Pesala Mallikharjuna Prasad’s Post

🔥 𝐄𝐧𝐡𝐚𝐧𝐜𝐢𝐧𝐠 𝐒𝐥𝐢𝐜𝐞𝐫 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐒𝐭𝐲𝐥𝐞𝐬 𝐢𝐧 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐟𝐨𝐫 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐌𝐚𝐤𝐞𝐫𝐬 🔥 When creating reports for CEOs and business decision-makers, it's essential to provide a walkthrough that offers a clear understanding of the data. In Power BI, slicers play a crucial role in this process, especially when using the multi-select option. We can visualize these slicers in two different styles to cater to varying needs: 1. 𝐌𝐢𝐧𝐢𝐦𝐚𝐥𝐢𝐬𝐭𝐢𝐜 𝐒𝐭𝐲𝐥𝐞 This style focuses on simplicity and efficiency. By using a measure and a card visual, we can showcase the number of values selected and the total number of available values. This approach provides a clean, straightforward view of the data selection without overwhelming the user. 2. 𝐃𝐞𝐭𝐚𝐢𝐥𝐞𝐝 𝐒𝐭𝐲𝐥𝐞 In addition to the minimalistic details, this style displays the actual values selected, offering a more comprehensive walkthrough of the data. This detailed view helps decision-makers understand exactly what data points are being analyzed. 𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐅𝐨𝐫𝐦𝐚𝐭𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐫𝐨𝐬𝐬-𝐅𝐢𝐥𝐭𝐞𝐫𝐢𝐧𝐠 𝐎𝐩𝐭𝐢𝐨𝐧𝐬 Power BI allows for conditional formatting to highlight slicers based on selection status. For example, in the accompanying video, you'll see slicers that are color-coded to indicate whether or not they have been selected. This visual cue can enhance the user's interaction with the report. Furthermore, Power BI provides the option to enable or disable cross-filtering between slicers as needed, offering flexibility in how data is viewed and analyzed. Conclusion By customizing slicer visualization styles and leveraging conditional formatting and interaction options, we can create more engaging and informative reports for decision-makers. 🎯 𝐏𝐥𝐞𝐚𝐬𝐞 𝐬𝐡𝐚𝐫𝐞 𝐲𝐨𝐮𝐫 𝐭𝐡𝐨𝐮𝐠𝐡𝐭𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐜𝐨𝐦𝐦𝐞𝐧𝐭𝐬 𝐛𝐞𝐥𝐨𝐰, 𝐚𝐧𝐝 𝐝𝐨𝐧'𝐭 𝐟𝐨𝐫𝐠𝐞𝐭 𝐭𝐨 𝐥𝐢𝐤𝐞, 𝐬𝐡𝐚𝐫𝐞, 𝐚𝐧𝐝 𝐟𝐨𝐥𝐥𝐨𝐰 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐬𝐮𝐜𝐡 𝐜𝐨𝐧𝐭𝐞𝐧𝐭! #PowerBI #DataVisualization #Insights #Analytics #SlicerVisualization #SubscribeNow #DataVisualization #ReportMakeover #DataInsights #VisualAppeal #DataViz #report #dashboard #pbicorevisuals #powerbiupdate #visualization #salestrends #FigmaTemplates #ContentCreation #DynamicReports #CommunityThanks #PWP #DAX #DAXDairy #DataAnalyst #DataAnalytics #Vega #BusinessIntelligence #Visualization #BI #PowerBIDeveloper #Deloitte #KPMG #EY #tcs #pwc #Infosys #Developer #PowerBIwithPrasad #Lumel #VisualCustomization #Creativity #LikeShareSubscribe

