AnalystUnyime (@datadetective_u) 's Twitter Profile
AnalystUnyime

@datadetective_u

Data Analyst | Business Intelligence Analyst | Business Analyst

ID: 3343827874

linkhttps://www.linkedin.com/in/unyimeenangudo-data-analyst calendar_today24-06-2015 08:29:59

46 Tweet

73 Takipçi

1,1K Takip Edilen

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

For example: site: icims. com "ESG analyst" "New York" site:apply.workable.com "data analyst" "fully remote" site: greenhouse.io "UI/UX designer" "Remote" site:jobs.smartrecruiters.com "front end developer manager" "United Kingdom"

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

site:lever.co "content writer" "Dubai" site: myworkdayjobs.com "Cybersecurity Expert" "London" This is a game-changer for job seekers!

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

10 Essential DAX Functions Every Power BI Learner Should Know! If you’re learning Power BI, mastering DAX is a must! Here are 10 powerful DAX functions that will enhance your data analysis skills: 1. SUM – Calculate total sales. Total Sales = SUM(Sales[SalesAmount])

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

2.AVERAGE – Find the average sales per transaction. Average Sales = AVERAGE(Sales[SalesAmount]) 3.COUNTROWS – Count the number of transactions. Transaction Count = COUNTROWS(Sales) 4. DISTINCTCOUNT – Count unique customers. Unique Customers = DISTINCTCOUNT(Sales[CustomerID])

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

5. CALCULATE – Apply filters dynamically (e.g., sales for a specific category). Total Sales (Category) = CALCULATE(SUM(Sales[SalesAmount]), Products[Category] = "Electronics")

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

6.FILTER – Calculate sales above a threshold. High Value Sales = CALCULATE(SUM(Sales[SalesAmount]), FILTER(Sales, Sales[SalesAmount] > 1000))

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

7. IF – Categorize transactions as "High" or "Low" based on sales amount. Transaction Category = IF(Sales[SalesAmount] > 500, "High", "Low") 8. RELATED – Fetch product names from the Products table into the Sales table. Product Name = RELATED(Products[ProductName])

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

9. YEAR – Extract the year from a transaction date. Transaction Year = YEAR(Sales[TransactionDate]) 10. DATESYTD – Calculate year-to-date sales. YTD Sales = TOTALYTD(SUM(Sales[SalesAmount]), Sales[TransactionDate])

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

DAX makes your Power BI reports more dynamic, insightful, and powerful, helping you analyze data more effectively! Which of these functions do you use most often? Or do you have a favorite not listed here? Let’s discuss in the comments!

Dr. Khulood Almani | د.خلود المانع (@khulood_almani) 's Twitter Profile Photo

💥🧠What are the🔝60 #AI Tools You Can’t Afford to Miss in 2025❓ 🌟 ما هي أهم 60 أداة ل #الذكاء_الاصطناعي لعام 2025؟ 1️⃣ 🎥 Video Editing: ↳ Transform video creation with Descript, Veed & Canva. These tools offer powerful AI-driven features for seamless video production. 2️⃣

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

A great dashboard answers one key question: “Now what?” Because data without action is just noise. #DataAnalytics #BusinessIntelligence #WomenInTech

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

What’s the one tool you can’t live without as an analyst? I’ll go first: Power BI + Excel combo. Game-changing. #AnalyticsTwitter #SQLCommunity #DashboardDesign

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

Just wrapped up a Power BI dashboard showing employee attrition patterns—visuals tell stories data alone can’t. Want a sneak peek? #PowerBI #HRAnalytics

AnalystUnyime (@datadetective_u) 's Twitter Profile Photo

3 quick Excel tips every data analyst should know: 1. Ctrl + Shift + L = Filters 2. ALT + E + S + V = Paste Values 3. F4 = Repeat last action #ExcelTips #DataAnalytics

Ezekiel (@ezekiel_aleke) 's Twitter Profile Photo

As a Data Analyst. There’s 90% chance that you’ll need this in your job. Especially those in finance sector. Learn it now:

As a Data Analyst.

There’s 90% chance that you’ll need this in your job.

Especially those in finance sector.

Learn it now: