Data 360

Data 360 explained one step at a time, from ingesting data to acting on it.

Data 360 (formerly Data Cloud) is powerful, and it can be challenging to jump in and navigate. In this series, I build it up piece by piece, from ingesting data and mapping it to the data model through identity resolution and segmentation, so you can see how the parts fit together.

Whether you’re just starting with Data 360 or already working with it, the goal is to understand each core component and what it can do.

Formerly the Data Cloud Diaries series, and some of the video titles still use that name.

Data Cloud Diaries: Ingesting Data from Amazon S3 (5.1)
Data Cloud Diaries: Querying Data from Data Lake Objects (DLOs) using the REST API (5.2)
Data Cloud Diaries: Step by Step Data Stream to Data Lake to Data Model Objects (5.3)
Data Cloud Diaries: Initial Mapping and Loading Individual DMO from Amazon S3 (5.4)
Data Cloud Diaries: Data Model Mapping from Standard and Custom Data (5.5)
Data Cloud Diaries: Mapping to Party to Prepare for Identity Resolution (5.6)
Data Cloud Diaries: Identity Resolution, Match Rules, and Reconciliation Rules (5.7)
Data Cloud Diaries: Segmentation, Creating Sets of Data to Act On (5.8)
Data Cloud Diaries: Accessing DMOs through Salesforce and APIs (5.9)
Data Cloud Diaries: Accessing DMOs from Apex, from default Data Space (5.10)
Data Cloud Diaries: Using Ingestion API for Airline Flight Data - Part 1 (5.11)
Data Cloud Diaries: Using Ingestion API for Airline Flight Data - Part 2, the C# Bridge Code (5.12)
Data Cloud Diaries: Using Bulk Ingestion API for Airline Flight Data - Part #1 (5.13)
Data Cloud Diaries: Using Bulk Ingestion API for Airline Flight Data - Part #2 (5.14)
Data Cloud Diaries: Creating a Calculated Insight from SQL (5.15)
Data Cloud Diaries: SQL Calculated Insight Development (5.16)
Data Cloud Diaries: Accessing Calculated Insights through Data Cloud API (5.17)
Data Cloud Diaries: Creating a Streaming Insight (5.18)
Data Cloud Diaries: Using Data Actions to Send Platform Events to Salesforce Core (5.19)
Data Cloud Diaries, Data Transformation Demo (5.20)
Data Cloud Diaries: JDBC Driver Access into Data Cloud from DBeaver (5.21)
Data Cloud Diaries: Using Data Spaces to Separate Your Data and the Extra Steps to Connect (5.22)
Data Cloud Diaries:Amazon S3 Revisited (5.26)
Data Cloud Diaries: Overview of Methods for Loading and Ingesting Data into Data Cloud (5.23)
Data Cloud Diaries - Deeper in to Data Streams (5.27)
Data Cloud Diaries - Ingesting from Amazon S3 - Cool Updates (5.24)
Data Cloud Diaries - Enhancing the Data Stream. (5.28)
Data Cloud Diaries - Data Cloud Triggered Flow (5.25)

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