How data scientists and engineers can build models and data pipelines, and scale machine-learning rapidly while collaborating with the business
Does this sound familiar: experiencing performance and productivity issues with your data science and data engineering efforts on Apache Spark? Spending too much time managing your infrastructure instead of building machine-learning models, analytic apps, and data products? You are not alone.
See how Viacom, HP, and Hotels.com overcame these challenges to connect data science and data engineering using Databricks, the company that created Apache Spark. The results? Faster performance, scaled data processes, simplified infrastructure, streamlined workflows, and greater collaboration.
Ready to discover how unifying your data science, engineering, and analytics can benefit your company?
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