The easiest way to transfer data from/into Google BigQuery
Vlada Malysheva, Creative Writer @ OWOX
If you are still working as Cinderella to collect data for reports at the end of each month, you are in urgent need of a kind fairy godmother! Use a magic wand from OWOX - an enchanting free add-on that transfers your data from Excel or Google Sheets into Google BigQuery and back in a couple of clicks.
Automate data transfer, build complex and useful reports such as cohort analysis or ROPO, and focus on getting fresh ideas to grow your business. And you may not worry; this data transfer carriage won't turn into a pumpkin!
Why you need to transfer data
Who's the fairest of them all? If you ask a marketer this question, then in 90% of cases, you will hear Google Analytics and Excel (or Google Spreadsheets). Of course, on the market, there's always something new, automated, and with the use of machine learning. However, these pillars of the Earth are still there.
There are enough functions for many marketers who work in small companies. These platforms are tested, work without breakdowns, and everyone knows how to use them - the ideal choice for small and medium-sized businesses, especially when one or more people are using this information for work.
However, what to do when you no longer have one landing page but an online store gradually growing? Obviously, the amount of data that needs to be analyzed is also growing. You not only need to analyze the increasing number of advertising campaigns and user behavior but also combine all this data. Besides, you have to keep in mind that your customers use both laptops and mobile gadgets to visit your website. It's a common practice when a user found something on the website from a laptop, left the page, then on a mobile device, he saw advertising on social networks and went back to the store to finish his order. To analyze this amount of data, it needs to be stored somewhere, and the best option is cloud-based data warehouses.
You probably have access to gigabytes of user data every day, but this amount doesn’t bring value until you make it work for you. In this article, we look at what raw data is, why it’s needed, and how to get it and use it.
Why Google BigQuery
Among the many solutions available in the cloud data storage market, the option from Google, BigQuery, is most suitable for marketers. Why is this service considered the most convenient?
First of all, marketers worldwide use Google products in their work: Google Ads, Google Analytics, YouTube, and other Google services. And, of course, BigQuery storage is a part of this infrastructure and has native integration with all other Google services.
Secondly, the service is easy to use and fast to work with. Also, a large number of specialists know how to work with this platform and there are pre-made sets of SQL queries to use.
With GBQ, you can easily solve such pressing problems of marketers as real-time bid management and segment automation. As we know, marketing performance's success depends on a quick reaction to market changes, personalization, and automation of marketing.
Should you choose a standard data warehouse or a data lake? In this article, we discuss why Google BigQuery as a data lake is the best choice.
The easiest way to transfer data into Google BigQuery
If you want to create advanced analytics, for example, to build ROPO reports using offline and online data, you need to find an easy and convenient way of uploading data. Certainly, everything can be done in the old manner, collecting data manually and wasting a big half of the working hours. But why suffer if it's possible not to?
More than 100,000 users worldwide use a free add-on from OWOX BI — BigQuery Reports. Using the OWOX BI add-on, you get your data processed in Google BigQuery, and the results of the query automatically imported into Google Sheets.
For example, you collect data from a mobile app and website into GBQ, then you add data from all marketing channels, email and CRM systems. Afterwards, in the Sheets, you can see a report on individual user activities or build a cohort analysis or LTV calculation.
Another use case is linked files that multiple departments require. For example, the marketing department fills the plans in the budgeting document, and the finance department fills in the facts. This data is then uploaded into GBQ, processed, and downloaded back to the required files. Thus the finance department receives plans, and the marketing department receives facts.
The free add-on allows you to set up data transfer between Google BigQuery and Excel (Spreadsheets) in two clicks and the opposite direction. Also, among the advantages of using add-on are:
- Auto-update reports. You can specify the frequency of updates you want.
- Create your own query collection. Analysts or developers can save queries with the predetermined parameters you need.
- Free add-on. You pay exclusively for processing data in the BigQuery storage.
- Safety. Add-on uses only official APIs from Google.
- Data control. You control who has access to your data.
If you go through the user reviews, you get these: it’s handy, it’s flawless, it’s a lifesaver. These words speak for themselves, don't they?
Regardless of where you want to upload data, you need to take three simple steps.
How to use an add-on for data transfer
Step 1. Install the add-on. You can also download it directly from the Google Sheets menu.
Depending on what you want to do, select Add a new report or Upload data to BigQuery from the drop-down menu.
Step 2. If you want to download data from BigQuery storage, specify the name of the project. If necessary, define dynamic parameters for your query. Click Add & Run.
If you want to upload data into the data storage from Google Sheets, you should specify the project in the BigQuery and the data loading scheme. Click Start Upload.
Step 3. You’re amazing and your data has been successfully transferred!
Want to be sure about the quality of your data? In this article, we tell you how to check the quality of data at all stages of collection, from the statement of work to completed reports.
Your data should work for you! To use all the collected data about your customers and get important insights from it, use the simple and easy way - the OWOX BI BigQuery Reports connector.
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How can I transfer data from Google BigQuery to another platform or storage solution?- You can transfer data from Google BigQuery using various methods such as exporting data to a Cloud Storage bucket, using the BigQuery Data Transfer Service, or using third-party tools. - To export data to a Cloud Storage bucket, you can use the `bq extract` command or the BigQuery Export feature within the BigQuery web UI. - The BigQuery Data Transfer Service allows you to schedule automatic exports of BigQuery data to other Google Cloud services like Cloud Storage, BigQuery Data Warehouse, and Google Sheets. - There are also third-party tools available that provide more advanced options for data transfer from BigQuery to external platforms.
What are the benefits of using Cloud Storage for transferring data from Google BigQuery?- Using Cloud Storage for transferring data from BigQuery offers several benefits. - Cloud Storage provides a scalable and reliable storage solution for your data, ensuring data durability and availability. - It allows you to easily share data between different Google Cloud services and external platforms. - Cloud Storage supports parallel data transfer, which can significantly improve data transfer speeds. - Additionally, Cloud Storage provides features like data lifecycle management, access controls, and versioning, ensuring the security and integrity of your transferred data.
Can I automate the data transfer process from Google BigQuery to another platform?- Yes, you can automate the data transfer process from BigQuery to another platform using various methods. - One option is to use the BigQuery Data Transfer Service, which allows you to schedule regular exports from BigQuery to other Google Cloud services. - You can set up transfer configurations with specific schedules, filter conditions, and destination parameters, enabling automated data transfers. - Another approach is to create custom scripts or workflows using tools like Cloud Functions, Dataflow, or Cloud Composer. - These tools enable you to build automated data pipelines and execute data transfer processes based on triggers, events, or schedules.