Cloud data platforms (CDP) and cloud data warehouses (CDW) offer immense potential for organizations to leverage their data assets and drive innovation. People are increasingly migrating from on-premises databases to cloud-based solutions due to the scalability, flexibility, and cost-effectiveness offered by cloud platforms. Cloud databases provide businesses with the ability to scale resources dynamically, adapt to fluctuating workloads, and reduce infrastructure maintenance overhead. Additionally, cloud databases offer features such as built-in security, automated backups, and seamless integration with other cloud services, making them an attractive option for modern data management needs.
However, as businesses increasingly rely on these platforms, managing cloud costs becomes a critical challenge. Dealing with consumption costs that can ebb and flow with workloads is a new challenge for those who formerly operated on-prem with restricted resources. Failing to understand this impact can leave budgets busted with unexpected bills.
Let’s delve into the cloud spend overview of CDP/CDW; examining key statistics, expense items, and factors driving expense growth. Additionally, we'll explore strategies for reducing cloud spend and highlight the importance of proper data quality and performance monitoring in cost optimization.
Cloud Data Platform (CDP) / Cloud Data Warehouse (CDW) Spend Overview
The adoption of cloud services continues to accelerate, with organizations investing heavily in CDP and CDW solutions. Uncommon about a decade ago, the market is awash in cloud data solutions. We all know the big ones; Snowflake, Google BigQuery, Redshift, and Databricks – and there are many more joining the market. Cloud computing is here to stay. Gartner forecasts worldwide public cloud spending to eclipse $679 Billion this year. Clearly, we cannot ignore the impact of cloud data operations on organizational data budgets.
Stats, Predictions, and Research Insights
Numerous studies and surveys offer valuable insights into cloud spending trends and challenges. For instance, an Anodot survey revealed that 44% of executives surveyed said their company wastes at least one-third of cloud spend each year, emphasizing the need for better cost management strategies.
The Usual Expenses:
So what are the usual suspects when it comes to cloud spend related to data?
- Compute: Represents expenses related to processing data and running applications within the cloud environment. Users running queries, applications serving up data from the database, and pipeline compute – all contribute to rising costs. It’s OK for compute resources and cloud costs to trend upward; as long as the increase is tied to a business outcome. No one gets fired for running a thousand dollar query worth hundreds of thousands in business value.
- Storage: Encompasses costs associated with retaining and managing data in cloud storage solutions, often based on volume and access frequency. Again, storing more and more data is not necessarily wrong. It’s all about storing the RIGHT data to support the business. If the data is useful and being used, by all means hold onto it.
- Data Movement: Arises when transferring data between different regions, availability zones, or services within the cloud infrastructure. Data pipelines are important. We have to move data from the point of acquisition through pipelines and processes to get it to the place where it is most useful. Data science data needs to go into the appropriate platform the same as operational reporting data does – these are likely different platforms. The key is to move the right data at the right times to meet business needs.
- Data Transformation: Involves cloud spend on converting, manipulating, or processing data to meet specific requirements or formats. The old saw of “data is the new oil” still rings true. Data as ingested is in a raw format and needs to be refined by transformational processes as it flows through pipelines to end up in the right format in the right end system.
Understanding and effectively managing these core components are crucial for optimizing cloud data expenditure and achieving cost efficiency.
Why Cloud Spend Grows Over Time
Despite the benefits of cloud data platforms, expenses can escalate over time due to several factors:
- Scalability: One of the primary attractions of cloud data platforms is their scalability. However, this very feature can also contribute to cost escalation. As businesses expand their operations or experience spikes in data usage, they often scale up their cloud resources to accommodate the increased demand. While this scalability is essential for meeting evolving business needs, it can result in higher costs if not managed efficiently. Without proper monitoring and optimization, organizations may end up over-provisioning resources, leading to unnecessary expenses.
- Complexity: Cloud environments can be inherently complex, especially as organizations adopt multi-cloud or hybrid cloud strategies. With various services, configurations, and pricing models available, navigating the complexities of cloud data platforms can be challenging. As a result, organizations may struggle to understand their cloud usage patterns fully, making it difficult to identify opportunities for cloud cost optimization. Complexity also increases the likelihood of configuration errors or inefficient resource allocation, further exacerbating cloud expenditure.
