{"id":8439,"date":"2025-03-11T09:15:17","date_gmt":"2025-03-11T08:15:17","guid":{"rendered":"https:\/\/powerbi.pl\/blog\/news\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover"},"modified":"2025-03-11T09:15:17","modified_gmt":"2025-03-11T08:15:17","slug":"hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover","status":"publish","type":"post","link":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover","title":{"rendered":"HR data analysis in Power BI: monitoring employment and employee turnover"},"content":{"rendered":"<h2>Why is HR data analysis crucial for organisations?<\/h2>\n<p>Modern organisations operate in a dynamic environment where human resource management is based on facts rather than intuition. Analysis of HR data allows for: <\/p>\n<ul>\n<li>Identification of trends in employment and turnover,<\/li>\n<li>Forecasting future staffing needs,<\/li>\n<li>Reduction of costs related to excessive staff turnover,<\/li>\n<li>Increase employee commitment and satisfaction,<\/li>\n<li>Developing effective recruitment strategies.<\/li>\n<\/ul>\n<p>Microsoft Power BI provides interactive reports and dashboards that provide insight into key HR indicators, enabling better human capital management.<\/p>\n<h2>Which HR indicators are worth monitoring in Microsoft Power BI?<\/h2>\n<p>Power BI allows you to visualise and analyse key HR indicators such as:<\/p>\n<ul>\n<li><strong>Turnover rate <\/strong>\u2013 number of employees leaving in a given period,<\/li>\n<li><strong>Average length of service<\/strong> \u2013 helps to assess the stability of the team,<\/li>\n<li><strong>Number of new hires <\/strong>\u2013 allows you to evaluate the effectiveness of your recruitment,<\/li>\n<li><strong>Recruitment costs per position<\/strong> \u2013 indicates the efficiency of the recruitment process.<\/li>\n<li><strong>Employee absence<\/strong> \u2013 allows you to detect problems related to commitment.<\/li>\n<\/ul>\n<p>Power BI allows you to create interactive reports where users can analyse data by department, location, or job level.<\/p>\n<h2>Create HR reports in Power BI step by step<\/h2>\n<p>Creating HR reports in Power BI is a process that requires several key steps \u2013 from data collection, through cleaning and modelling, to creating interactive dashboards. Each of these steps affects the quality and effectiveness of the analysis, enabling HR teams to make informed decisions. Let&#8217;s see how it works in practice.  <\/p>\n<h3>Data collection and integration<\/h3>\n<p>The first step is to collect data from various sources, such as:<\/p>\n<ul>\n<li><strong>HR systems<\/strong> (e.g. SAP HR, Workday, TETA HR, enova365) that store information about employees&#8217; employment, salaries, working hours and absences. This data is often stored in closed ecosystems, so integration with Power BI is necessary via API or CSV\/Excel file exports. <\/li>\n<li><strong>Excel and Google Sheets <\/strong>are often used by HR departments to store detailed employee data, e.g. recruitment results, training plans or benefit budgets. Although this format is convenient, it requires regular updating and synchronisation with other data. <\/li>\n<li><strong>SQL databases<\/strong>, where comprehensive information about employment, organisational structure and history of personnel changes can be found. Integration with databases allows for automatic data retrieval and updates in real time. <\/li>\n<\/ul>\n<p>Power BI allows you to simultaneously combine data from different sources, thus avoiding working with incomplete and scattered information. This ensures that all key HR indicators are available and always up to date in one place. <\/p>\n<h3>Cleaning and preparing data<\/h3>\n<p>Data from different sources may contain errors and inconsistencies, so correct preparation is crucial for accurate analysis. Power Query allows you to remove missing values, standardise formats (e.g. uniform job titles), and combine and transform data from different HR systems. Importantly, eliminating duplicates and redundant records allows you to obtain consistent and reliable information. These actions make reporting more efficient and analyses more accurate.   <\/p>\n<h3>Data modeling<\/h3>\n<p>The next step is data modelling. This allows for optimised analysis by creating relationships between tables and defining key indicators. This makes it possible to analyse changes in employment, turnover and salaries in the context of the entire organisation. Using DAX allows for advanced calculations, such as segmentation of turnover by department or tracking recruitment trends. Good modelling makes reports dynamic and supports accurate HR decisions.    <\/p>\n<h3>Data visualization<\/h3>\n<p>Well-designed visualisations in Power BI make it easier to interpret HR data. It is worth using different types of charts depending on the indicators being analysed: <\/p>\n<ul>\n<li><strong>Bar and line charts <\/strong>\u2013 ideal for monitoring employment and turnover trends. For example, the number of new hires and departures can be displayed monthly and annually. <\/li>\n<li><strong>Pivot tables and matrices<\/strong> \u2013 useful for a detailed analysis of the employment structure in different departments and company locations. They allow for quick filtering and comparison of data. <\/li>\n<li><strong>Heat maps and scatter plots<\/strong> help identify areas with high employee turnover and analyse factors influencing staff fluctuation..<\/li>\n<li><strong>KPIs on dashboards<\/strong> \u2013 track key metrics such as average tenure, turnover, or the number of days it takes to hire a new employee.<\/li>\n<\/ul>\n<p>Interactive visualisations allow users to explore data and quickly detect key HR trends.<\/p>\n<h3>Create interactive dashboards<\/h3>\n<p>The final stage is creating dashboards in Power BI, which enable intuitive data exploration and quick decision-making. Thanks to filters and slicers, users can dynamically explore information by department, position, or period. Personalised views and automatic alerts make it easier to monitor key indicators and react to changes. This allows you to keep track of turnover, recruitment,, and other relevant trends in your organisation.   <\/p>\n<h2>How does Power BI help to reduce staff turnover?<\/h2>\n<h3>1. Analysis of resignation trends in different departments and periods<\/h3>\n<p>Microsoft Power BI allows you to monitor the number of employees leaving, broken down by specific departments, locations, and periods (e.g. months, quarters, years). This allows you to identify which teams are experiencing the highest turnover and whether there are seasonal departure patterns. For example, suppose the number of notices of termination submitted in a particular department increases every year simultaneously. In that case, this may suggest a problem related to workload, pay, or the atmosphere of the team. By analysing this data, preventive measures can be taken, such as changing the pay policy, increasing benefits or improving working conditions.   <\/p>\n<h3>2. Correlation of turnover with the results of satisfaction surveys<\/h3>\n<p>One of the key ways to predict employee turnover is to analyse their level of job satisfaction. Power BI allows you to combine turnover data with the results of satisfaction surveys, enabling you to identify the relationship between a low rating of working conditions and the number of employees leaving. For example, suppose employees in a particular department consistently report low satisfaction with management or the team atmosphere, and at the same time there is a high turnover in this department. In that case, this may indicate a need for personnel changes or the implementation of measures to improve team motivation. With this data, HR can take specific steps, such as training for managers, improving internal communication or implementing employee development programmes.   <\/p>\n<h3>3. Monitoring the impact of organisational changes on staff turnover<\/h3>\n<p>Many employees leave their jobs due to organisational changes such as restructuring, management changes, the introduction of new processes or company mergers. Power BI allows you to analyse the impact of such changes on employee turnover, enabling organisations to anticipate potential risks better. For example, suppose the number of employees leaving a department increases after a reorganisation. In that case, it can be analysed whether the changes have hurt team morale and whether stabilising measures are necessary. This allows the company to react more quickly to the negative effects of changes, e.g. through additional training, information sessions or support programmes for employees.   <\/p>\n<h3>4. Data segmentation according to age, seniority and job level<\/h3>\n<p>Microsoft Power BI allows for in-depth analysis of turnover in different demographic groups, which allows for a better understanding of which categories of employees leave most often and why. For example, the study may show that younger employees are likelier to go after a short period, suggesting the need to improve onboarding and adaptation programmes. On the other hand, if turnover is high among older, experienced employees, it may indicate a need to adjust promotion policies or improve the remuneration system. With this data, HR can implement more personalised retention strategies, such as mentoring, career paths tailored to different age groups, or flexible employment arrangements for seniors.   <\/p>\n<h3>5. Implementation of effective retention strategies<\/h3>\n<p>Data analysis in Power BI allows you to identify problems and solve them effectively by implementing appropriate retention strategies. Internal promotion programmes can be introduced if the data indicates that employees leave due to a lack of career paths. If the reason is salaries, it is worth reviewing and comparing the pay policy with the market. You can also implement loyalty programmes, benefits tailored to the needs of employees, and regular team discussions to increase engagement and job satisfaction. Thanks to Power BI, organisations can adapt their activities based on accurate data, increasing the effectiveness of HR strategies.    <\/p>\n<h2>Benefits of implementing Power BI in HR analysis<\/h2>\n<p>Power BI provides many benefits for HR departments, including:<\/p>\n<ul>\n<li><strong>Better data transparency<\/strong> \u2013 all indicators in one place, updated in real time,<\/li>\n<li><strong>Save time<\/strong> \u2013 automate reporting instead of creating Excel lists manually.<\/li>\n<li><strong>Improved decision-making <\/strong>\u2013 access to data enables faster and more accurate personnel decisions,<\/li>\n<li><strong>Customisable reports<\/strong> \u2013 reports can be customised to meet the needs of management, managers, and HR departments.<\/li>\n<li><strong>Trend forecasting<\/strong> \u2013 using artificial intelligence and machine learning in Power BI to predict future HR challenges.<\/li>\n<\/ul>\n<h2>Is it worth implementing Power BI in your company?<\/h2>\n<p>Power BI is a tool that supports the digital transformation of the HR department. It makes it easy to analyse data, predict trends and make decisions based on reliable information. Companies that implement Power BI gain a competitive advantage through more effective human resources management.  <\/p>\n<p>If your company wants to improve HR processes, monitor key indicators and minimise employee turnover, Power BI may be the ideal solution. Start using data analytics today to build a stronger and more committed workforce! <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Effective human resource management requires access to reliable data and tools that enable real-time analysis. Power BI is a solution that allows HR professionals to monitor employment and employee turnover rates, helping them make strategic decisions based on data. In this article, we will look at how to use Power BI for HR analysis and the benefits it brings to organisations.  <\/p>\n","protected":false},"author":2,"featured_media":10274,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[30],"tags":[409],"class_list":["post-8439","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-microsoft-power-bi-en","tag-hr-data-analysis-in-power-bi"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>HR data analysis in Power BI: monitoring employment and employee turnover | EBIS - Microsoft Power BI Partner<\/title>\n<meta name=\"description\" content=\"HR data analysis in Power BI - find out how modern data analysis systems can improve human resources management.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"HR data analysis in Power BI: monitoring employment and employee turnover | EBIS - Microsoft Power BI Partner\" \/>\n<meta property=\"og:description\" content=\"HR data analysis in Power BI - find out how modern data analysis systems can improve human resources management.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover\" \/>\n<meta property=\"og:site_name\" content=\"EBIS - Microsoft Power BI Partner\" \/>\n<meta property=\"article:published_time\" content=\"2025-03-11T08:15:17+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/powerbi.pl\/wp-content\/uploads\/2024\/03\/EBIS-RGB-znak_500px-3.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"500\" \/>\n\t<meta property=\"og:image:height\" content=\"186\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Ma\u0142gorzata Dadok-Grabska\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ma\u0142gorzata Dadok-Grabska\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"7 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":[\"Article\",\"BlogPosting\"],\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#article\",\"isPartOf\":{\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover\"},\"author\":{\"name\":\"Ma\u0142gorzata Dadok-Grabska\",\"@id\":\"https:\/\/powerbi.pl\/en#\/schema\/person\/0f852d864de2411bda6ff9991846aa20\"},\"headline\":\"HR data analysis in Power BI: monitoring employment and employee