Databricks Workloads Optimization
Reduce Costs, Accelerate Processing
Cut Costs, Boost Efficiency
In an era where data inefficiencies and high costs are prevalent, GlobalDots introduces our curated solution for Databricks Optimization, which improves application performance by optimizing on the runtime level and dynamically adjusted autoscaling. This solution directly tackles lengthy data processing and rising expenses, delivering a streamlined, continuous & autonomous effective approach to optimize Databricks workloads.
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Average 23% Reduction in processing time Improvement -
Average 30% Cost reduction -
Up to 80% Reduction in engineering time
Your Benefits
Enhanced Data Processing
Achieve more in less time with a 23% reduction in processing time across Spark workloads in Databricks environments – crucial for fast-paced business environments
Improved Performance
Databricks Workloads Optimization allows data engineering & data science teams to improve performance and their efficiency
Real-Time Orchestration
Avoid constant monitoring and benchmarking with autonomous and continuous optimization, custom tuning workload resource capacity specifically for your Databricks workload
