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Salesforce and Snowflake Native Data Integration Options

Introduction

Salesforce and Snowflake became strong technology partners more than a year ago. That partnership fruited prebuilt, bi-directional integration options between the two leading platforms in CRM and Data domains. The solution offers easy-to-use, point-and-click integration to push CRM data into Snowflake Data Cloud and also receive analytics data from Snowflake into Salesforce. The native Salesforce and Snowflake integration is built on top of Salesforce Tableau CRM (recently renamed CRM Analytics).

Architecture

From a technical perspective, there are 4 options that the Salesforce-Snowflake native data integration features can offer:

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Veeva Nitro and AWS SageMaker for Life Sciences Data Scientists

Introduction

There is a rise in industry-specific data analytics solutions because building up and maintaining custom data warehouses is difficult. It requires extensive development and operational efforts to define the appropriate industry-specific data model for the business intelligence tools, follow all the shape changes over time (new tables, new columns, new relationships) and design the ETL processes for a wide variety of data sources. It is just hard to build a solution on top of a generic data warehouse where you can get great platform capabilities but you still have to start with a CREATE DATABASE SQL command.

This is the reason why Veeva decided to build Nitro, the data science and analytics platform. It is designed to accelerate time-to-value by getting data quickly from Veeva Commercial Cloud (CRM, Vault, Align, Network)  and other common life sciences platforms (e.g. Salesforce Marketing Cloud) into Nitro using predefined intelligent connectors. 

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Snowflake Data Encryption and Data Masking Policies

Introduction

Snowflake architecture has been built with security in mind from the very beginning. A wide range of security features are made available from data encryption to advanced key management to versatile security policies to role-based data access and many more, at no additional cost. This post will describe data encryption and data masking functionalities.

Snowflake Security Reference Architecture

Snowflake Security Reference Architecture includes various state-of-the-art security techniques that offer multiple outstanding cloud security capabilities. It includes data encryption while data at rest, secure data transfers while data in transit, role-based table access, column and row-level access to a particular table, network access/IP range filtering, multi-factor authentication, Federated Single Single On, etc.

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Snowflake External Functions

Introduction

Snowflake has recently announced external functions available in public preview. This allows developers to invoke external APIs from within their Snowflake SQL queries and blend the response into their query result, in the same way as if they were internal Snowflake functions.

In this article, we will demonstrate how to invoke an API via Amazon Web Services API Gateway that will trigger an AWS Lambda function. The Lambda function (written in Python) then  invokes a public API from to return the exchange rate for USD and multiple foreign currencies that can be used to calculate our sales values in USD and a number of selected currencies in SQL query running in our Snowflake warehouse. This solution eliminates the need for loading exchange rates into Snowflake regularly and also guarantees accurate, reliable real-time currency values.

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Snowflake and Salesforce Integration With AWS AppFlow

Amazon Web Services has recently announced a new service called AWS AppFlow, which is a fully managed serverless integration service to allow secure data transfer between various Software as Service providers such as Salesforce, ServiceNow, Snowflake, AWS Redshift, etc. The functionality supports no-code integration with mapping, validating, and merging fields on the fly.

This article covers integrating Salesforce CRM and one of the most popular cloud data warehouses, Snowflake using AppFlow.