turnover\",\"datePublished\":\"2025-03-11T08:15:17+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover\"},\"wordCount\":1506,\"publisher\":{\"@id\":\"https:\/\/powerbi.pl\/en#organization\"},\"image\":{\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#primaryimage\"},\"thumbnailUrl\":\"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/03\/Analiza-danych-HR-w-Power-BI-monitorowanie-zatrudnienia-i-rotacji-pracownikow.svg\",\"keywords\":[\"HR data analysis in Power BI\"],\"articleSection\":[\"Microsoft Power BI\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover\",\"url\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover\",\"name\":\"HR data analysis in Power BI: monitoring employment and employee turnover | EBIS - Microsoft Power BI Partner\",\"isPartOf\":{\"@id\":\"https:\/\/powerbi.pl\/en#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#primaryimage\"},\"image\":{\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#primaryimage\"},\"thumbnailUrl\":\"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/03\/Analiza-danych-HR-w-Power-BI-monitorowanie-zatrudnienia-i-rotacji-pracownikow.svg\",\"datePublished\":\"2025-03-11T08:15:17+00:00\",\"description\":\"HR data analysis in Power BI - find out how modern data analysis systems can improve human resources management.\",\"breadcrumb\":{\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#primaryimage\",\"url\":\"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/03\/Analiza-danych-HR-w-Power-BI-monitorowanie-zatrudnienia-i-rotacji-pracownikow.svg\",\"contentUrl\":\"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/03\/Analiza-danych-HR-w-Power-BI-monitorowanie-zatrudnienia-i-rotacji-pracownikow.svg\",\"width\":900,\"height\":600,\"caption\":\"data analytics in hr power bi\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Strona g\u0142\u00f3wna\",\"item\":\"https:\/\/powerbi.pl\/en\/home-page\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"HR data analysis in Power BI: monitoring employment and employee turnover\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/powerbi.pl\/en#website\",\"url\":\"https:\/\/powerbi.pl\/en\",\"name\":\"EBIS - Microsoft Power BI Partner\",\"description\":\"us\u0142ugi analityczne\",\"publisher\":{\"@id\":\"https:\/\/powerbi.pl\/en#organization\"},\"alternateName\":\"Microsoft Power BI\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/powerbi.pl\/en?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/powerbi.pl\/en#organization\",\"name\":\"EBIS\",\"alternateName\":\"EBIS\",\"url\":\"https:\/\/powerbi.pl\/en\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/powerbi.pl\/en#\/schema\/logo\/image\/\",\"url\":\"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/12\/favicon-ebis.png\",\"contentUrl\":\"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/12\/favicon-ebis.png\",\"width\":512,\"height\":512,\"caption\":\"EBIS\"},\"image\":{\"@id\":\"https:\/\/powerbi.pl\/en#\/schema\/logo\/image\/\"},\"sameAs\":[\"https:\/\/www.linkedin.com\/company\/ebis-business-intelligence\/\"]},{\"@type\":\"Person\",\"@id\":\"https:\/\/powerbi.pl\/en#\/schema\/person\/0f852d864de2411bda6ff9991846aa20\",\"name\":\"Ma\u0142gorzata Dadok-Grabska\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/powerbi.pl\/en#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/ed5c3428270dd07207a7ff9b14e8e35984ed1601651e6daa7f1fb281f041b1df?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/ed5c3428270dd07207a7ff9b14e8e35984ed1601651e6daa7f1fb281f041b1df?s=96&d=mm&r=g\",\"caption\":\"Ma\u0142gorzata Dadok-Grabska\"},\"url\":\"https:\/\/powerbi.pl\/en\/blog\/author\/malgorzatadg\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"HR data analysis in Power BI: monitoring employment and employee turnover | EBIS - Microsoft Power BI Partner","description":"HR data analysis in Power BI - find out how modern data analysis systems can improve human resources management.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover","og_locale":"en_US","og_type":"article","og_title":"HR data analysis in Power BI: monitoring employment and employee turnover | EBIS - Microsoft Power BI Partner","og_description":"HR data analysis in Power BI - find out how modern data analysis systems can improve human resources management.","og_url":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover","og_site_name":"EBIS - Microsoft Power BI Partner","article_published_time":"2025-03-11T08:15:17+00:00","og_image":[{"width":500,"height":186,"url":"https:\/\/powerbi.pl\/wp-content\/uploads\/2024\/03\/EBIS-RGB-znak_500px-3.webp","type":"image\/webp"}],"author":"Ma\u0142gorzata Dadok-Grabska","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Ma\u0142gorzata Dadok-Grabska","Est. reading time":"7 