#Databricks-notebooks

Showing 8 of 8 repositories tagged #databricks-notebooks, ranked by stars

Azure-Samples
Azure-Samples
azure-databricks-mlops-mlflow

Azure Databricks MLOps sample for Python based source code using MLflow without using MLflow Project.

Score
0
★ 97 ⑂ 61
Jupyter Notebook
microsoft
microsoft
A-TALE-OF-THREE-CITIES

Analyzing the safety (311) dataset published by Azure Open Datasets for Chicago, Boston and New York City using SparkR, SParkSQL, Azure Databricks, visualization using ggplot2 and leaflet. Focus is on descriptive analytics, visualization, clustering, time series forecasting and anomaly detection.

Score
20
★ 87 ⑂ 37
R
osin-vladimir
osin-vladimir
architect_big_data_solutions_with_spark

code, labs and lectures for the course

Score
0
★ 48 ⑂ 37
Jupyter Notebook
jrlasak
jrlasak
databricks_apparel_streaming

Databricks DLT Apparel Pipeline Project: Learn medallion architecture, streaming, and data engineering with Delta Live Tables. Includes synthetic data, step-by-step guide, and certification prep.

Score
100
★ 45 ⑂ 30
Python
jrlasak
jrlasak
databricks_data_engineer_associate_cert_prep

Databricks Data Engineer Associate Certification Lab: End-to-end hands-on project covering Auto Loader, Medallion Architecture, SCD Type 2, Unity Catalog governance, and Databricks Jobs orchestration. Build a production-grade pipeline on Databricks Free Edition.

Score
80
★ 44 ⑂ 29 +1/day
Python
databrickslabs
databrickslabs
splunk-integration

Databricks Add-on for Splunk

Score
0
★ 29 ⑂ 20
Python
jrlasak
jrlasak
databricks_optimization_techniques

Delta Lake Optimization Project: Hands‑on lab to explore partitioning, Z‑Ordering, compaction (manual & auto), Liquid Clustering, and VACUUM using a synthetic sales dataset in Databricks. Includes a step‑by‑step notebook to measure file scans, bytes read, and query performance for each optimization.

Score
60
★ 20 ⑂ 29 +1/day
Python
jrlasak
jrlasak
databricks_fintech_monitoring

Databricks Real-Time Fintech Monitoring Pipeline: Hands-on lab to build a streaming fraud detection system using Auto Loader, watermarked deduplication, stream-static joins, and windowed rules engines in Databricks. Covers dual-SLA architecture for real-time alerts and batch compliance reporting.

Score
40
★ 12 ⑂ 11
Python
Related Topics
#databricks#data-engineering#pyspark#hands-on#azure#python#azure-databricks#etl#medallion-architecture#delta-lake#ml#ml-monitoring

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