This article describes how to use a data visualization tool like Google Analytics or Google Queries to collect data about the personal information that you share on LinkedIn, and then analyze it to create a data analytic system.
If you’re new to this topic, it’s best to read the previous article, “Building a Data Analytics System on LinkedIn.”
LinkedIn uses the following techniques to collect and analyze data: 1.
The company collects personal information from its users and associates with the companies that use it.
For example, you can see a graph of who is using LinkedIn on a particular day, or what your profile picture is.
For some businesses, LinkedIn will even share the data with its customers and partners to help them improve their businesses.
The data is stored in LinkedIn’s own proprietary data store, which can be accessed from a web browser.
This data is then stored in an internal database, and a variety of third-party services will analyze and visualize the data, creating reports that will be sent to a human editor.
The reports are stored in a SQLite database, which is accessed through an API.
This allows LinkedIn to access the data from its internal database for analysis.
The following sections describe how to build and run this system, and why you might want to use it for a data analysis.
Building the Data Analytics Solution First, you’ll need a few things: a data visualizer.
For this example, we’ll use an online tool called Visualizer.
It will allow you to generate charts and graphs of the data and create a report, which you can then print out and analyze.
You can also import your own data from Google Analytics, Queries, or any other third-parties and use it to build the data visualization.
3 Ways to Build a Data Visualizer On Google Analytics and Queries you can create an analysis using either the data visualizers included in Google Analytics.
The first time you use Google Analytics to analyze data, you have to first add the analytics company to the Google Analytics tracking network.
Once you’ve added them, you will have the option to create analysis reports for individual users and groups.
To create an individual analysis report, click the Add Report button.
Next, select the report you want to create, and enter the information in the fields below: Name: _____ _____ Company: _____________ Contact: _______ Name: ______ Email: _______________________ Password: _________________________ The data visualization report will then appear in a new tab.
This tab will have an Advanced tab, where you can configure the visualizer to use your data.
In the Advanced tab you can also configure a variety toggling options, including color, font size, and the size of the chart you want the visualization to create.
Finally, in the Data Visualizers tab, you specify which data visualization software you would like to use for the visualization, such as Google Analytics Pro, Microsoft Visualizer, or Queries.
If there are other visualizers you’d like to run on LinkedIn data, just click the Run Visualizer button.
Building a Data Analyzer on LinkedIn’s Own Data Store You can use Google or Microsoft Visualizers to build your own visualization, but you will need to import data from LinkedIn’s data store first.
The information that LinkedIn collects and analyzes on its own data store is called “LinkedIn Data.”
This data includes information about your LinkedIn account, your profile, your contacts, your photos, your favorite hashtags, and your likes and dislikes.
You need to export this data to a CSV format and then import it to a Google or other visualization tool.
The easiest way to import the data is to use Google’s Data Import tool.
You will need the following information: 1.
Your LinkedIn ID 2.
Your account’s user name and password 3.
Your profile picture 4.
Your avatar and profile picture (if you have one) 5.
The URL of your LinkedIn page 6.
The LinkedIn API Key 7.
A CSV file containing the CSV file you just imported.
The Data Import Tool The Data Import Wizard is the same tool that you would use to import your LinkedIn data from a Google Analytics report.
You’ll need to create your data import using a spreadsheet.
For each user or group that you want analyzed, create a new spreadsheet and then enter the following data: Name _____ First Name _________________ Email ______________________ Phone ____________________ Gender ___________________ Organization __________________ FirstName ________________ ________________ LastName _______________________________ Email ______________________________ Password __________________________ When you are finished, save the spreadsheet, and close the wizard.
Now, you need to add the LinkedIn Data to your Excel file.
You should start by importing your LinkedIn Data into an Excel spreadsheet.
Once your spreadsheet is open, click File > Import.
In Excel, select File > Save as… and then select the file you created earlier.