Databricks is a cloud-based data engineering tool used to process and transform large amounts of data and explore the data through machine learning models. It combines data warehouses & data lakes into a lakehouse architecture.

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Was Sie lernen werden
Learn to integrate AWS with Databricks.
Learn Data Lineage, Databricks Tags and Data Catalog in Databricks.
Learn to implement RBAC (Role-Based Access Control) in Databricks.
Kompetenzen, die Sie erwerben
- Kategorie: Data Security
- Kategorie: General Data Protection Regulation (GDPR)
- Kategorie: Data Pipelines
- Kategorie: Personally Identifiable Information
- Kategorie: Extract, Transform, Load
- Kategorie: Data Validation
- Kategorie: Data Integration
- Kategorie: Data Quality
- Kategorie: Data Warehousing
- Kategorie: Fraud detection
- Kategorie: Data Lakes
- Kategorie: Databricks
- Kategorie: Data Cleansing
- Kategorie: Amazon Redshift
- Kategorie: Amazon Web Services
- Kategorie: Data Governance
- Kategorie: Metadata Management
- Kategorie: Data Management
- Kategorie: Role-Based Access Control (RBAC)
Wichtige Details

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12 Aufgaben
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In diesem Kurs gibt es 4 Module
Welcome to Week 1 of Data Governance with Databricks course. This week, you will learn about Introduction to Databricks on AWS. Additionally, you will learn about the benefits and features of Databricks and AWS Integration.
Das ist alles enthalten
9 Videos3 Lektüren3 Aufgaben1 Diskussionsthema
This week, we learn Data Classification Techniques including Data Lineage and Impact Analysis and Metadata Management and Data Catalogs. We will also learn about the Data Profiling and Quality Assessment, Data Cleansing Techniques and implement Data Cleansing Pipelines in Databricks.
Das ist alles enthalten
8 Videos1 Lektüre3 Aufgaben
This week, we will learn about RBAC, Data Access Control Models and Data security policies in Databricks. We will also learn how to implement RBAC in Databricks, and Data Security Best practices.
Das ist alles enthalten
10 Videos1 Lektüre3 Aufgaben
This week, we will learn about Data Governance in Data Pipelines including Data Lineage in Data Pipelines, ETL/ELT processes, Data Versiong and Change Data Capture. We will also about Data Governance Best Practices and Tools including Continuous Improvement of Data Governance Processes and implementation and applying best practices in Data goverance.
Das ist alles enthalten
14 Videos3 Lektüren3 Aufgaben
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