Data Prep for Data Science in Minutes—A Real World Use Case Study of Telematics
Data exploration is an iterative and discovery oriented process. Data scientists spend an inordinate amount of time shaping and feature engineering their data in order to work on high value machine learning models. Come learn how Datameer can ease that complex data preparation process and allow you to focus on what matters most- developing the best model for your predictive analysis. In this session we will present an end-to-end Telematics use case to show you how you can get from zero to insight in minutes. Learn how Datameer provides easy integration with your Spark ML and Spark clusters.
1. Self-Serve Data Pipeline and Discovery Platform
Import / Link Prepare / Curate Discovery / Analyze Export / Deploy
Data Engineer Data Analyst
• Codeless Data Integration • Spreadsheet UI (No Coding) • Visual Data Insight Discovery • Export to Any Source
• 70+ Built in Connectors • 270+ Built in Functions • Second Response Times • View Full Data Lineage
• Any Size / Any Data • Transform / Enrich Any Data • Scale Across / Drill Down • Scheduling / Automation
Raw Data Production Data
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