ETL depuis Shopify vers Snowflake en quelques clics

Rivery offers a set of Predefined Reports for Shopify for rapid data integration. Using these reports, you can quickly analyze the data without having to learn the intricacies of the way the data is organized within the Shopify API. Simply provide your Shopify credentials and choose the report to load into your cloud data warehouse.
The Shopify data source in Rivery comes with the below predefined reports (click to navigate to the full data structure documentation):

• Addresses
• Shop
• Products
• Orders
• Customers
• Order Transaction
• Marketing Event
• Inventory Level
• Analytic Report

Extracting data from Shopify is crucial for businesses aiming to gain comprehensive insights into their e-commerce operations and optimize performance. By analyzing sales data, companies can track revenue trends, identify top-performing products, and make informed decisions about pricing strategies. Customer data extraction enables businesses to understand purchasing behavior, segment customers, and tailor marketing campaigns for improved retention and higher conversion rates. Additionally, monitoring inventory levels and forecasting demand helps in maintaining optimal stock levels, preventing stockouts, and reducing excess inventory.

Moreover, Shopify data can be leveraged to enhance order fulfillment and shipping processes, ensuring timely deliveries and reducing costs. Analyzing returns and refunds provides insights into product quality and customer satisfaction, allowing businesses to address issues proactively. Understanding the effectiveness of marketing campaigns, including conversion rates and customer acquisition costs, helps in optimizing marketing spend and strategies.

Lucy & Yak, extracts data from Shopify with Rivery, and centralizing it with Snowflake, allowing their data team to build a Weekly Sales Stock & Intake (WSSI) tool in Tableau for the rest of the team to utilize.

Shopify releases a new API version every 3 months at the beginning of the quarter.
Version names are date-based to be meaningful and semantically unambiguous.

Each stable version is supported for a minimum of 12 months. This means that there are at least 9 months of overlap between two consecutive stable versions. When a new stable version is introduced and contains changes that affect your app, you have 9 months to test and migrate your app to the new version before support for the previous version is removed.

Rivery manages the Shopify Data Integration for you, so you don’t need to worry about API upgrades breaking your data pipelines. Rivery will continually maintain the integration with the latest API versions. Most upgrades would be seamless requiring no action on your end. If any API version change require your attention — like added, removed, or modified reports/data fields that you may be using — Rivery will notify you ahead of time with the details and any possible actions required.

Utiliser les connecteurs de données de Rivery est très simple. Il suffit d’entrer vos identifiants, de définir la cible où vous souhaitez charger les données (par exemple, Snowflake, BigQuery, Databricks ou tout data lake) et de mapper automatiquement le schéma pour le générer sur la cible. Vous pouvez contrôler les données que vous avez besoin d’extraire de la source et la fréquence de synchronisation de vos données. Pour en savoir plus, suivez la documentation spécifique.

Oui. Tous les connecteurs de données au sein de Rivery sont conformes aux normes de sécurité et de confidentialité les plus élevées, y compris : RGPD, HIPAA, SOC2 et ISO 27001. De plus, lorsque les données sont transférées vers votre entrepôt de données cible, vous pouvez configurer le transfert via votre propre système de fichiers cloud plutôt que via Rivery.

Les connecteurs de données les plus populaires concernent des cas d’usage comme le marketing, les ventes et la finance. Ils incluent Salesforce, HubSpot, Google Analytics, Google Ads, LinkedIn Ads, Facebook Ads, TikTok et plus encore.

Rivery prend en charge la réplication de base de données CDC et l’extraction SQL standard, vous pouvez donc choisir la méthode qui vous convient le mieux. En savoir plus ici.