This article will unveil a 3-step process to set up Google Drive to Databricks Integration. We will build an ETL pipeline to replicate Google Drive data on Databricks.
By employing Hevo ETL pipelines, you will save hours. The need for an extensive data preparation process will not exist, allowing you to concentrate on core business activities to reach new heights of profitability.
Read along to learn more exciting aspects of Google Drive to Databricks Integration.
Why Connect Google Drive to Databricks?
As organizations expand, it is challenging to consolidate data into a single source of truth for better reporting and analysis.
By replicating your Google Drive data to Databricks, you can take advantage of customized dashboards which provide you and your team with actionable insights in a visualized format.
Google Drive to Databricks Integration enables an organization-wide data unification with a consistent format. You can leverage Hevo, a No-Code Data Pipeline, to make the data replication process a cakewalk.
Let’s take a quick look at what Google Drive to Databricks Integration has to offer:
- Complete Analysis With a 360-degree View: It allows you to access advanced reports for additional insights from your Google Drive data. In a magnificent dashboard, you can see who your customers are, what they buy, and where they come from. You can also obtain insights about various products, distribution methods, client lifetime values, and more.
- Combine & Assemble to Get Customized Information: Keep track of your organization-wide data by extracting relevant data from Google Drive and combining it with data from other sources. All your data and insights are gathered in one location, enabling you to get faster analytics.
- Separate Computing and Storage: Using Google Drive enables storage scalability for unprocessed and processed data that flows from disparate sources. Utilizing Databricks’ scalable computing, you can scale vertically and horizontally over that data, enabling several concurrent users to access and modify the data as necessary.
- Support for Transactions: Data lakes frequently struggle to handle several users and groups reading and publishing data simultaneously. When reading and writing this data concurrently, support for Atomicity, Consistency, Isolation, and Durability (ACID) transactions is necessary to ensure that there are no conflicts among various participants. This ACID support is natively provided by Databricks when using the open-source format Delta Lake.
- Say No to CSV Files and Python Scripts: Focus on creating a data stack and improving data quality rather than writing custom code to integrate Sales and Marketing technology. Thanks to Hevo, an automated data pipeline solution. Your business team will obtain the data in an analytics-ready format, and no engineering favors are necessary.
How to connect Google Drive to Databricks Using Hevo?
Step 1: Configure Google Drive as a Source
Note: You can also perform data transformations using either Python-based or drag-and-drop transformations, which does not require you to be a tech freak.
Step 2: Configure Databricks as a Destination
Step 3: Finish setting up your ETL pipeline.
Data Replication Frequency
|Default Pipeline Frequency||Minimum Pipeline Frequency||Maximum Pipeline Frequency||Custom Frequency Range (Hrs)|
|5 Mins||5 Mins||24 Hrs||1-24|
Now that you’ve configured your Google Drive as your data source & Databricks as your data destination, you have successfully created your data pipeline, which is ready to rock. You can also schedule your pipeline to run at different frequencies; click here to learn more.
Why Use Hevo?
Hevo and Databricks open an unconventional world of possibilities and offer better Price/Performance by 12x compared to conventional cloud data solutions.
And, if yours is anything like the 1000+ data-driven companies that use Hevo, more than 70% of the business apps you use are SaaS applications Integrating the data from these sources in a timely way is crucial to fuel analytics and the decisions that are taken from it. But given how fast API endpoints etc, can change, creating and managing these pipelines can be a soul-sucking exercise.
Hevo’s no-code data pipeline platform lets you connect over 150+ Data Sources like Google Drive in a matter of minutes to deliver data in near real-time to your warehouse like Databricks.
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Here’s how Hevo challenges the normal to offer something new and exceptional:
- Faster Insight Generation: Hevo offers reliable and swift Rapid Analysis. Hevo allows you to select your most valuable data and pull it from the connected data source with just one click, all without the assistance of developers. Yes, you can do it without any extensive technical training!
- Data Transformation: Not every data source can be used directly for analysis. With Hevo, Models & Workflows as a part of Post-Load Transformations enable you to query data in real-time and process your data in an analytics-ready form.
- Fully Managed: With simple no-code UI dashboards for pipeline monitoring, auto-schema management, and personalized ingestion/loading schedules, Hevo gives data teams total control. Remove the need to create complex scripts or coding to extract, transform, and import your data into Databricks from Google Drive. Automate your end-to-end data flows using Hevo.
- Collaborative Development: Databricks’ Unified Analytics Platform (UAP) combines data science, engineering, and business to speed up innovation, requiring data unification from disparate sources. Using Hevo, the Databricks Destination can be set up instantly.
- Transparent Pricing: Say goodbye to all the complicated and secretive pricing schemes. Your ELT spending is entirely evident & thanks to Hevo’s pricing. You have the option to select a plan based on the requirements of your company. Maintain control with adjustable credit limits and spend notifications for unanticipated data flow increases.
Try Hevo today for free and save your engineering resources.
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This post has touched the surface of the many critical aspects of setting up Google Drive to Databricks Integration.
There is rapid growth and prominence of Databricks as a significant player when it comes to managing massive datasets. By removing the silos that might complicate the data, Databrick’s solution enables organizations to utilize their data fully.
Many organizations are still debating whether to Build vs. Buy ETL pipelines. Numerous factors such as team size, clientele served, and company size influences an organization’s decision.
Quick Tip: Focus on performance improvement, self-service search, and discovery as you move away from traditional Data federation technologies to Data warehouses. Invest more to analyze data thoroughly than spending time searching for it.
Experience fully automated, hassle-free data replication for Google Drive by immediately starting your journey with Hevo and Databricks.
Share your experience understanding the Google Drive to Databricks Integration in the comments below! We would love to hear your thoughts.
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