Saving Data to Google Sheets From BigQuery

It’s been a while since I’ve started working on datasets with BigQuery. Most of the time, I need to generate reports for several teams that work with/love spreadsheets. There are multiple ways to extract and present data (Connecting to Data Studio, Google Sheets via OWOX, etc.), but today I’m just going to show you one way.

Extracting and Saving to Google Sheets

Have your query prepared, and for those of you starting out, here’s the general syntax.

SELECT * FROM `GCP_Project_Name.Dataset.Table`
WHERE [CONDITIONS]

There are 2 options you can choose from when extracting:

Option 1

If your query is fairly simple and completes relatively quickly, I’d suggest to run the query from Google sheets directly using the native data connector (You may need to have a GSuite subscription for this feature).

Click on “Connect to BigQuery”, select the project, paste the query, then click “Insert results”.

#bigquery #google-sheets #data #macro #data-science

What is GEEK

Buddha Community

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Saving Data to Google Sheets From BigQuery

It’s been a while since I’ve started working on datasets with BigQuery. Most of the time, I need to generate reports for several teams that work with/love spreadsheets. There are multiple ways to extract and present data (Connecting to Data Studio, Google Sheets via OWOX, etc.), but today I’m just going to show you one way.

Extracting and Saving to Google Sheets

Have your query prepared, and for those of you starting out, here’s the general syntax.

SELECT * FROM `GCP_Project_Name.Dataset.Table`
WHERE [CONDITIONS]

There are 2 options you can choose from when extracting:

Option 1

If your query is fairly simple and completes relatively quickly, I’d suggest to run the query from Google sheets directly using the native data connector (You may need to have a GSuite subscription for this feature).

Click on “Connect to BigQuery”, select the project, paste the query, then click “Insert results”.

#bigquery #google-sheets #data #macro #data-science

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).

---

This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

How To Blend Data in Google Data Studio For Better Data Analysis

Using data to inform decisions is essential to product management, or anything really. And thankfully, we aren’t short of it. Any online application generates an abundance of data and it’s up to us to collect it and then make sense of it.

Google Data Studio helps us understand the meaning behind data, enabling us to build beautiful visualizations and dashboards that transform data into stories. If it wasn’t already, data literacy is as much a fundamental skill as learning to read or write. Or it certainly will be.

Nothing is more powerful than data democracy, where anyone in your organization can regularly make decisions informed with data. As part of enabling this, we need to be able to visualize data in a way that brings it to life and makes it more accessible. I’ve recently been learning how to do this and wanted to share some of the cool ways you can do this in Google Data Studio.

#google-data-studio #blending-data #dashboard #data-visualization #creating-visualizations #how-to-visualize-data #data-analysis #data-visualisation

How to send data from Google BigQuery to Google Sheets and Excel

Google BigQuery (GBQ) doesn’t require additional maintenance costs and processes your data in less than a minute. You can learn about uploading data to GBQ from CSV and JSON files, using the BigQuery API, or from other Google services in this article. Today, we’ll tell you how to upload data from BigQuery to your all-time favorites — Google Sheets and Excel.

How to import data from Google BigQuery to Google Sheets

The easy way to load data into Google Sheets is using the BigQuery Reports add-on from OWOX BI. You can install it for free directly from the Add-ons menu in Google Sheets, or you can download it from the Chrome Web Store.

Image courtesy of the author

2. Once you’ve installed the OWOX BI BigQuery Reports add-on, you’re ready to load data from storage. To do so, go to the Add-ons menu in Google Sheets, hover your mouse over OWOX BI BigQuery Reports, and select Add a new report.

Image courtesy of the author

2. In the add-on menu that appears on the right side of the screen, specify the name of your GBQ project. You can then either create a new SQL query for the selected project or select a previously used query from the drop-down list.

Image courtesy of the author

1. If necessary, define dynamic parameters for your query. Then click Add & Run.
2. Your data is ready! Data from GBQ will be uploaded to a new sheet in Google Sheets.

Advantages of the OWOX BI BigQuery Reports add-on:

• You can load data from BigQuery to Google Sheets and vice versa.
• You control access to your data.
• You can share data with colleagues in one click from Google Sheets.
• You get access to a simple query editor.
• Reports are automatically updated.

You can learn more about setting up the OWOX BI BigQuery Reports connector and automating reports in Google Sheets based on information from Google BigQuery on the OWOX blog.

How to import data from Google BigQuery to Excel

1. To import data from Google BigQuery to Excel, first of all, you need a unique key to run queries against BigQuery. You can create this key any time you like, but remember that it has an expiration date.

Image courtesy of the author

If necessary, you can always create a new key.

Image courtesy of the author

You can also expire your current key using the Revoke Key button or in your Google profile settings.

Image courtesy of the author

#google-sheets #analytics #data #google-big-query #excel #data analysis