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8 min read

Dear Rest of the Company — WTF!? Someone is Draining My Data Budget!

In today’s intricate and interconnected business world, data has become a vital asset that fuels decision-making, innovation, and operational efficiency. This surge in data demand within companies has, however, led to rising costs. And as all data leaders know, with higher demand for data comes higher expenses.
Managing out-of-control cloud spending is already a major headache for data teams. But with the explosive growth of generative AI, data leaders are bracing for even higher cloud costs in 2024 to support the increasing use of AI models.

We are going to look at how you can tame your data spend, but before you read how here’s a printable list you can share with your colleagues or post on the canteen wall or break out area, highlighting how they can be a solution to data cost spikes, rather than the cause. 

The Main Issue: Lack of Data Usage Visibility

The biggest challenge in controlling data costs is often figuring out what’s causing these expenses and how to address them. This is because there’s a lack of visibility into how data is used, not just how it’s processed. Most issues related to reducing cloud waste stem from this core problem.
If an organization can see how its data cloud resources are used—like which data product is being created, at what stage in the pipeline, and which teams are using it—they can make smarter decisions about resource management. This visibility would help pinpoint people or teams that frequently leave environments running or refresh data in real-time for reports that are only generated once a month, unnecessarily racking up costs.

Unfortunately, most organizations lack this visibility because Data Cloud provider bills only show data storage and computation charges over a specific period. So while we have observability tools that map out usage, they are not focused on cost. But understanding and monitoring costs is crucial for budgeting, planning, and managing data cloud spending.

The Solution: Making Data Visibility and Responsibility a Team Effort

Imagine a scenario where every department in a company understands the true cost of the data they use. Marketing teams become more mindful of the costs tied to high-resolution campaign assets. Sales departments might rethink the impact of duplicated customer information on the data pipelines between Salesforce and Snowflake. This kind of empowered ownership fosters accountability, leading to smarter data practices and, ultimately, reduced costs.

Achieving this shift involves two key steps. First, organizations need to ensure transparency. Data analytics tools that highlight storage usage and processing costs at the domain level are essential. Second, fostering a culture of data ownership is crucial. Clear communication channels empower individuals across departments to understand the impact of their data choices.

By working together, data teams can equip departments with the tools and knowledge needed to make informed decisions about data storage, computing and usage. This collective effort breaks down silos, promotes collaboration, and drives a more cost-effective approach to data management. In essence, empowered data cost ownership isn’t just about saving money—it’s about maximizing data to drive innovation.

Five Steps to Enhance Data Accountability

  1. Raise Awareness Through Transparency

    Ensuring the continuous transparency of the cost of data to the users of data should be the cornerstone of any steps to enhance accountability. This needs to make cost awareness a natural part of the decision making process of individual teams and departments when it comes to data usage. To achieve this, organizations need to shift their approach and find the correct tool that gives full transparency of cost implications to every stakeholder in the business, and not just the data team.

  2. Implement Active Data Governance Policies

    While it is important to establish clear data governance policies that outline best practices for data usage, storage, processing and runtime, these should not be merely guidelines. To ensure adherence these need to be a set of active policies that provide the guide rails to keep users in line with the data usage strategy of the organization.

  3. Encourage Cost-Effective Data Practices

    Promote the adoption of cost-effective data practices across the organization. Implement monitoring tools to track data usage and provide regular reports to team leaders, highlighting areas where costs can be reduced. It’s like having a fitness tracker for your data – trim the fat!

  4. Foster a Culture of Shared Responsibility

    Cultivating a culture where everyone feels responsible for managing data costs is crucial. The first step to a shared responsibility is awareness and ownership. This can only be truly achieved by integrating data cost management and performance metrics into the routines of all data users within the organization. When teams understand that cost-effective data practices are a shared goal, they are more likely to collaborate and contribute to overall cost savings.

  5. Utilize Automation and Optimization Tools

    Leveraging automation and optimization tools is the only method to effectively streamline data management processes. Automated data lifecycle management can help enforce cost policies, while optimization tools can also identify and rectify inefficient data practices, providing actionable insights to reduce costs. Think of such tools as a sophisticated air traffic control system for your data ecosystem: constantly monitoring the flow of data to ensure efficiency, cost effectiveness, and optimal resource utilization.

 

Ushering In A New Era of Data Visibility, Attribution and Explainability

Being able to clearly view and trace flows of data from its origin through its transformation journey, to how it’s being used, when and by whom, allows data leaders for the first time to bring the ultimate clarity to their organization’s data usage.

Seemore Data empowers data leaders to elevate their operations by providing comprehensive visibility, significant cost savings, and enhanced productivity. By offering full transparency across the modern data stack, we enable leaders to gain deep insights into usage patterns, costs, and performance metrics. This clarity allows organizations to achieve substantial savings — up to 40% — by identifying and eliminating idle resources and mitigating expensive demand spikes. The resulting cost efficiencies create opportunities for data teams to reinvest those savings strategically, focusing on high-impact data products that drive tangible business value. With Seemore Data, data leaders can simultaneously optimize their current operations and fuel future innovations, creating a virtuous cycle of improvement and value creation.

 

Time to Share Data Responsibility and Accountability

Data cost spikes are often an unseen consequence of actions taken by various teams within a company. By fostering awareness, implementing robust data governance policies, encouraging cost-effective practices, promoting shared responsibility, and utilizing automation tools, organizations can effectively manage and mitigate these costs.

Remember, effective data cost management is not just the responsibility of data teams – it’s a collective effort that requires collaboration and commitment from everyone in the company. By working together, you can ensure that your data remains a valuable asset without becoming a financial burden by limiting those WTF moments when it comes to your data budget.

And don’t forget to get your colleagues on board by sharing this ‘Dear Rest of the Company: Our Data Budget Has a Few Favors to Ask You’ list of action items they can follow to be part of the solution rather than part of the problem. 

Are you interested in continuing this discussion directly with Guy? You can message him at guy@seemoredata.io to delve deeper into how to ensure data responsibility and accountability in your organization.

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