Hey connections I am 🚀 excited to share my Thrid project 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝘃𝗲 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱📈 done in Power Bi. 🔍 𝗧𝗶𝘁𝗹𝗲 : EdgeTech: Pioneering Excellence in Quality, Profitability, and Sustainability 📋 𝗦𝗧𝗘𝗣𝗦 𝗙𝗢𝗟𝗟𝗢𝗪𝗘𝗗: 1️⃣ 𝗗𝗔𝗧𝗔 𝗦𝗢𝗨𝗥𝗖𝗘: Gathered from Kaggle. 2️⃣ 𝗗𝗔𝗧𝗔 𝗧𝗥𝗔𝗡𝗦𝗙𝗢𝗥𝗠𝗔𝗧𝗜𝗢𝗡: Used Power Query to clean the data, removed nulls and duplicates, and fine-tuned data types. 3️⃣ 𝗗𝗔𝗧𝗔 𝗟𝗢𝗔𝗗𝗜𝗡𝗚: Imported the transformed data into Power View for analysis. 4️⃣ 𝗗𝗔𝗧𝗔 𝗜𝗠𝗣𝗟𝗘𝗠𝗘𝗡𝗧𝗔𝗧𝗜𝗢𝗡: Leveraged DAX to create calculated measures and columns, refining the data for deeper insights. 5️⃣ 𝗥𝗘𝗣𝗢𝗥𝗧𝗦 𝗖𝗥𝗘𝗔𝗧𝗜𝗢𝗡: Crafted user-friendly visualizations that tell a compelling data story through our dashboard. 🌟 𝗘𝗹𝗲𝘃𝗮𝘁𝗶𝗻𝗴 𝗘𝗱𝗴𝗲 𝗧𝗲𝗰𝗵'𝘀 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: 𝗞𝗲𝘆 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 🌟 🔍 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 • Return rate at 6.8%, showing steady improvement over the years. • Addressing issues like wrong color (62%) and defective products (21%) to enhance satisfaction. 💼 𝗣𝗿𝗼𝗳𝗶𝘁 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 • Gross profit at $14.81M with a robust 99% margin. • Prioritizing high-profit product categories and customer segments for strategic growth. 🌱 𝗦𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗖𝗼𝗺𝗺𝗶𝘁𝗺𝗲𝗻𝘁 • Recycling rate at 91.8%, showcasing environmental responsibility. • Embracing eco-friendly practices for a greener future. 📈 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁 • Monitoring and setting targets for ongoing enhancement across all   fronts. • Striving for excellence in quality, profitability, and sustainability. Any suggestions will be welcome 😊 #MicrosoftPowerBi #PowerQuery #DAX #Datamodeling #Ecommerce #networking #freshers #KPI #sales #RelationshipBuilding #DataVisualization #PowerBiServices #Deloitte #TigerAnalytics #Pwc #Kpmg #EY #HCL #Wipro #BIResearch #codebasics #DataAnalysis #MarketInsights #BusinessStrategy #ConsumerBehavior #Analytics #dashboard #research #Microsoft #kaggle #PowerQuery #Excel #sql #powerbi #powerbideveloper #data #businessintelligence #CEO #internship #AI #ML #Accounts

𝐄𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐒𝐢𝐧𝐠𝐥𝐞-𝐋𝐢𝐧𝐞 𝐚𝐧𝐝 𝐌𝐮𝐥𝐭𝐢-𝐋𝐢𝐧𝐞 𝐎𝐩𝐭𝐢𝐨𝐧𝐬 𝐢𝐧 𝐃𝐚𝐭𝐚 𝐋𝐚𝐛𝐞𝐥𝐬 𝐢𝐧 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈🌀✨ Data visualization is a powerful tool for understanding and communicating insights from data. One key aspect of effective data visualization is the use of data labels, which provide context and clarity to visualized information. In this article, we'll explore the differences between single-line and multi-line options in data labels and discuss when each option is most appropriate. Understanding Data Labels: Data labels are text elements associated with data points in a chart or graph. They display key information such as values, percentages, or category names directly on the visual representation of the data. Data labels enhance the interpretability of charts by providing viewers with precise data points without the need for reference to a separate legend or axis. 🎯 Single-Line Data Labels: Single-line data labels, as the name suggests, consist of text displayed on a single line. They are often used in situations where space is limited or where a concise presentation is preferred. Single-line data labels are well-suited for simple charts with a small number of data points, such as bar charts or pie charts. 🎯 Multi-Line Data Labels: Multi-line data labels allow for the display of text across multiple lines. They are particularly useful when conveying complex information or when longer descriptions are necessary to provide context to data points. Multi-line data labels are commonly used in line charts, scatter plots, or other visualizations with more detailed data. P.S. Don't forget to like, share, and follow for more such content. #PowerBI #DataViz #ZapRing #Zapringtechnoversion #DENEB #FigmaTemplates #ContentCreation #DynamicReports #CommunityThanks #pwp #powerbi #dax #daxdairy #dataanalyst #dataanalytics #Vega #businessintelligence #visualization #bi #powerbideveloper #deloitte #kpmg #ey #developer #powerbiwithprasad

