TMall To Google BigQuery -Made Easy
Replicate TMall to Google BigQuery minute
Do you want an easy way to migrate data from TMall to Google BigQuery? If yes, then you can perform this process with a powerful ETL tool: Daton.
Often sellers cannot decide which channel is appropriate for selling their items or spending their advertising budget. To maximize profits and minimize losses, sellers must learn about the demand and supply trends of the market. Learning about the trends will enable sellers to grow revenue and provide customers with a smooth shopping experience. Thus, companies must tally the data from different business software. For example, mobile apps, inventory management software, CRMs, customer support platforms, and payment gateways.
Moreover, sellers should first consolidate their data to a data warehouse like Google BigQuery for calculations and gain deeper insights into the data. The data migration is hassle-free, and no coding is required. Then, replicate your TMall data to Google BigQuery to optimize your marketing campaigns and integrate it with analytics, engagement, billing, customer support and sales data to estimate your true ROI.
Why integrate TMall to Google BigQuery?
TMall is an e-commerce website for e-retailers in China. This website also operates in India, Australia and other parts of the world. To understand the importance of data integration, let’s take a simple case of a seller who sells his products in China and India. While operating in different regions, the seller’s TMall account will produce a massive amount of data. And this data will further generate many data silos. Several categories like marketing, logistic channels, inventories, and the target audience of each country will generate data silos. And thus, to track the data from source to destination, sellers will use various software. Now, in case the seller wants to calculate the total profit from his business, he will use the below-mentioned formula:
Profits/Losses = Sales – Expenses.
And finally, the seller will collect several expense data from various categories. For example, Inventory data from inventory management software like Olabi; marketing expense data from ad platforms like Facebook ads, YouTube ads. Similarly, other expenses can be collected from account software like Freshbooks, Zoho books or excel. And this data collection task has to be repeated for each country where he sells. In the same way, the seller will collect the sales data. And finally, the seller will calculate the profit/loss. Thus, this tedious task will consume a lot of time, and even can be expensive.
Moreover, due to time lag caused by data collection and analysis delays, there will be a lack of accuracy in the final results. Thus, sellers must consolidate their data into an efficient data warehouse like Google BigQuery. It will not only simplify the process but also optimize the business performance. Daton is one such powerful ETL tool that seamlessly migrates real-time data from TMall to Google BigQuery.
TMall is an e-commerce website for retailers. Alibaba manages this Chinese website, and it offers a B2C (business to consumer) e-retail store. Also, TMall enables local Chinese and international brands to sell their products to Greater China customers. Lately, TMall is helping sellers in customer acquisition and retention by developing brand awareness. In 2014, Alibaba founded a cross-border marketplace called TMall Global. This website supports all foreign brands to trade their products directly to Chinese shoppers. Alipay by Alibaba group is the leading payment gateway used by TMall. As of now, around 50000 sellers work with TMall.
Google BigQuery Overview
Google BigQuery is a cloud-based service and is the first serverless data warehouse which Fortune 500 enterprises and start-ups use. It automatically accomplishes any demands of a query. The best part about applying Google BigQuery is that you can immediately load data to the service as soon as you start using it. Therefore, a mechanism to load data in the data warehouse and the efficiency in writing SQL queries is an essential factor. Also, it optimizes the storage and datasets in the background. Thus, it makes real-time analysis faster and simple. Furthermore, Google BigQuery service offers an excellent pricing model based on the amount of data processed by incoming queries, not on the storage or the compute capacity for processing queries.
How to replicate TMall to Google BigQuery?
You can replicate TMall to Google BigQuery data warehouse in two ways.
Build a data pipeline
This process consumes a lot of time and manpower and needs a much experience. In such a process, there are more chances of making errors. You need to extract data using TMall APIs & then connect it properly with the Google BigQuery data warehouse.
Use Daton to integrate TMall & Google BigQuery
Use Daton to integrate TMall & Google BigQuery is the quickest and effortless method to save your efforts and time. Leveraging a cloud data pipeline like Daton most importantly accelerates and simplifies the time it takes to build automated reporting. Configuring data replication on Daton only takes a few minutes and a few clicks. You won’t require any code or manage any infrastructure, yet they can access their TMall data in a few hours.
Daton is easy and simple to use. The interface permits analysts and developers to use UI elements to configure data replication from TMall data into Google BigQuery.
Daton takes care of:
- Rate limits,
- Historical data load,
- Incremental data load,
- Table creation, deletion &reloads,
- Refreshing access tokens,
And many more important features to help analysts so that they can focus more on data analysis rather than worry about the data migration.
Steps to Integrate TMall with Daton
- Sign in to Daton
- Select TMall from the Integrations page
- Provide Integration Name, Replication Frequency, and History. The integration name cannot be changed later as it would be used in creating tables for the integration.
- You will be redirected to the TMall login page for authorizing Daton to extract data periodically.
- Post successful authentication, you will be prompted to choose from the list of available TMall accounts
- Select the required tables from the available list of tables
- Then select all required fields for each table
- Submit the integration
Here are more reasons to explore Daton for TMall to Google BigQuery Integration.
- Faster Integration of TMall to Google BigQuery– TMall to Google BigQuery is one of the integrations Daton can handle very fast and seamlessly. By following a few steps, you can easily connect TMall to Google BigQuery.
- No Effort & Maintenance: Daton takes care of all the data replication processes and infrastructure automatically once you sign up for a Daton account and configure the data sources. You don’t need to manage any infrastructure or write codes.
- You get an incredibly friendly customer support team who ensure that you leave the data engineering to Daton and focus on analysis and insights.
- Daton is an Enterprise-grade data pipeline which you get at an unbeatable price to help your business become data-driven. Get started today for just $10 with a single integration and scale up as your demands increase.
- Robust Scheduling Options: allows you to schedule jobs based on their requirements using a simple configuration step.
- Daton supports popular cloud data warehouses like Snowflake, Google BigQuery, Oracle Autonomous Data Warehouse, PostgreSQL and more.
- Flexible loading options allows optimizing data loading behaviour to maximize storage utilization and ease of querying.
- Enterprise-grade encryption gives your peace of mind.
- Support for 100+ data sources: In addition to TMall, Daton can extract data from various resources like Databases, Sales and Marketing applications, Analytics and Payment platforms. Daton will ensure that all useful data can be transferred to Google BigQuery for generating relevant insights.