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Begin by exporting the data you need from your LinkedIn pages. LinkedIn provides an option to download data directly. Go to the LinkedIn settings, navigate to the "Data Privacy" section, and select "Get a copy of your data." Choose the specific data you need, such as page analytics or follower data, and request the archive. LinkedIn will notify you once the data is ready for download. Download the CSV or Excel files provided.
Once you've downloaded your LinkedIn data, open the files in a spreadsheet application like Microsoft Excel or Google Sheets. Review the data to ensure it is complete and accurate. Clean the data by removing any unnecessary columns or rows and correcting any inconsistencies. Save the cleaned data in a CSV format, which is widely compatible with various data platforms.
Access your Starburst Galaxy account and ensure you have the necessary permissions to create and manage tables. If you do not have an account, sign up and configure your environment according to your organizational needs. Familiarize yourself with the Starburst Galaxy interface and its capabilities for importing data.
In Starburst Galaxy, navigate to the SQL Editor or use the command line interface to create a new table that will host your LinkedIn data. Use SQL commands to define the table schema based on the structure of your CSV file. For example:
```sql
CREATE TABLE linkedin_data (
column1_name datatype,
column2_name datatype,
...
);
```
Ensure the data types for each column match those in your CSV file to avoid import errors.
Use Starburst Galaxy's built-in data import capabilities to load your CSV file into the new table. This can be done by executing a SQL COPY command in the SQL Editor. For example:
```sql
COPY linkedin_data FROM 's3://your-bucket/linkedin_data.csv' WITH (FORMAT CSV);
```
This command assumes that your CSV file is accessible via a cloud storage service such as Amazon S3. Ensure the file path and access permissions are correct.
After you have loaded the data, run a series of SQL queries to verify that the data in Starburst Galaxy matches the original data from your CSV file. Check for correct data values, consistent formats, and complete data records. Use SQL commands like `SELECT` and `COUNT` to perform these checks.
To keep your data current, establish a routine for exporting updated data from LinkedIn and importing it into Starburst Galaxy. Set reminders or automate the process using scripts to periodically download new data, clean it, and load it into your table. This ensures your data analysis remains relevant and up-to-date.
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.
LinkedIn Pages are a great platform for organizations to post industry updates, job opportunities, information about life at their organization, and much more. LinkedIn Pages can be used by admins and followers when signed in to LinkedIn.com on desktop and mobile devices. A LinkedIn Page permits you to represent your organization on LinkedIn. LinkedIn Pages offer a platform for companies, universities, and high schools to share information about their brand with visitors and followers. A LinkedIn Page assists.
LinkedIn Pages API provides access to a wide range of data related to LinkedIn Pages. The API allows developers to retrieve and manage data related to company pages, including company information, updates, and followers. Here are the categories of data that LinkedIn Pages API provides access to:
1. Company information: This includes basic information about the company, such as name, logo, description, and website URL.
2. Updates: This includes all the updates posted on the company page, including text, images, and videos.
3. Followers: This includes information about the followers of the company page, such as their names, job titles, and locations.
4. Analytics: This includes data related to the performance of the company page, such as engagement metrics, follower growth, and demographics.
5. Employee information: This includes information about the employees of the company, such as their names, job titles, and LinkedIn profiles.
6. Content recommendations: This includes recommendations for content that is likely to perform well on the company page based on LinkedIn's algorithm.
Overall, LinkedIn Pages API provides developers with a comprehensive set of data that can be used to build powerful applications and tools for managing LinkedIn Pages.
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:





