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1
Intro
2
Nielsen's Architecture (AT THE TIME)
3
Data Lake
4
Data Arrival Pain Points
5
Recovering from failures
6
Is it the end of the day yet? When do we process data?
7
Is it the end of day yet? Legacy answers to a legacy problem
8
Little Fires Everywhere
9
Auditing window? Let's design our metadata
10
Auditing Header Injection
11
Shipping Audit Window to Collection Point
12
Consuming Audit Data
13
In Context
14
Storing Data and Querying to Optimum
15
Designing Out Output Table
16
Shout out to my dad....
17
Optimizing PostgreSQL for Audit Queries
18
Managing Partitions with Apache Airflow
19
Offloading Data to History
20
Scheduling your spark job
21
It is not the end of the day
22
Alerts and add-ons
23
Alerting system
24
Detecting duplications
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore the intricacies of data auditing and workflow optimization in this 37-minute conference talk from NDC Conferences. Dive into Nielsen's robust Kafka architecture and ETL processes, uncovering strategies to track, analyze, and store auditing information. Learn about implementing an AVRO Audit header, designing metadata for auditing heartbeats, and optimizing auditing tables. Discover how to create an alert-based monitoring system using technologies like Kafka, Avro, Spark, Lambda functions, and complex SQL queries. Gain insights into managing partitions with Apache Airflow, offloading data to history, and scheduling Spark jobs. Understand how to detect duplications and implement an effective alerting system. Finally, tackle the age-old question: "Is it the end of the day yet?" through the lens of data processing and legacy problem-solving.

Auditing Your Data and Answering the Question - Is It the End of the Day Yet?

NDC Conferences
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