Lyft Engineering

OCTOBER 3, 2023

Consequences of Bad Hive Data Poor data quality in Hive caused tainted experimentation metrics, inaccurate machine learning features, and flawed executive dashboards. It will ensure the number of canceled rides for this day is not more than 3 standard deviations outside the 90-day historic mean.

Big Data 84

Big Data Metadata Data Warehouse Data 84

Cloudera

JUNE 15, 2021

Which security features we wish to enable – Kerberos, TLS, HDFS Transparent Data Encryption , LDAP integration, etc. You can include in this section services such as Apache Spark 3 , Apache NiFi or Apache Flink although these will require configuration of separate CSD s. verbose < 0 through to 3.

Cloud 81

Cloud AWS Kafka Management 81

Netflix Tech

DECEMBER 3, 2022

This time we’ll try to give justice to the intro and then we will focus on one of the very first features Dataflow came with. That feature is called sample workflows , but before we start in let’s have a quick look at Dataflow in general. Dataflow mock command is another standalone feature.

Data Pipeline 143

Data Pipeline Scala Metadata Food 143

ProjectPro

NOVEMBER 30, 2021

3) ETL Pipeline vs. Data Pipeline: ETL Pipelines are Batch-processed, and Data Pipelines are Real-Time Furthermore, ETL pipelines move data in chunks at regular intervals and in batches, and the pipeline might run twice per day or at a time when system traffic is low. How to Build ETL Pipeline in Python?

Process 52

Process Data Pipeline Data Warehouse AWS 52

Monte Carlo

MAY 17, 2023

Detect Data Incidents Faster 3. Fix Data Incidents Faster 4. Monitor For ML Model Feature Anomalies 56. Data observability platforms deploy features such as data lineage, query change detection, and correlation insights to determine where issues are occurring at the system, code, or data level.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Detect data incidents faster 3. Fix data incidents faster 4. Monitor For ML Model Feature Anomalies 56. Data observability platforms deploy features such as data lineage, query change detection, and correlation insights to determine where issues are occurring at the system, code, or data level.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52