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1
Intro
2
About us
3
Bad data
4
Theory
5
Cost of Data Quality
6
Do things 100
7
Reasons for bad data
8
Data Quality Process
9
Data Platform Landscape
10
Governance Layer
11
Ingest Layer
12
Microsofts portfolio
13
DQS
14
Data Quality Matrix
15
Profiling
16
Profiling in Excel
17
Machine Learning SDK
18
Azure ML Data Prep
19
Python Profiling
20
FuzzyWuzzy
21
FuzzyGrouping
22
Console
23
Azure Data Cutter
24
Tags
25
Common Data Model
Description:
Explore a comprehensive data quality solution using Microsoft's Data Platform in this conference talk from PASS Summit 2019. Learn how to leverage Machine Learning Services, Common Data Model, Azure Data Factory, SQL Server 2019, and more to address data quality challenges. Discover the costs associated with poor data quality and understand the reasons behind it. Dive into the Data Quality Process and explore Microsoft's portfolio for data governance and ingestion. Gain insights into profiling techniques using Excel, Machine Learning SDK, Azure ML Data Prep, and Python. Examine fuzzy matching concepts and explore tools like Azure Data Cutter and Common Data Model to enhance your data quality initiatives.

Data Quality Round-trip in the MS Dataplatform

PASS Data Community Summit
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