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Power BI visualization interview questions and answers

1-What is Power BI and how does it help in data visualization?
Power BI is a business analytics tool by Microsoft that enables users to visualize and analyze data from various sources. It allows users to create interactive dashboards, reports, and visualizations.
Power BI helps in data visualization by providing a wide range of chart types, customizable visuals, and interactive features that enable users to explore and present data effectively.

2-What are the different types of visualizations available in Power BI?
Power BI offers various types of visualizations, including bar charts, line charts, pie charts, scatter plots, maps, tables, matrices, cards, gauges, and more.
Each visualization type serves a specific purpose, allowing users to represent data in a way that best suits their needs and insights they want to convey.

3-How can you create a custom visualization in Power BI?
Power BI allows the creation of custom visualizations using the Power BI Visuals SDK (Software Development Kit). Developers can use various web technologies like HTML, CSS, and JavaScript to build custom visuals that can be imported into Power BI. These custom visuals provide additional flexibility and functionality beyond the default set of visualizations.

4-How can you create drill-through actions in Power BI?
To create drill-through actions in Power BI, you need to define drill-through pages and configure the drill-through settings. First, you create a new report page that contains the details you want to drill into. Then, you configure the drill-through settings by specifying the target fields and values that trigger the drill-through action. Users can then right-click or use the ellipsis (…) on a visual to drill through to the detailed page.

5-What is the role of bookmarks in Power BI visualizations?
Bookmarks in Power BI allow users to capture and save the current state of a report page, including visuals, filters, and other settings. Bookmarks can be used to create interactive presentations or storytelling experiences by navigating between different bookmarked views. They help users create a guided exploration of the data and provide a consistent user experience.

6-How can you create a slicer in Power BI?
To create a slicer in Power BI, you need to select the slicer visualization from the visualizations pane. Then, you choose the field you want to use as a slicer, and Power BI automatically creates the slicer based on the distinct values in that field. Users can interact with the slicer to filter data across multiple visuals in the report.

7-What is the role of filters in Power BI visualizations?
Filters in Power BI allow users to narrow down the data displayed in visuals based on specific criteria. Filters can be applied to individual visuals or across the entire report. Users can use filters to focus on specific categories, time periods, or data subsets, providing more precise and targeted insights.

8-What is the role of conditional formatting in Power BI visualizations?
Conditional formatting allows users to format the appearance of visuals based on specific rules or conditions. It helps highlight data points that meet certain criteria, making it easier to identify patterns, outliers, or important insights. With conditional formatting, you can change colors, font sizes, data bars, or icons within visuals based on the values or ranges you define.

9-What is the role of cross-filtering in Power BI visualizations?
Cross-filtering in Power BI allows users to filter one visual based on selections made in another visual. When users interact with one visual, such as selecting a data point or category, the other visuals on the report page adjust accordingly to display the relevant data. Cross-filtering helps users explore data relationships, analyze data from different perspectives, and gain insights across multiple visuals simultaneously.

10-How can you enhance the performance of Power BI visualizations?
To optimize the performance of Power BI visualizations, consider the following practices:

  • Minimize the use of calculated columns and instead utilize measures for calculations.
  • Reduce the number of visuals and data points in a report.
  • Optimize data model design by properly configuring relationships and using appropriate data types.
  • Apply filters to limit the data displayed and improve query performance.
  • Leverage data summarization techniques, such as aggregations and data reduction strategies, to enhance query speed.

11-How can you share Power BI visualizations with others?
Power BI offers various options to share visualizations with others. You can publish your report to the Power BI service and share it with specific individuals or groups. Alternatively, you can export your report as a PDF or PowerPoint presentation to distribute. Power BI also provides embedding capabilities, allowing you to integrate visualizations into websites or applications for broader access.

12-How can you implement advanced analytics techniques in Power BI visualizations?
Power BI provides advanced analytics capabilities through the integration with Azure Machine Learning and R scripts. You can use these features to incorporate predictive analytics, clustering, forecasting, and other advanced techniques into your visualizations. By leveraging these tools, you can gain deeper insights and make data-driven decisions based on sophisticated analyses.

13- Types of Power BI visuals?

  • Bar Chart: A chart that uses rectangular bars to represent data values. Each bar’s length corresponds to the data value it represents.
  • Column Chart: Similar to a bar chart, it uses vertical columns to represent data values.
  • Line Chart: A chart that displays data points connected by lines, primarily used to show trends or patterns over time.
  • Area Chart: Similar to a line chart, it displays data points connected by lines and filled with color to show the magnitude of values over time.
  • Line and Stacked Column Chart: A visualization that combines a line chart and stacked column chart in a single visual. It displays data as vertical columns stacked on top of each other, representing different categories or groups, while also showing a line chart that represents a trend or continuous variable over time or another dimension
  • Line and Clustered Column Chart: This visual allows for comparison between multiple categories or groups using clustered columns, while also showcasing a trend or continuous variable using the line chart.
  • Pie Chart: A circular chart divided into slices, each representing a proportion of a whole or a category.
  • Donut Chart: Similar to a pie chart, but with a hole in the center, providing more space for additional information.
  • Scatter Chart: A chart that displays individual data points as dots or markers to represent the relationship between two variables.
  • Tree Map: A chart that uses nested rectangles to represent hierarchical data, where the size of each rectangle corresponds to a specific value.
  • Matrix: A table-like visualization that displays data in rows and columns, often used for cross-tabulations and comparisons.
  • Table: A tabular representation of data with rows and columns, displaying values in a structured format.
  • Card: A visual element that displays a single value or metric, often used to highlight a key performance indicator (KPI).
  • Gauge: A visual element that represents a value within a specified range using a dial or needle, providing a way to measure progress or status.
  • KPI (Key Performance Indicator): A visual element that displays a specific metric or performance measure, typically using icons or symbols to indicate performance levels.
  • Funnel Chart: A chart that represents stages of a process or conversion, where the width of each segment represents the relative magnitude or quantity.
  • Waterfall Chart: A chart that illustrates the cumulative effect of positive and negative values on a total, showing how values contribute to the final result.
  • Map: A visual representation of geographic data, displaying locations and values on a map using markers, bubbles, or choropleth shading.
  • Shape Map: A map visualization that uses custom shapes or regions to represent data values, enabling more specific and unique mapping representations.
  • Ribbon Chart: A specialized chart that shows multiple data series as ribbons flowing along a horizontal axis, providing a visual comparison of values across categories.
  • Slicer: A visual control used to filter data in other visuals by selecting specific values or ranges, allowing users to interactively slice and dice the data.

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