HR INSIGHTS DASHBOARD

Getting Started

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Optimizing HR Analytics Capabilities with Power BI:

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A Simple Guide to Enhancing Smart Decision-Making in Modern Businesses. Discover how user-friendly dashboards can provide HR professionals with fast and valuable insights to improve decision-making. HR dashboards empower professionals to make data-driven decisions that optimize workforce management, enhance employee satisfaction, and drive organizational success.

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Project Overview:

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• Topic: HR Analysis Insights 

• Data Source: Sample HR dataset

• Tools Used: Excel & Power BI

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Project Achievements:

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• Improved team retention strategies

• Enhanced the hiring process

• Enhanced overall work quality

• Boosted individual productivity

• Increased trust among team members

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Data Gathering and Import

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• The initial step involves gathering relevant data and defining business requirements.

• For this project, sample data provided in Excel format will be used.

• After the installation of Power BI Desktop, the data is imported by selecting the appropriate file type and loading the tables. This action establishes a connected dataset for analysis within Power BI.

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Data Transformation

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After importing the raw data, the next step involves cleaning and transforming it to make it easier for analysis. Key steps in this process include:

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• Removing irrelevant columns 

• Eliminating duplicate values

• Using Find and Replace

• Adjusting data types

• Introducing new conditional columns

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Visualization and Reporting

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By utilizing Power BI's visualization tools, informative charts are created to display employee demographics such as age distribution, gender diversity, and departmental representation. With structured data, effective visualization is achieved, providing valuable insights for better decision-making. Key components include:

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• Attrition Report: This report presents key performance indicators (KPIs) such as the total number of employees, total attrition, attrition rates, average age, average salary, and average years of employment, providing a comprehensive snapshot of organizational performance. It offers a comprehensive view of the company's attrition analysis.

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• Attrition By Education Donut Chart: Examining attrition rates by educational background offers insights into how education influences employee retention, guiding the development of retention strategies and skill enhancement initiatives. The doughnut chart highlights attrition rates: Life Sciences (38%), Medical (27%), Technical (14%), Marketing (15%), Other (5%), and Human Resources (3%).

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• Attrition By Age Column Chart: Exploring the reasons why individuals leave their jobs at different ages enables companies to create strategies to maintain employee satisfaction throughout their careers. This column chart illustrates the sum of attrition counts based on age groups. The age group 26-35 had the highest sum of attrition counts at 116, accounting for approximately half of the total. Across all five age groups, the sum of attrition counts ranged from 8 to 116.

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• Attrition By Gender: Analyzing why employees leave their jobs, particularly based on gender, can reveal any disparities in the workplace that may contribute to attrition among men and women. Addressing these variations promotes a fair and inclusive work environment, ultimately improving employee retention.

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• Attrition By Salary: Understanding how many people leave their jobs based on their pay helps identify if there are problems with compensation affecting job retention. This column chart shows that employees earning between 5k and 10k are more likely to leave their jobs compared to others. Fixing pay issues can make employees happier and more likely to stay.

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• Attrition By Job Role: Examining job-specific attrition rates helps identify potential issues within each department, allowing companies to take targeted action to improve retention. Laboratory Technicians had the highest sum of attrition count at 62, while HR had the lowest at 12, as shown in this column chart.

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• ​Job Satisfaction Matrix: This matrix displays the ratings given by employees in different job roles. It reveals that Laboratory Technicians expressed the lowest satisfaction, as indicated by the highest number of 1-star ratings.

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• Attrition By Years at Company: Understanding attrition rates based on employee tenure sheds light on retention challenges. Identifying why employees leave at different stages helps develop strategies to cultivate engagement and loyalty throughout their time with the company.

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• Job Involvement By Gender: Analyzing job involvement levels across genders provides insights into workforce dynamics. Understanding the differences in job engagement between male and female employees helps craft initiatives to promote equality and inclusivity in the workplace.

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• Departmental Slicer: This slicer allows users to filter data based on departmental values such as HR, Research & Development, and Sales.

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Conclusions: To sum up, using data is vital for HR Analytics. Understanding how employees behave, what they aim for, and how many leave, while also keeping an eye on the bigger picture of the company, helps in making smart choices. This enables HR teams to refine their strategies and stay ahead in the fast-paced online landscape.

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