AML Demo 2017

An in-depth walkthrough of Paxata capabilities. The objective: Prepare a clean and complete dataset which supports a time-sensitive Anti-Money Laundering (AML) analysis. Introduction: 0:12 Common Data Challenges 0:57 AML Data Preparation Process with Paxata Paxata in Action: 1:52 New project creation 2:13 Brief overview of data library and project UI 2:58 Data profiling and quality checks on full dataset 3:57 Filter out the noise, focus on the signal 4:22 Data shaping ('Group By' in this case) 5:03 Combine with database table using join detection 5:48 More data profiling to confirm accuracy of key attributes 6:41 Intelligent data cleansing using built-in text algorithms 7:30 Outlier detection and resolution (using find+replace) 7:52 Merge in external data 8:13 Smart import detection of semi-structured XML file 9:03 Split column with visual preview 9:14 Save a lens (data snapshot) to capture final AnswerSet (output) 9:27 Inject missing data on the fly 9:37 Use Step Editor to mute, modify, reorder, and manage steps in real time 9:46 Inject a new step with built-in append intelligence 10:10 Drag-and-drop step reordering 10:31 Export AnswerSet to Tableau Server 10:52 Link back to Paxata data lineage using ClicktoPrep™ 11:28 Activate column lineage and version history 11:52 Automate the end-to-end data prep workflow Feel free to view this video at a higher speed by clicking on the Settings (gear icon) and selecting your preferred Speed setting.