Question 120: What is the difference between general purpose clusters & job cluster? I) General-Purpose Clusters: -> General-purpose clusters are interactive clusters that provide a platform for running interactive queries, notebooks, and ad-hoc analyses. -> They are designed for exploratory data analysis, data visualization, and collaborative work where users can interactively run code and queries. -> These clusters are long-running, meaning they can be kept alive for an extended period of time. -> General-purpose clusters are suitable for scenarios where you want to provide users with a continuous environment for running code and analyzing data interactively. -> They can be attached to notebooks, where users can write code and execute it directly on the cluster. II) Job Clusters: -> Job clusters are temporary clusters that are spun up specifically to run batch jobs or tasks. ->They are designed for running scheduled jobs, data processing tasks, and workflows. -> Job clusters are created, run the specified job, and then terminated automatically once the job is completed. This helps manage resources efficiently, as you're not paying for idle clusters. -> Job clusters are suitable for scenarios where you need to process data periodically or on a scheduled basis, such as ETL processes or data pipeline steps. -> You can define the job settings and configurations, including the cluster type, number of nodes, and libraries needed for the job. -> Once the job is done, the cluster is automatically terminated, saving costs and resources. In summary, the main difference between general-purpose clusters and job clusters lies in their use cases and lifecycles. General-purpose clusters are meant for interactive analysis and can be kept alive for longer periods, while job clusters are designed for executing specific batch jobs and are created and terminated as needed to optimize resource utilization. The choice between these two types of clusters depends on your specific requirements, whether you're working interactively or running scheduled data processing tasks. #databricks #pyspark #spark #clusters #interviewpreparation #deloitteinterview

Title: "Alteryx Data Cleaning Tutorial: Converting Unstructured Data to Structured Data" Description: Are you ready to master data cleaning and transformation with Alteryx? In this comprehensive tutorial, I'll guide you through the process of converting unstructured data into structured, actionable insights. As a skilled data analyst with hands-on experience in Alteryx, I'll walk you through each step of the workflow, from removing null values to refining column data types. In this video, you'll learn: How to leverage Alteryx's intuitive interface to streamline the data cleaning process Techniques for identifying and eliminating null values to ensure data accuracy Strategies for removing unnecessary columns and optimizing data structure for analysis Tips for performing data type changes to ensure consistency and compatibility Whether you're a seasoned data professional looking to expand your skill set or a newcomer eager to learn the fundamentals of data cleaning, this tutorial is perfect for you. Join me on this journey to unlock the full potential of your data and take your analytical skills to the next level. Don't miss out on this opportunity to enhance your expertise and stay ahead in today's competitive job market. Watch now and start transforming your data with Alteryx! #DataAnalytics #DataCleaning #DataTransformation #Alteryx #DataInsights #DataDrivenDecisions #AnalyticsInnovation #DataScienceSkills #TechTalent #HRRecruitment #CEOInsights #DigitalTransformation #BusinessIntelligence #DataProficiency #AnalyticsStrategy #FutureOfWork #SkillsDevelopment #TalentAcquisition #DataLeadership #AnalyticsExcellence

