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Unravel

Rightsizing Your Data Infrastructure: Optimizing Databricks Cluster and Workspace Configurations

Join us for another enlightening session in our Weekly Walkthrough series, "FinOps Metrics That Matter," where we focus on the critical aspect of rightsizing your Databricks infrastructure for optimal performance and cost-efficiency. Achieving the right balance between performance and cost is paramount. However, a striking 80% of data management experts grapple with precise cost forecasting and management (Forrester). The primary culprits? Insufficient granular visibility, data silos, and a lack of AI-driven predictive tools.

Data Platform Economics: Measuring and Improving Cost-per-Query in Snowflake

80% of data management experts struggle to forecast data-related cloud costs with precision (Forrester). The root causes? A critical shortage of granular visibility needed for accurate cost allocation, fragmented data siloed away from those who need it most, and a notable absence of AI-driven tools and automated processes capable of predicting future expenditures. Streamline your approach to cloud cost management and data operations with Unravel. Move beyond mere observation to take immediate, impactful action for transformative results.

Data Platform Economics: Measuring and Improving Cost-per-App in Databricks

80% of data management experts struggle to forecast data-related cloud costs with precision (Forrester). The root causes? A critical shortage of granular visibility needed for accurate cost allocation, fragmented data siloed away from those who need it most, and a notable absence of AI-driven tools and automated processes capable of predicting future expenditures. Learn how to get granular costs with ease using Unravel Data. Join this Weekly Walkthrough series, FinOps Metrics that Matter, to understand the critical benefits of drilling down into your costs at the most detailed levels.

KPIs for Cost Management: Evaluating Costs in Snowflake

Precise cost forecasting and management are essential, yet 80% of data management experts struggle (Forrester). The challenges stem from a lack of granular visibility, siloed data, and the absence of AI-driven predictive tools. Discover your new set of metrics to understand and optimize your spending with Unravel Data. Join this Weekly Walkthrough series, FinOps Metrics that Matter, to understand these core metrics to speak the language of both finance and data engineering, and bridge the gap between technical and business stakeholders.

BigQuery Cost Management

Effective cost management becomes crucial as organizations increasingly rely on Google BigQuery for their data warehousing and analytics needs. This checklist delves into the intricacies of cost management and FinOps for BigQuery, exploring strategies to inform, govern, and optimize usage while taking a holistic approach that considers queries, datasets, infrastructure, and more.

Configuration Management in Modern Data Platforms

In the world of big data, configuration management is often the unsung hero of platform performance and cost-efficiency. Whether you’re working with Snowflake, Databricks, BigQuery, or any other modern data platform, effective configuration management can mean the difference between a sluggish, expensive system and a finely-tuned, cost-effective one.

KPIs for Cost Management: Evaluating Costs in Databricks

Precise cost forecasting and management are essential, yet 80% of data management experts struggle (Forrester). The challenges stem from a lack of granular visibility, siloed data, and the absence of AI-driven predictive tools.Discover your new set of metrics to understand and optimize your spending with Unravel Data. Watch this Weekly Walkthrough series, FinOps Metrics that Matter, to understand these core metrics to speak the language of both finance and data engineering, and bridge the gap between technical and business stakeholders.

Databricks + Unravel: Achieve Speed and Scale on the Lakehouse

Companies are under pressure to deliver faster innovation, enabled by cloud-based data analytics and AI. In order to deliver faster business value, data teams are looking to achieve speed and scale through data and AI pipeline performance and efficiency. A recent MIT Technology Review Insights report finds that 72% of technology leaders agree that data challenges are the most likely factor to jeopardize AI/ML goals.