Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Google Cloud Professional Data Engineer (GCP-PDE) Certification with Practice Exam
01 Introduction to data engineering
02 Introduction to BigQuery (2:47)
01 Data Engineer role (10:11)
03 Data Lakes and Warehouses (3:06)
04 Transactional Databases vs Data Warehouses (2:55)
05 Manage Data Access and Production (2:20)
02 Building a data lake
01 Data storage and ETL options on Google Cloud (2:52)
02 Building a Data Lake with Cloud Storage (10:17)
03 Secure Cloud Storage (5:56)
04 Storing different data types (5:50)
05 Cloud SQL as a relational Data Lake (5:36)
03 Building a data warehouse
01 Building a Data Warehouse (5:38)
02 BigQuery for Data Warehouses (9:29)
03 Load data into BigQuery (9:29)
04 Schema design in BigQuery (3:40)
05 Example case scenario - Nested and repeated fields (6:43)
06 Optimize with Partitioning and Clustering (5:45)
04 Managing and Securing Dataflow Operations in Google Cloud with Dataflow
01 Beam Portability (4:47)
02 Separate Compute and Storage with Dataflow (4:20)
03 Dataflow Identity Access Management (4:40)
04 Google Cloud Dataflow Quotas (4:50)
05 Enhance security while running Dataflow (2:43)
06 Dataflow security features (4:14)
05 Essentials of Data Integration Techniques - From ETL to BigQuery Optimization
01 EL, ELT and ETL (4:12)
02 Build BigQuery Operations (3:09)
03 Using E-T-L (2:37)
04 Solve data quality issues with ETL (5:29)
06 Optimize Big Data Processing with Hadoop and Spark on Dataproc
02 Run Hadoop on Dataproc (8:00)
01 From Traditional Databases to Hadoop and Spark Ecosystems (5:06)
03 Cloud Storage vs Hadoop (5:20)
04 Optimize Dataproc (3:00)
05 Optimize Dataproc Storage (7:32)
06 Optimize Dataproc templates and autoscaling (4:24)
07 Optimize Dataproc monitoring (2:27)
07 Building Robust Data Processing Pipelines with Dataflow
02 How Dataflow works (3:20)
01 Using Dataflow (6:03)
03 Creating Dataflow pipelines with Python programming (5:07)
04 Designing a Dataflow pipeline (3:09)
05 Transform data with PTransforms (9:20)
06 Side inputs and windows of data (4:12)
07 Creating and re-using pipeline templates (3:49)
LAB - 01 Designing data processing systems
01.02 Data Encryption and Key Management (9:53)
01 01 Working with Identity and Access Management (IAM) (11:56)
01.03 Encrypt Data Uing Cutomer Managed Key (7:12)
01.04 Load data from Cloud Storage into BigQuery (6:51)
01.05 Run Queries in BigQuery (7:26)
Source Files
LAB - 02 Working with Dataprep
02.01 Data Cleaning and Validation using Dataprep (5:54)
02.02 Uing Dataprep to validate files from Cloud Storage (4:32)
02.03 Creating Plans in DataPrep (5:44)
Source Files
LAB - 03 Data Discovery and Inspection using Data Loss Prevention
03.01 Create a template in Data Loss Prevention (6:54)
03.02 Create scan configuration in DLP (3:11)
03.03 Create inspection job in Data loss prevention (5:07)
03.04 Visit Dashboard in Data Loss Prevention (3:22)
Source Files
LAB - 04 Work with Data Catalog, BigQuery, and Cloud Run
04.02 Perform data transfer using BigQuery (6:19)
04.01 Tag Dataet in Data Catalog (10:10)
04.03 Create a delivery pipeline (6:23)
04.04 Create a release in delivery pipeline (4:50)
04.05 Verify the release in Cloud Run (7:06)
04.06 Create a servoce in Cloud Run (4:11)
04.07 Connect to Github repository (2:48)
Source Files
LAB - 05 Working with Dataflow
05.01 Create a pipeline in dataflow (10:53)
05.02 Create a job in dataflow (6:36)
05.03 Work with SQL Workbench in Dataflow (8:59)
Source Files
LAB - 06 Create and work with Virtual Private Cloud (VPC)
06.01 Work with Virtual Private Cloud (VPC) (8:35)
06.02 Create a Virtual Private Cloud (3:47)
06.03 Create a VPC Network Peering (6:05)
Source Files
LAB - 07 Working with Cloud Composer
07.01 Create Cloud Composer Environment (6:26)
07.02 Accessing the Web Interface from the Google Cloud Console (3:51)
07.03 Get teh details of your Composer environment (6:51)
07.04 Get the Database Connection Parameters (2:00)
07.05 Get the Database Endpoint Address (2:30)
07.06 Work with DAGs (3:43)
Source Files
LAB - 08 Working with Cloud Datastore
08.02 View the database properties using the cloud shell (3:37)
08.01 Create a database using Cloud Datastore (4:43)
08.03 Store data in the database in Cloud Datastore (8:37)
08.04 View an entity in a database (1:48)
08.05 Run a query (3:02)
Source Files
LAB 10 - 10 Creating a SQL instance
10.02 Create a MySQL database on the instance (2:03)
10.01 Create an instance in Cloud SQL (11:18)
10.03 Create a table (4:24)
10.04 Import data into the table (4:07)
10.05 Create Views on the table (3:42)
Source Files
11 Work with Spanner
11.01 Work with Cloud Spanner (5:34)
11.02 Create a database in Spanner (5:48)
11.03 Create a table in Spanner (2:40)
11.04 Add data into a table in Spanner (3:49)
11.05 Update table schema (2:12)
11.06 Create an index (2:24)
Source Files
12 Work with Memorystore
12.02 View instance information (4:33)
12.01 Working with MemoryStore (8:30)
12.03 Edit an instance (2:14)
12.04 Delete an instance (1:36)
Source Files
13 Work with Pub-sub
13.01 Create a topic in pub_sub (5:09)
13.02 Create a subscription (6:44)
Source Files
14 Work with Cloud Data Fusion and Dataproc
14.01 Work with Cloud Data Fusion (9:55)
14.02 Required Custom roles and permissions (4:06)
14.03 Work with the data pipeline (9:45)
14.04 Role of Dataproc ith Data Fusion (5:43)
Source Files
Test Your Knowledge
Practice Exam
08.03 Store data in the database in Cloud Datastore
Lesson content will be unlocked within 30 minutes.
Teachable is working on this bug.
No further action will be required on your part
.
Thank you for your patience