How to load data from Looker to Redis

Learn how to use Airbyte to synchronize your Looker data into Redis within minutes.

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Set up a Looker connector in Airbyte

Connect to Looker or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Redis for your extracted Looker data

Select Redis where you want to import data from your Looker source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Looker to Redis in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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TL;DR

set up Looker as a source connector (using Auth, or usually an API key)
set up Redis as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Looker

Looker is a Google-Cloud-based enterprise platform that provides information and insights to help move businesses forward. Looker reveals data in clear and understandable formats that enable companies to build data applications and create data experiences tailored specifically to their own organization. Looker’s capabilities for data applications, business intelligence, and embedded analytics make it helpful for anyone requiring data to perform their job—from data analysts and data scientists to business executives and partners.

What is Redis

Redis is an open-source, in-memory data structure store that can be used as a database, cache, and message broker. It supports a wide range of data structures such as strings, hashes, lists, sets, and sorted sets. Redis is known for its high performance, scalability, and flexibility. It can handle millions of requests per second and can be used in a variety of applications such as real-time analytics, messaging, and session management. Redis also provides advanced features such as pub/sub messaging, Lua scripting, and transactions. It is widely used by companies such as Twitter, GitHub, and StackOverflow.

Integrate Looker with Redis in minutes

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Prerequisites

A Looker account to transfer your customer data automatically from.
A Redis account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Looker and Redis, for seamless data migration.

When using Airbyte to move data from Looker to Redis, it extracts data from Looker using the source connector, converts it into a format Redis can ingest using the provided schema, and then loads it into Redis via the destination connector. This allows businesses to leverage their Looker data for advanced analytics and insights within Redis, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Looker as a source connector

1. Open Looker and navigate to the Admin panel.

2. Click on "Connections" and then "New Connection".

3. Select "Airbyte" as the type of connection.

4. Enter a name for the connection and the URL for the Airbyte instance.

5. In the "Authentication" section, select "OAuth2" as the authentication method.

6. Enter the Client ID and Client Secret provided by Airbyte.

7. In the "Advanced" section, set the "API Version" to "v1".

8. Click "Test" to ensure the connection is successful.

9. Save the connection and navigate to the "Explore" panel.

10. Select the Airbyte connection as the data source and choose the relevant tables to explore.

Note: It is important to ensure that the Airbyte instance is properly configured and the necessary connectors are installed before attempting to connect to Looker. Additionally, the specific steps for adding credentials may vary depending on the version of Looker being used.

Step 2: Set up Redis as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the Redis destination connector and click on it.
4. You will be prompted to enter your Redis connection details, including the host, port, password, and database number.
5. Once you have entered your connection details, click on the "Test" button to ensure that your connection is working properly.
6. If the test is successful, click on the "Save" button to save your Redis destination connector settings.
7. You can now use the Redis destination connector to send data from Airbyte to your Redis database.
8. To set up a data integration pipeline, navigate to the "Sources" tab and select the source connector that you want to use.
9. Follow the prompts to enter your source connector settings and configure your data integration pipeline.
10. Once your pipeline is set up, you can run it to start sending data from your source to your Redis database using the Redis destination connector.

Step 3: Set up a connection to sync your Looker data to Redis

Once you've successfully connected Looker as a data source and Redis as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Looker from the dropdown list of your configured sources.
Select your destination: Choose Redis from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Looker objects you want to import data from towards Redis. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Looker to Redis according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Redis data warehouse is always up-to-date with your Looker data.

Use Cases to transfer your Looker data to Redis

Integrating data from Looker to Redis provides several benefits. Here are a few use cases:

Advanced Analytics: Redis’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Looker data, extracting insights that wouldn't be possible within Looker alone.
Data Consolidation: If you're using multiple other sources along with Looker, syncing to Redis allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Looker has limits on historical data. Syncing data to Redis allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Redis provides robust data security features. Syncing Looker data to Redis ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Redis can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Looker data.
Data Science and Machine Learning: By having Looker data in Redis, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Looker provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Redis, providing more advanced business intelligence options. If you have a Looker table that needs to be converted to a Redis table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a Looker account as an Airbyte data source connector.
Configure Redis as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Looker to Redis after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

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How to Sync Looker to Redis Manually

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FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is Looker?

What data can you extract from Looker?

Looker's API provides access to a wide range of data categories, including:

1. User and account data: This includes information about users and their accounts, such as user IDs, email addresses, and account settings.

2. Query and report data: Looker's API allows users to retrieve data from queries and reports, including metadata about the queries and reports themselves.

3. Dashboard and visualization data: Users can access data about dashboards and visualizations, including the layout and configuration of these elements.

4. Data model and schema data: Looker's API provides access to information about the data model and schema, including tables, fields, and relationships between them.

5. Data access and permissions data: Users can retrieve information about data access and permissions, including which users have access to which data and what level of access they have.

6. Integration and extension data: Looker's API allows users to integrate and extend Looker with other tools and platforms, such as custom applications and third-party services.

Overall, Looker's API provides a comprehensive set of data categories that enable users to access and manipulate data in a variety of ways.

How do I transfer data from Looker?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:
1. Set up Looker to Redis as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Looker to Redis and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

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How to load data from Looker to Redis

Learn how to use Airbyte to synchronize your Looker data into Redis within minutes.

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Deploy Airbyte Open Source

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Looker and Redis

Get your data syncing in minutes

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TL;DR

set up Looker as a source connector (using Auth, or usually an API key)
set up Redis as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Looker