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Question

How does DirectQuery help with large datasets?

Answer 1

This mode is suited for when you have large datasets to pull data from. Instead of slowing down performance by having to load large amounts of data into Power BI, you can use DirectQuery to create a connection to the source, solving data latency issues as well.

Answer 2

In Dual mode, you can identify some data to be directly imported and other data that must be queried. Any table that is brought in to your report is a product of both Import and DirectQuery modes. Using the Dual mode allows Power BI to choose the most efficient form of data retrieval.

Answer 3

Azure Analysis Services is an Azure product that allows you to ingest data from multiple data sources, build relationships between the data, and creates calculations on the data. The calculations are built using data analysis expressions (DAX). Azure Analysis Services is similar to the data modeling and storage technology in Power BI.

Answer 4

Getting data from Azure Analysis Services cubes is similar to getting data from SQL Server, in that you can: - Authenticate to the server. - Pick the cube you want to use. - Select which tables you need.

Answer 5

You will likely import the data directly into Power BI. An acceptable alternative is to import all other data that you want (from Excel, SQL Server, and so on) into the Azure Analysis Services model and then use a live connection. Using this approach, the data modeling and DAX measures are all performed in one place, and it's a much simpler and easier way to maintain your solution.

Answer 6

While importing data into Power BI, you may encounter errors resulting from factors such as: - Power BI imports from numerous data sources. - Each data source might have dozens (and sometimes hundreds) of different error messages. - Other components can cause errors, such as hard drives, networks, software services, and operating systems. - Data can often not comply with any specific schema.

Answer 7

Relational source systems often have many people who are concurrently using the same data in the same database. Some relational systems and their administrators seek to limit a user from monopolizing all hardware resources by setting a query timeout. These timeouts can be configured for any timespan, from as little as five seconds to as much as 30 minutes or more.

Answer 8

This error indicates that you've pulled too much data according to your organization's policies. Administrators incorporate this policy to avoid slowing down a different application or suite of applications that might also be using that database.

Answer 9

You can resolve this error by pulling fewer columns or rows from a single table. While you are writing SQL statements, it might be a common practice to include groupings and aggregations. You can also join multiple tables in a single SQL statement. Additionally, you can perform complicated subqueries and nested queries in a single statement. These complexities add to the query processing requirements of the relational system and can greatly elongate the time of implementation.

Answer 10

If you need the rows, columns, and complexity, consider taking small chunks of data and then bringing them back together by using Power Query. For instance, you can combine half the columns in one query and the other half in a different query. Power Query can merge those two queries back together after you are finished.

Answer 11

Occasionally, you may encounter the "We couldn't find any data formatted as a table" error while importing data from Microsoft Excel. Fortunately, this error is self-explanatory. Power BI expects to find data formatted as a table from Excel. The error event tells you the resolution. Perform the following steps to resolve the issue: - Open your Excel workbook, and highlight the data that you want to import. - Press the Ctrl-T keyboard shortcut. The first row will likely be your column headers. - Verify that the column headers reflect how you want to name your columns. Then, try to import data from Excel again. This time, it should work.

Answer 12

Usually, this error is caused by the file moving locations or the permissions to the file changing. If the cause is the former, you need to find the file and change the source settings. - Open Power Query by selecting the Transform Data button in Power BI. - Highlight the query that is creating the error. - On the left, under Query Settings, select the gear icon next to Source.

Answer 13

You can pull data from files, relational databases, cubes, cloud-based applications, websites, and more.

Answer 14

Retrieving data from different data sources requires treating each data source differently. For instance, Microsoft Excel data should be pulled in from an Excel table. Relational databases often have query timeouts. You can connect to cubes with Connect live which allows you to see data changes in real-time.

Answer 15

It is important to select the correct storage mode for your data. Do you require that visuals interact quickly but don't mind possibly refreshing the data when the underlying data source changes? If so, select Import to import data into Power BI. If you prefer to see updates to data as soon as they happen at the cost of interactivity performance, then choose Direct Query for your data instead.

Answer 16

To start shaping your data, open Power Query Editor by selecting the Transform data option on the Home tab of Power BI Desktop.

Answer 17

When you work in Power Query Editor, all steps that you take to shape your data are recorded. Then, each time the query connects to the data source, it automatically applies your steps, so your data is always shaped the way that you specified.