Explore the intersection of data security and data quality strategy in this 37-minute conference talk from Louisville Infosec 2014. Delve into the importance of trusting and securing data, understanding the difference between simple and simplistic approaches, and examining data quality through the lens of workflow transparency. Learn about data measurements, the potential pitfalls of big data hype, and the challenges of balancing data repair costs with organizational risks. Gain insights into data governance, data maturity assessment, and the role of data architecture in designing effective data storage and movement guidelines.
Overview
Syllabus
Intro
Do you trust your data?
How secure is our data?
Difference between simple and simplistic...
Data Quality is SIMPLE.
Workflow Transparency
Example Oil Processing Flow
What does your data manufacturing process look like?
Additionally - Data Security?
Data Measurements
Caution: Big Data Snake Oil
Summary of Challenge The cost of repairing data manufacturing systems must be weighed while including risks included in the previous sides among others identified within your organizations
Data Governance (DG)
Data Maturity Data Maturity - An assessment "thermometer" with gradients beginning with othroughs Each level has a set of organisation specific criteria that defines characteristics of data expected to be found at each of the levels
Data Architecture Technology focused rules and guidelines on how data storage and movement should be designed