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":["Article","BlogPosting"],"@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#article","isPartOf":{"@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover"},"author":{"name":"Ma\u0142gorzata Dadok-Grabska","@id":"https:\/\/powerbi.pl\/en#\/schema\/person\/0f852d864de2411bda6ff9991846aa20"},"headline":"HR data analysis in Power BI: monitoring employment and employee turnover","datePublished":"2025-03-11T08:15:17+00:00","mainEntityOfPage":{"@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover"},"wordCount":1506,"publisher":{"@id":"https:\/\/powerbi.pl\/en#organization"},"image":{"@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#primaryimage"},"thumbnailUrl":"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/03\/Analiza-danych-HR-w-Power-BI-monitorowanie-zatrudnienia-i-rotacji-pracownikow.svg","keywords":["HR data analysis in Power BI"],"articleSection":["Microsoft Power BI"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover","url":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover","name":"HR data analysis in Power BI: monitoring employment and employee turnover | EBIS - Microsoft Power BI Partner","isPartOf":{"@id":"https:\/\/powerbi.pl\/en#website"},"primaryImageOfPage":{"@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#primaryimage"},"image":{"@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#primaryimage"},"thumbnailUrl":"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/03\/Analiza-danych-HR-w-Power-BI-monitorowanie-zatrudnienia-i-rotacji-pracownikow.svg","datePublished":"2025-03-11T08:15:17+00:00","description":"HR data analysis in Power BI - find out how modern data analysis systems can improve human resources management.","breadcrumb":{"@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#primaryimage","url":"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/03\/Analiza-danych-HR-w-Power-BI-monitorowanie-zatrudnienia-i-rotacji-pracownikow.svg","contentUrl":"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/03\/Analiza-danych-HR-w-Power-BI-monitorowanie-zatrudnienia-i-rotacji-pracownikow.svg","width":900,"height":600,"caption":"data analytics in hr power bi"},{"@type":"BreadcrumbList","@id":"https:\/\/powerbi.pl\/en\/blog\/microsoft-power-bi-en\/hr-data-analysis-in-power-bi-monitoring-employment-and-employee-turnover#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Strona g\u0142\u00f3wna","item":"https:\/\/powerbi.pl\/en\/home-page"},{"@type":"ListItem","position":2,"name":"HR data analysis in Power BI: monitoring employment and employee turnover"}]},{"@type":"WebSite","@id":"https:\/\/powerbi.pl\/en#website","url":"https:\/\/powerbi.pl\/en","name":"EBIS - Microsoft Power BI Partner","description":"us\u0142ugi analityczne","publisher":{"@id":"https:\/\/powerbi.pl\/en#organization"},"alternateName":"Microsoft Power BI","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/powerbi.pl\/en?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/powerbi.pl\/en#organization","name":"EBIS","alternateName":"EBIS","url":"https:\/\/powerbi.pl\/en","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/powerbi.pl\/en#\/schema\/logo\/image\/","url":"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/12\/favicon-ebis.png","contentUrl":"https:\/\/powerbi.pl\/wp-content\/uploads\/2025\/12\/favicon-ebis.png","width":512,"height":512,"caption":"EBIS"},"image":{"@id":"https:\/\/powerbi.pl\/en#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.linkedin.com\/company\/ebis-business-intelligence\/"]},{"@type":"Person","@id":"https:\/\/powerbi.pl\/en#\/schema\/person\/0f852d864de2411bda6ff9991846aa20","name":"Ma\u0142gorzata Dadok-Grabska","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/powerbi.pl\/en#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/ed5c3428270dd07207a7ff9b14e8e35984ed1601651e6daa7f1fb281f041b1df?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/ed5c3428270dd07207a7ff9b14e8e35984ed1601651e6daa7f1fb281f041b1df?s=96&d=mm&r=g","caption":"Ma\u0142gorzata Dadok-Grabska"},"url":"https:\/\/powerbi.pl\/en\/blog\/author\/malgorzatadg"}]}},"_links":{"self":[{"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/posts\/8439","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/comments?post=8439"}],"version-history":[{"count":0,"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/posts\/8439\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/media\/10274"}],"wp:attachment":[{"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/media?parent=8439"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/categories?post=8439"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/powerbi.pl\/en\/wp-json\/wp\/v2\/tags?post=8439"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}