, also reported by 64% of respondents. The need to invest in different platforms, tools, and services across multiple clouds adds to the overall cost of operations.

Another challenge highlighted in the report is the time it takes to obtain insights from data. 60% of organizations reported experiencing delays in extracting valuable insights due to the complexities of managing data across multiple cloud platforms. This delay not only hampers real-time decision-making but also slows down the overall business process. In addition, 48% of decision-makers expressed concerns about the accuracy of insights obtained from their data residing in multiple clouds, raising doubts about the reliability of their analytical outputs.

Data Consolidation and Analytics:

The report also sheds light on the difficulties organizations face when consolidating data from various cloud platforms. 80% of businesses admitted to the need for regular data snapshots to be pulled into a central pool for analysis and decision-making. This process of data consolidation is time-consuming and resource-intensive. Furthermore, 70% of organizations reported using different analytics platforms on each cloud, leading to the need for consolidating and reconciling answers from various sources. This not only increases the complexity of analytics but also prolongs the time required to derive actionable insights.

The challenges organizations face in consolidating data from multiple cloud platforms have been acknowledged by various technology companies. Several companies have developed solutions to address these difficulties and streamline the process of data consolidation and analytics. Let’s explore some showcases from these technology firms:

1. Amazon Web Services (AWS): AWS offers a service called AWS Glue, which helps organizations automate the process of data preparation and consolidation. It provides capabilities for discovering, cataloging, and transforming data from various sources, including multiple cloud platforms. AWS Glue can be used to create data pipelines that consolidate data into a central data lake or data warehouse for analysis. By automating data consolidation tasks, organizations can save time and resources, enabling faster insights.
2. Microsoft Azure: Microsoft Azure provides Azure Data Factory, a cloud-based data integration service. It allows organizations to create data-driven workflows that facilitate the consolidation of data from different cloud platforms. With Azure Data Factory, users can orchestrate the movement and transformation of data, enabling the integration of data from various sources into a unified data store. This simplifies the data consolidation process and enables efficient analytics across multiple cloud platforms.
3. Google Cloud Platform (GCP): GCP offers a solution called Google Cloud Data Fusion, which enables organizations to build and manage data integration pipelines. It allows users to ingest, transform, and consolidate data from various sources, including multiple cloud platforms. Google Cloud Data Fusion provides a visual interface for designing data pipelines, making it easier for organizations to handle the complexities of data consolidation. By leveraging this solution, businesses can accelerate the integration and analysis of data across their multi-cloud environments.
4. Snowflake: Snowflake is a cloud-based data platform that provides a unified and scalable solution for data consolidation and analytics. It allows organizations to consolidate data from multiple cloud platforms and traditional data sources into a single, centralized data warehouse. Snowflake’s architecture separates storage and compute, enabling organizations to scale their analytics workloads based on demand. This flexibility, combined with its powerful query and data integration capabilities, simplifies the process of data consolidation and accelerates insights generation.

Overcoming Challenges in Multi-Cloud Environments

The reliance on multiple cloud platforms poses significant challenges for decision-makers in enterprise organizations. The report highlights the issues of inconsistent answers, high costs, delays in obtaining insights, and concerns about accuracy. These challenges arise due to the complexity of managing data across multiple clouds and the need for data consolidation and analytics. To overcome these challenges, businesses should carefully evaluate their cloud strategies, consider the potential trade-offs, and adopt comprehensive solutions that can integrate and streamline their cloud environments. By doing so, organizations can leverage the benefits of the cloud while minimizing the operational challenges associated with its proliferation.