Step by step guide on managing data connections and queries in Power BI Desktop

2. Managing Queries with Power Query Editor
After establishing the connection to a data source, maintaining queries manages the dataset such that it is structured, optimized and clean.
1. Click on Transform Data after still loading the data source.
2. This should launch the Power Query Editor, in which you can shape and refine the data to fit as you wish before bringing it into Power BI.

Necessary Transformations of Data
• Removing columns: Relevance should remain on columns retained so that it isn't repetitive in load and increases efficiency.
• Filtering rows: Deprive any unneeded entries based on some condition (e.g., null is removed, filtered by date range).
• Changing types: Make sure it's correctly assigned so it's never erroneously calculated.
• Merging Queries: Bring data from a few tables together using common fields (for instance merging sales and customer in one go on Customer ID).
• Appends Queries: Stacking of like datasets together (makes sense to gather up in monthly reports).
• Creating Calculated Column: Doing new columns with your calculations in the Power Query formula bar.

3.Data Refresh and Scheduled Updates Management

Manual Refresh
To refresh the data manually:
1. Open up the Home Tab and choose Refresh in Power BI Desktop.
2. Power BI gets updated data at the source.

Scheduled Refresh in the Power BI Service
Going to publish reports in the internet world will mean setting up an automatic refresh:
1. Publish Power BI report into Power BI Service.
2. Now go to Dataset Settings.
3. Schedule Refresh. Fill in authentication details.
4. The refresh interval will now be set daily, hourly or based on updates.
Tip: Be sure to note whether the data sources allow scheduling. Some sources (local Excel files, for example) may need an on-premise gateway.

4. Performance Optimization on Big Data

Loading Less Data
•Select the Import mode only for data that you really need.
•Filter rows that are of no use before they are loaded into Power BI.
•If handling large volumes of data, try to aggregate data at the source itself.

Apply Query Folding
Instead of processing data in Power BI, query folding pushes those transformations to the data source. This helps in optimizing performance.
•Works best when using SQL Server or Oracle databases and other relational databases.
•Avoid breaking the query folding by applying high-level transformations at an early stage in Power Query.

Establish Relationships
•Correctly define one-to-many (1:M) relationships.
•Promote simplicity of the queries and performance enhancement by means of star schema design.
•Restrictive relationships or complex joins that will drag processing should be avoided.

5. Handling Query and Connection Errors
Frequent Errors and Resolutions
1) Ensure you have the right authentication details to access secured data sources in case of credential issues.
2) Check for null values, formatting errors, or truncated data in missing or corrupt data.
3) Data type mismatches: double-check that numeric columns are not stored as text and that date formats meet expectations.
4) Query timeout issues: Optimization of queries, sizing down the amount of data, and verification of network connectivity might be an answer if queries are taking an extended period.

Troubleshooting Guide:
•Query dependency check: Go to Power Query Editor > View > Query Dependencies.
•By selecting each transformation in the Power Query Editor, validate them.
•Before loading the data, use F5 (Refresh Preview) in the Power Query Editor to check if errors still occur.

6.Query Management and Data Connections Best Practices
•Organize Data Connections: Query names should be meaningful and not duplicative for any reason.
•Document Types of Changes Made: A better tested way to troubleshoot any query is to add descriptions.
•Performance: Measure and record loading time for the report and execution time for the query.
•Parameters: They dynamically modify the query (for filtering and transformations) based on user-defined parameters.
•Data Source Credentials: Preventing broken refreshes by allowing the setting of valid credentials in the Power BI Service.

Conclusion
Proper data connection and query management within Power BI Desktop are vital to the making of credible, efficient, and scalable reports. Therefore, using Power Query Editor, performance optimized and proactive error handling gives birth to a clean, structured dataset ready for analysis.
The better you get at these techniques, the easier it will be to use Power BI and the most useful and widely applied reports you shall produce. Keep practicing, fine tuning and optimizing to realize the maximum potential of Power BI!