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Plausible offers an API to access your analytics data. Start by obtaining your API key from Plausible. Navigate to your Plausible account settings, locate the API section, and generate or retrieve your API key. This key will be used for authentication in subsequent steps.
Use the Plausible API to extract the desired data. You can make HTTP GET requests to the API endpoints to fetch metrics and analytics data. Use tools like `curl` or a programming language with HTTP request capabilities (e.g., Python with `requests` library) to perform these operations. Ensure you include your API key for authentication.
Once you've fetched the data, transform it into a JSON format that is compatible with Elasticsearch. This involves structuring the data according to Elasticsearch's expected format, ensuring fields are appropriately mapped and any nested structures are correctly represented.
If you haven't already, set up an Elasticsearch instance where the data will be stored. You can either host it on a server or use a cloud-based Elasticsearch service. Configure your Elasticsearch instance by defining index patterns that match the transformed data structure.
Before sending data to Elasticsearch, ensure it is ready for indexing. This means creating a bulk request for multiple entries, if applicable, and ensuring each JSON document is correctly formatted for insertion into Elasticsearch. The data should be wrapped in an action metadata format specifying the index operation.
Use the Elasticsearch Bulk API to index the data. Send the prepared JSON data to your Elasticsearch instance using HTTP POST requests. This can be done using tools like `curl` or programmatically using libraries such as Elasticsearch's client libraries for Python (`elasticsearch-py`) or Java (`elasticsearch-java`).
After indexing, verify that the data has been successfully transferred to Elasticsearch. You can do this by querying the Elasticsearch index and checking if the documents are present and correctly formatted. Use Kibana or a similar tool to visualize and confirm that the data is accurately represented in your Elasticsearch instance.
By following these steps, you'll be able to move data from Plausible to Elasticsearch without relying on third-party connectors or integrations.
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.
Appreciable Analytics is an open-source project dedicated to making web analytics more privacy-friendly. Our goal is to reduce corporate surveillance by providing an alternative web analytics tool that doesn't come from the AdTech world. Trusted by thousands of paying customers. We are completely independent, self-funded, and bootstrapped. The legal entity is incorporated in Estonia, while our team works remotely and flexibly.
Plausible's API provides access to a variety of data related to website traffic and user behavior. The following are the categories of data that can be accessed through Plausible's API:
1. Site Metrics: This category includes data related to the overall performance of a website, such as the number of page views, unique visitors, bounce rate, and average session duration.
2. Traffic Sources: This category includes data related to the sources of traffic to a website, such as search engines, social media, direct traffic, and referral traffic.
3. User Behavior: This category includes data related to user behavior on a website, such as the pages visited, time spent on each page, and the actions taken on the website.
4. Geolocation: This category includes data related to the geographic location of website visitors, such as the country, region, and city.
5. Devices: This category includes data related to the devices used by website visitors, such as desktop, mobile, and tablet.
6. Browsers: This category includes data related to the browsers used by website visitors, such as Chrome, Firefox, Safari, and Internet Explorer.
Overall, Plausible's API provides a comprehensive set of data that can be used to analyze website traffic and user behavior, and to make data-driven decisions to improve website performance.
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.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