Miguel Myers and the #pbicorevisuals Team - as I've been taking the #IBCS Certified Analyst course this week, I've realized that you are at this moment uniquely positioned to change business reporting for the entire world... ...and while the thoughts are fresh in my mind, I wanted to take this opportunity to encourage you to go "all in" in doing so. Published research demonstrates that incorporation of IBCS standards into business reporting processes can increase user processing speed by 46%, and decrease interpretation errors by 61%. The adoption of IBCS by top corporations, including Mercedes Benz, Coca Cola, Philips, SAP and many others underscores these benefits. However, currently to fully implement the IBCS standard within #powerbi requires the use of custom visuals which limits adoption in 3 major ways: 🔸 Organizational restrictions - per surveys I've done of Power BI developers, approximately 1/3 of their organizations outright ban the use of custom visuals, or require a formal exception request that is rarely granted 🔸 Cost constraints - there are a number of high-quality custom visuals for Power BI that are relatively easy to use, but can be costly to implement - putting them out range for a substantial number of organizations and independent developers 🔸 Expertise constraints - conversely, there are excellent free alternatives including #deneb and #ggplot2 that can produce IBCS-consistent visuals, but each require a dedicated visualization "grammar" with a steep learning curve However, recently added features to the native Power BI visuals including error bars, the new Card visual, reference labels, and the Dec 2023 bar and column enhancements have begun to open the door for IBCS implementation using only native visuals - a trend I enthusiastically support. While IBCS implementation was not the primary driver behind the addition of these features, innovative leaders within the Power BI community (some members of the PBI Core Visuals Team), including Andrzej Leszkiewicz, Aleksandra Godlewska, Gustaw Dudek, Imran Haq, Chris A., Davide Bacci and others have been leading the way in showing how these capabilities can be used to create IBCS-type visuals and reports. As impressive as their work is, in many cases it remains a bit of a "magic trick", requiring advanced skills in areas such as DAX or dynamic SVG image creation, which are outside the capabilities of the average Power BI user. Thus, as the #pbicorevisuals team is evaluating its priorities for 2024, I would urge you to prioritize those enhancements to the core visuals that will not only enable these capabilities for experts, but make them accessible to a wide range users. I believe doing so will not only benefit Power BI users (and hopefully, Excel users as well), but as the dominant player in business software, Microsoft will send a clear message that will strengthen the IBCS standard worldwide, and raise the bar for business reporting globally.

Day 8 of Data Analytics Series. Using E- commerce data to create interactive power Bi dashboard. Powerbi is a powerful tool for Data Visualisation and listing out KPI’s to understand business metrics. Learning its fundamentals step by step by creating dashboards that involve using #OLAP functions like slice-dice, roll up , drill through etc. . . . . . #Datascience #jobs #analyst #kpmg #target #deloitte #wellsfargo

Hello Everyone, Hope you doing great, This is Anudeep from BMR infotek. We have an open position with our client, Role Tableau Developer Location Remote This is Anudeep from BMR infotek. We have an open position with our client, Role Tableau Developer Location Remote Client uses Exo-insight and Alteryx to extract information from PBCS. Data is extracted from a PBCS ASO cube. Much of the data would be available within two different BSO cubes, but all of it is available in the ASO cube.  Client has been working on building extracts out of PBCS for over a year and has made little to no process. The extracts take too long as they are pulling dynamically calculated members across accounts and views (i.e. YTD, QTD). YTD and QTD calculations are not always as simple as adding up the months, but need to be recalculated with the YTD numerator and YTD denominator.  If we can make minor changes to PBCS to support a better Tableau process we can take care of those updates.  There is a concern about managing calculations in both PBCS and Tableau. However, they are open to including calculations in Tableau if the risk of the calculation changing is low.  An example of one of the calculations that takes a long time to extract is primary stats. Each department is assigned a primary stat with a flag in EPBCS. The calculation references the flag and pulls the data for the corresponding statistic. Extracting this dynamic calc from EPBCS takes quite a bit of time. We could migrate the statistics and department flags to Tableau and have that calculate on the tableau side with very low risk that the tableau calculation would change.  They want about 30 analysis across 4 dashboards. Many of the analysis have the same or similar row structure, but have a different view of columns (12 month, PY Comparison, Actuals vs Forecast, etc). All of these analysis currently exist out of EPBCS. They don’t need to match the exact format of the PBCS report, but being able to pull the data into a usable format in excel is important to them. Thanks and Regards, Anudeep Reddy BMR Infotek, Inc. anudeep@bmrinfotek.com #tableau #alteryx #PBCS #benchsales #c2C #requirement #remote #consultants