- Lack of Visibility: A lack of visibility into cloud usage and costs is a common challenge for many organizations. Without comprehensive monitoring and reporting tools, businesses may struggle to track their cloud spending accurately. This lack of visibility can lead to cost overruns, as organizations may unknowingly exceed their budget or fail to identify areas of inefficiency. Additionally, without clear insights into usage patterns and trends, organizations may struggle to forecast future cloud expenses effectively, making it challenging to plan and budget accordingly.
- Shadow IT: Where departments or individuals within an organization independently procure and manage cloud services without the IT department's oversight, can also contribute to escalating cloud costs. When different teams adopt cloud services independently, it can lead to redundant subscriptions, overlapping functionality, and inefficient resource utilization. Without centralized control and governance, organizations may struggle to monitor and manage these disparate cloud resources effectively, resulting in increased costs and potential security risks.
Ways to Reduce Your Cloud Spend
Cloud data is here for the foreseeable future. With our understanding of where the expenses come from, and how they grow over time, we can begin to right-size our spend. To mitigate the risk of escalating cloud expenses, organizations can implement the following strategies:
- Reduce Time and Cost of Data Issues Debugging Process: Implement automated monitoring and alerting systems to detect and troubleshoot data issues promptly. Automated oversight of ALL of your data is imperative to staying atop of fixing your data problems before costs get out of hand.
- Automation: Leverage automation tools to optimize review of data spend, performance, usage, and quality. With the increase in data and tools, human teams simply do not have time to successfully monitor for these crucial metrics.
- Data Freshness Issues: Address data freshness issues by optimizing data ingestion pipelines and implementing real-time data processing solutions. Your data-based decisions are only as good as the freshness of your data. Data that is not up to date will lead either to poor quality decision making affecting business outcomes, or time spent waiting on correction. Catching it early reduces this cost.
- Over-consumption of Data Warehouse Resources: Right-size data warehouse instances, optimize queries, and implement workload management policies to reduce resource overconsumption. Right-sizing your data space is essential to optimizing your data ROI.
- Data Integrity: Implement data quality checks, validation rules, and integrity constraints to ensure data accuracy and reliability.
- User Scenarios: Analyze user scenarios and usage patterns to identify optimization opportunities and tailor resources accordingly.
- Data Cleansing: Regularly cleanse and deduplicate data to eliminate redundant or obsolete records and reduce storage costs.
- Identifying Spending Patterns: Use cost analytics tools to analyze spending patterns, identify cost drivers, and optimize resource allocation.
- User Permissions and Incident Resolutions: Implement strict access controls, permissions management, and incident response procedures to prevent unauthorized usage and mitigate security risks.
How Proper Data Quality and Performance Monitoring Can Help
Proper data quality and performance monitoring are essential for cost optimization in cloud environments. By proactively monitoring data quality, performance metrics, and resource utilization, organizations can identify inefficiencies, prevent cost overruns, and optimize cloud spend. For example, ThoughtSpot's case study demonstrates how Revefi helped cut 30% of cloud data platform costs by implementing comprehensive data observability and governance solutions.
Why Revefi for Your Enterprise Data Observability and Cloud Cost Management
Revefi is a comprehensive and cohesive offering for enterprise data quality, usage, performance, and cloud cost management. With Revefi, organizations can gain real-time insights into their data pipelines, ensure data integrity, and optimize cloud spend. By leveraging Revefi's advanced monitoring, automation, and analytics capabilities, organizations can achieve greater efficiency, cost savings, and business agility in their cloud operations.
As organizations increasingly rely on cloud data platforms and data warehousing solutions to drive digital transformation, managing cloud costs becomes a critical imperative. By understanding common expense items, implementing cost optimization strategies, and leveraging proper data quality and performance monitoring, organizations can navigate the complexities of cloud spending and drive sustainable growth in the digital era. With Revefi's solutions, organizations can gain visibility, control, and cost savings in their cloud data operations, enabling them to unlock the full potential of their data assets and drive business success.
Advance your cloud spend and CDW performance monitoring with Revefi – request your FREE demo today!
