Cost containment is a crucial aspect of managing any data team. It involves maintaining expense levels to prevent unnecessary spending or thoughtfully reducing expenses to improve profitability without risking long-term damage to the company. Here are seven strategies that data teams can use to contain costs when using Looker:
1. Prioritize High-Value Projects
Not all projects are created equal. Some will provide more value than others. Prioritizing these high-value projects can help contain costs.
- Identify projects with the highest potential return on investment (ROI).
- Allocate resources strategically to these projects.
- Postpone or cancel low-value projects that consume resources without delivering significant benefits.
2. Create a Cost-Conscious Culture
Creating a culture that values cost-efficiency can help contain costs. This involves educating team members about the importance of cost containment and encouraging them to make cost-effective decisions.
- Provide training on cost containment strategies.
- Encourage team members to suggest cost-saving ideas.
- Reward cost-effective behavior to reinforce the culture.
3. Establish Efficient Data Infrastructures
Efficient data infrastructures can reduce the amount of resources required to manage and analyze data, thereby containing costs.
- Use Looker's semantic modeling capabilities to streamline data management.
- Optimize data storage by centralizing it in Looker's platform.
- Reduce data redundancy and improve data quality to minimize storage costs.
4. Monitor Costs and Usage Continuously
Continuous monitoring of costs and usage can help identify areas where spending can be reduced. Looker's Cloud Cost Management Block can be instrumental in this process.
- Monitor multi-cloud spend to identify costly services or resources.
- Automate chargeback and billing to ensure accurate cost allocation.
- Use Looker's forecasting capabilities to predict future costs and adjust spending accordingly.
5. Collaborate with Vendors for Better Deals
Working closely with vendors can lead to better deals and cost savings. This includes negotiating contracts and seeking volume discounts.
- Negotiate Looker's platform and user pricing to get the best possible deal.
- Consider purchasing add-ons in bulk to secure volume discounts.
- Explore the possibility of getting a discount for long-term contracts.
6. Share Knowledge within the Industry
Sharing knowledge and best practices with other data teams can lead to new cost containment strategies.
- Participate in industry forums and events to learn about cost-saving strategies used by other data teams.
- Share your own cost containment strategies to get feedback and suggestions for improvement.
- Collaborate with other data teams to develop joint cost containment strategies.
7. Optimize Data Processes
Optimizing data processes can reduce the amount of time and resources required to manage and analyze data, thereby containing costs.
- Use Looker's integrations to automate data processes and reduce manual work.
- Optimize data workflows to minimize data processing time.
- Use Looker's data modeling capabilities to simplify complex data processes.
8. Maintain Data Hygiene
Maintaining data hygiene is crucial to cost containment. Clean, accurate data reduces the need for rework and ensures that resources are not wasted on incorrect data.
- Regularly clean and update your data to ensure its accuracy and relevance.
- Use Looker's data validation features to identify and correct data errors.
- Implement data governance policies to maintain the quality of your data over time.
9. Use Secoda to Automate Data Management
Secoda can help modern data teams reign in out of control data costs by providing a centralized platform for data search, cataloging, lineage, monitoring, and governance. This not only improves efficiency but also reduces the need for multiple tools.
Secoda helps automate various data management tasks, thereby reducing the time and resources required and containing costs.
- Use Secoda AI to automate tasks like documentation and generating dbt models.
- Utilize its contextual search feature to quickly find the right information, reducing time spent on data discovery.
- Leverage its data requests portal and automated lineage model to streamline data workflows.
