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Solving Inventory Woes at Better Buys Wholesale: A Power BI DAX Journey

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In today’s blog, we’re diving into one of the most common business challenges—inventory management. Whether you run a big operation or a small shop, the headache of maintaining the right stock levels is something everyone faces. In this fictional tale, we’ll use made-up numbers and scenarios to explore how Better Buys Wholesale (an imaginary FMCG giant) solved their inventory issues. For structure, I’m leaning on ChatGPT for support, while my own experience fills in the rest! The Better Buys Inventory Dilemma Picture this: Better Buys Wholesale is swimming in SKUs—over 1,500 of them. Their inventory spans everything from daily necessities to seasonal favorites. Yet, they’re struggling to find the balance between too much stock and too little. Imagine running out of that trendy summer drink just when customers are desperate for it, only to have a mountain of unsold, slow-moving snacks taking up valuable space in the warehouse. Sound familiar? It’s the classic inventory nightmare: ...
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Unlocking Sales Insights: Analyzing TADS, ADS, Shortfall, RADS, and Projections in Distribution Sales

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In today’s fast-paced distribution sales environment, businesses must rely on data-driven insights to stay competitive. Sales data holds valuable information that can empower companies to make informed decisions, hit their targets, and anticipate future demand. But to unlock these insights, it's essential to understand and analyze key performance indicators (KPIs) such as Target Average Daily Sales (TADS), Average Daily Sales (ADS), shortfall analysis, Required Average Daily Sales (RADS), and sales projections. In this blog, we’ll explore how businesses can utilize these metrics using DAX (Data Analysis Expressions) in Power BI , turning raw sales data into actionable insights. We’ll dive into real-life scenarios with XYZ Distributors , a mid-sized consumer electronics distributor based in the USA. A Real-Life Example: XYZ Distributors Imagine XYZ Distributors , a company with a product line that includes smartphones, home appliances, and other electronics. They sup...
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Big Problem, Small Solution: Using USERELATIONSHIP to Solve Performance Issues in Power BI

In the world of data analysis, especially in complex industries like distribution, building efficient dashboards can be a daunting task. I was recently asked to create a dashboard that tracks the performance hygiene of multiple distribution businesses. We called this dashboard "Rise of Discipline." The Challenge: Monitoring Performance Hygiene The key performance indicators (KPIs) we needed to track were quite comprehensive, including: Daily on-time presence of all employees at each distribution house. Daily Sales Target vs. Achievement (TGT vs ACH). Daily on-time (within Service Level Agreement - SLA) sales confirmation. Daily on-time deposit confirmation. Weekly petty expense entry (at least two times per week). Monthly budget vs. expense status. To complicate things further, we could only measure performance on weekdays. Holidays and weekends were excluded, but we still needed to track monthly targets on a month-to-date (MTD) basis, regardless o...
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Why Every Power BI Data Analyst Needs a Calendar Table (And How to Create One)

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As a Power BI Data Analyst, having a robust calendar table is absolutely essential. Whether you're performing advanced time-based calculations or managing period-specific metrics like Year-To-Date (YTD), Month-To-Date (MTD), or Week-To-Date (WTD), a well-constructed calendar table will be your go-to tool. It helps you efficiently handle time intelligence, improving both the accuracy and scalability of your reports. Without a proper calendar table, managing time-sensitive data becomes cumbersome, especially when you're dealing with complex date-based KPIs in various industries. The good news? Creating a calendar table is straightforward, and you can do it using DAX in Power BI. Here’s the DAX code to create a calendar table in Power BI: This DAX formula will help you create a dynamic and flexible calendar table that you can use for various time-related calculations in your Power BI models. Need the code in an easy-to-share format? Download the PD...
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Overcoming Challenges in Creating Calendar Tables in Power BI

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When it comes to crafting calendar tables in Power BI, users often face a range of hurdles that can complicate their data analysis journey: Navigating Multiple Date Columns: Having multiple date columns within a single table can make it challenging to accurately determine the minimum and maximum dates needed for a cohesive calendar. Limitations of MIN and MAX Functions: Relying solely on MIN and MAX dates to generate a Calendar table can create significant issues. This approach restricts comparisons, such as evaluating current sales against those from previous months, since the Calendar table will be limited to the specified date range. Cumbersome Time Intelligence Activation: Initiating Time Intelligence features under specific conditions can be tedious and inefficient when using traditional methods. Fortunately, these challenges can be effectively resolved by leveraging BRAVO , a powerful open-source tool meticulously designed to streamline the creation of Calen...
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TOPN

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Finding the top Nth largest or smallest data from a result set is a common request we receive in our everyday work as data analysts. Those N-values at the top or bottom of the list have a lot of power, which could help with their potential interpretations. Consider the hundreds of goods you might have in your business. You must be aware of which products are most popular and which are underperforming as a businessperson. You can guarantee your business growth with that knowledge. Making business choices will be simpler for you if you are familiar with the best-selling products. The TOPN() dax function in DAX has the best and simplest solution for your issue. My PBIX file on it contains more details, which you can read. PBIX file link: TOPN
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COUNT

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One well-liked data analysis function is count. It is something that a data analyst must employ frequently. While working with various counts, there may occasionally be some confusion. By briefly describing its type and definition in this PBIX file, I try to capitalize on the uncertainty that has arisen. The pbix file link: COUNT
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