In today’s tough market, data is a business's most important asset. It provides insights into customer behavior and business performance, which businesses can use to optimize workflows and improve advertising and marketing strategies. However, raw data is useless unless it is converted into an understandable format. This is where Power BI makes all the difference. Power BI is a group of software programs and apps that combine to turn data into coherent visualizations. Power BI provides access to raw data and enables its conversion. Power BI users can use the software to create reports and dashboards that indicate where changes are needed. This type of visualization also simplifies business owners' decision-making. What is Data Conversion or Transformation? Data conversion or transformation means taking raw data in its original structure and changing it into a format you can use for analysis. With Power BI, you can easily turn raw data into actionable reports. Power BI bridges the gap between the two ‘states’ of data. The transformation process includes cleaning the data, removing duplicate information, creating a data structure, and adding more information. Raw data imported into Power BI typically comes from other applications, such as databases, cloud apps, or Excel spreadsheets. The software also lets you connect to different data sources for direct data extraction. Once you have established the connection, Power BI will launch its Power Query Editor. This is the base from where the data transformation happens. Here, you can view your data and convert it into different formats before uploading it to the Power BI Desktop. Once uploaded, you can visualize the data.
The PQE is an online interface that allows you to transform your data using several features. These features give you a visual for each step, making the process easy to perform and track. With the PQE, you can identify and correct data errors, including inconsistencies and missing values. You can also filter out data you do not need and eliminate duplicates. If you find null values in your data, you can delete or replace them. Moreover, with PQE, you can modify the structure of your data. This means you can perform functions such as splitting columns and merging cells and tables. You can also create calculations if you need additional insights. Furthermore, the PQE allows you to format repetitive data like dates and numbers. This is crucial for accurate analysis.
There are several types of data transformations you can do with Power BI. These include text transformations, which is where splitting and merging happen. With text transformations, you can also change cases and replace values. Number transformations are one of the most common data transformations done in Power BI. During this process, you can round and truncate decimal places. You can transform your data numbers from one type of data to another. You can also calculate percentages and format numbers. Date and time transformations allow you to extract year, month, and day elements. When entering two dates, you can create hierarchies based on years or quarters and calculate ages, time differences, and time durations. When you transform date and time data, you can adjust the information to include different time zones. You can also convert text and numeric data to the time and date format. Furthermore, you can also perform condition transformations using Power BI. This means manipulating data based on certain conditions. To do this, open Power BI and launch the PQE. Choose the column needing conditional transformation and click the ‘transform’ tab. Select the ‘conditional column’ and use the dialog box to define the condition. This step requires using logical operators. You need to specify the output value when the condition is true, and you can also add additional conditions if needed. You can also use Power BI to perform data type conversions and aggregations. Aggregations are crucial for converting data into a format you can analyze. When performing data aggregations, you must identify the relevant data fields and select the required aggregation function. This function is typically based on how you want to analyze the data (average, maximum, sum, etc.). You need to use the DAX formula language to measure or create a new column in Power BI to aggregate. Apply the aggregation result to the correct calculation to get your insights.
Power BI empowers you to transform your data, no matter your preference. Whether you prefer the user-friendly interface of the Query Editor or the power of the Power Query Formula Language, Power BI provides the tools you need to get your data into usable shape. Transformations are accurate and reliable, ensuring the insights you get drive better business decisions.