This week, 📊 I had the opportunity to dive into customer financial behavior using the TechnoEdge company dataset in Power BI. Since Power BI is widely used and familiar, 🛠️ it was the perfect tool to create a customized solution that is both easy to use and highly informative. Here's what I accomplished: 1. 🌍 Displayed all geographical datasets in Power BI along with their corresponding data categories such as city, country, state, and region. 2. 📈 Showed the total number of customers, average annual income, average monthly debt, and total credit balance using cards and DAX formulas. 3. 📅 Presented the trend of current credit balance over time using an Area chart based on the date customers joined. 4. 🗺️ Compared the total loan amount by state using a clustered bar chart. 5. 🍰 Analyzed the distribution of loan statuses using a pie chart categorized by gender. Functions and features utilized: 1. ➕ DAX formulas 2. 🃏 Cards 3. 🔄 Slicers 4. 📉 Area Chart 5. 🥧 Pie Chart 6. 📊 Clustered Bar Chart 7. 📝 Text Box I'm thrilled with how the system turned out—it offers a clear, organized, and insightful view of customer financial behavior. This project reinforced my belief that with the right approach, Power BI can be a powerful tool for tracking finances and extracting meaningful insights. I hope you find this post helpful. Please feel free to share your feedback and suggestions in the comments below. 🌟 #Powerbi #DataAnlytics #DataModeling #DataVisualizations #DAX #PowerBiDeveloper #BankingSector #pawanlalwani #realtimeproject #ETL #Excel #datascientist #datascience #datacleaning #powerquery #powerpivot Hexaware Technologies Cognii.Co Cognizant Infosys Tech Mahindra Accenture in India

Power BI may seem like a visualization tool if you only use it to change chart colors and shadows. I promise it's much more! 𝐄𝐓𝐋 𝐄𝐍𝐆𝐈𝐍𝐄 (𝐏𝐨𝐰𝐞𝐫 𝐐𝐮𝐞𝐫𝐲) Power Query, the ETL (Extract, Transform, Load) engine, connects to SQL, CSV, Excel, emails, PDFs, and more. The goal is to organize, clean, and connect data for use. 𝐕𝐄𝐑𝐓𝐈𝐏𝐀𝐐 𝐄𝐍𝐆𝐈𝐍𝐄 (𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠 & 𝐂𝐚𝐥𝐜𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬) The VertiPac Engine receives cleaned data. Set up the Power BI model by writing DAX calculations and creating relationships. In these areas, Power BI will help you most. A well-built model can generate many reports for different business functions and departments. 𝐕𝐈𝐒𝐔𝐀𝐋𝐈𝐙𝐀𝐓𝐈𝐎𝐍𝐒 Power BI is more than a visualization tool, as many people think. The visualization layer creates attractive and understandable reports and charts from modeled data. 𝐒𝐇𝐀𝐑𝐈𝐍𝐆 𝐀𝐍𝐃 𝐂𝐎𝐋𝐋𝐀𝐁𝐎𝐑𝐀𝐓𝐈𝐎𝐍  You can upload your work to PowerBI.com to safely share with coworkers or bosses, making it different from other file sharing methods. With this feature, Power BI can share business intelligence as well as create reports. Power BI shouldn't be limited to visualization. Source: Goodly, Chandeep Chhabra -------------- Join me and ring the bell 🏏Azar Shaik. Every day I tell you how to do Data Analysis. -------------- Share this information with loved ones ♻ Shashank Singh 🇮🇳, Raghavan P, Munna Das, Mandar Patil, Aniket Kardile, Jess Ramos, MSBA #powerbi #powerbiinterview #questions #techmahindra #data #dataanalysts #interviewquestions #deloitte #servicebasedcompany #Scenariobased #techmahindhra #Accenture #Capgemini #MilEstOneCrEaTor #LearnWidGiggs #Goodly