Trending Feed
12 posts loaded

Day 3: Importing Data into Power BI (+ importing data from the web!) #dataanalyst #dataanalysis #dataanalytics #powerbi #powerquery

Comment “project” for my full video that breaks each of these projects down in detail with examples from my own work. If you’re using the Titanic, Iris, or COVID-19 dataset for data analytics projects, STOP NOW! These are so boring and over used and scream “newbie”. You can find way more interesting datasets for FREE on public data sites and you can even make your own using ChatGPT or Claude! Here are the 3 types of projects you need: ↳Exploratory Data Analysis (EDA): Exploring a dataset to uncover insights through descriptive statistics (averages, ranges, distributions) and data visualization, including analyzing relationships between variables ↳Full Stack Data Analytics Project: An end-to-end project that covers the entire data pipeline: wrangling data from a database, cleaning and transforming it. It demonstrates proficiency across multiple tools, not just one. ↳Funnel Analysis: Tracking users or items move from point A to point B, and how many make it through each step in between. This demonstrates a deeper level of business thinking by analyzing the process from beginning to end and providing actionable recommendations to improve it Save this video for later + send to a data friend!

Stop suffering in silence. These tools will level up your analysis game! Which one’s your fav? Comment down👇🏻 #dataanalysis #phdlife #statsmadeeasy #dataanalysis #rstats #prism #researchtools #scientificreels #academiaa #phd #phdwithanjali #juliusai @try_julius.ai

Repost to share with friends ♻️ Here’s how to become a data analyst in 2026 and beyond? 📈 The original video was 5 minutes long and I had to cut it down to 3 minutes because instagram. One part that got cut off was the job market. Should I post a part 2? what are other skills that would you add to the list?? #dataanalysis #dataanalyst #sql #python

Visualize your data in 4 simple steps using Power BI 🚀 1️⃣ Get Data – connect and import data from multiple sources 2️⃣ Data Modeling – build relationships so your data works together 3️⃣ Data Transformation – clean and shape your data for analysis 4️⃣ Visualization – turn insights into interactive dashboards Save this for later, share with your team, and follow for more Power BI tips! 📊🔥 #PowerBI #DataAnalytics #BusinessIntelligence

5 Data Analyst Projects That Can Get You Hired (With Tutorials) Most portfolios are filled with the same boring projects everyone else does. These five stand out because they solve real business problems and show recruiters you can think, not just code. Here are the 5 projects: 1. Sales Data Dashboard Build an interactive dashboard analyzing sales trends, revenue by region, and product performance using Excel, Power BI, or Tableau 📎 Tutorial: https://www.youtube.com/watch?v=fZn83JRt4Nk 2. Customer Segmentation Analysis Use Python and K-means clustering to segment customers based on behavior and create targeted marketing strategies 📎 Tutorial: https://365datascience.com/tutorials/python-tutorials/build-customer-segmentation-models/ 3. SQL Database Analysis Query and analyze customer purchase patterns, retention rates, and lifetime value using SQL 📎 Tutorial: https://www.geeksforgeeks.org/sql/customer-behavior-analysis-in-sql/ 4. Time Series Forecasting Predict future sales or trends using Python with ARIMA or Prophet models to demonstrate forecasting skills 📎 Tutorial: https://www.digitalocean.com/community/tutorials/a-guide-to-time-series-forecasting-with-prophet-in-python-3 5. A/B Testing Framework Design and analyze an A/B test to optimize website conversions or marketing campaigns using statistical testing 📎 Tutorial: https://www.kdnuggets.com/a-complete-guide-to-a-b-testing-in-python These aren't just tutorials you follow. They're projects that demonstrate real business impact, clean code, and the ability to communicate insights. Recruiters check GitHub. Make sure yours has well-documented projects that show practical impact, not just technical skills. Save this and start building. [dataanalyst, data, analyst, analytics, portfolio, projects, SQL, python, powerbi, tableau, excel, dashboard, visualization, forecasting, machinelearning, career, job, hired, beginner, tutorial, github, skills, business, insights, statistics, segmentation, testing, resume] #dataanalyst #dataanalysis #portfolio #projects

I won’t be mad if you copy this entire roadmap… #dataanalyst #dataanalysis #dataanalytics #data #analyst #techjobs #breakintotech #wfh #workfromhome #wfhjobs #remotejobs #remotework #excel #sql #tableau #python

🔥 Make your Power BI reports look like real apps! In this video, I’ll show you how to create a modern navigation bar — first with gradient colors, then with icon-based navigation 👇 🎨 Clean. ⚡ Interactive. 💡 Perfect for dashboards that wow your audience. Save this for later & follow @powerbiforeveryone for more design tricks 💛 #PowerBI #PowerBIDesign #PowerBITips #DataVisualization #DashboardDesign #PowerBIForEveryone #DataAnalytics #MicrosoftPowerBI

how I analyze data as a Business Analyst at Spotify! Spotify商業分析師如何分析數據? ft. @tableausoftware #womenintech #businessanalyst #dataanalyst #gendata #datafam #spotify

The best projects serve a real use case Comment “data” for all the links and project descriptions #tech #data #datascience #ml #explore

Here’s thing i wish i knew before becoming a data analyst 📊 1. SQL is your best friend — it gets you through 80% of the work. 2. Excel isn’t basic — pivot tables & formulas are used daily. 3. Visualization tools (Tableau/Power BI) make you stand out. 4. Communication > technical sometimes — if you can’t explain insights, they don’t matter. 5. You don’t need 100 certifications — projects & practice speak louder. 6. Most of your time is data cleaning — not fancy dashboards. 7. Business understanding is key — knowing why the data matters is more valuable than just coding. 8. Networking gets you jobs faster than applications — LinkedIn visibility + projects > sending 500 resumes [data analytics,data analyst, corporate, data]
Top Creators
Most active in #bi-data-analysis-techniques
Reels Graph Intelligence.
Advanced mapping of high-affinity Instagram Reels semantic patterns identified within the #bi-data-analysis-techniques ecosystem.
Strategic Implementation
Our semantic engine has identified these specific pattern clusters as high-affinity matches for #bi-data-analysis-techniques. Integrated usage of #bi-data-analysis-techniques with strategic Reels tags like #data analysis and #biing is statistically linked to a significant increase in initial Reels discovery velocity.
In-Depth Hashtag Analysis: #bi-data-analysis-techniques
Expert Review • June 4, 2026 • Based on 12 Reels
Executive Overview
#bi-data-analysis-techniques is an actively used Instagram hashtag. Across the 12 trending reels analyzed on this page, the content has accumulated a combined total of 5,734,755 views— demonstrating strong content velocity within this content vertical. The top creator ecosystem features 8 notable accounts, led by @marytheanalyst with 1,862,262 total views. The hashtag's semantic network includes 6 related keywords such as #data analysis, #biing, #analysis data, indicating its position within a broader content cluster.
Viewership & Reach Analysis
The 12 reels in this dataset have generated a combined 5,734,755 views, translating to an average of 477,896 views per reel. This strong average viewership suggests healthy algorithmic distribution. Reels using this hashtag are reliably reaching audiences interested in this niche.
The highest-performing reel in this dataset received 1,807,130 views. This viral outlier performance is 378% of the average reel performance in this set. This significant gap between the top performer and the average highlights the "viral lottery" nature of this hashtag — breakout hits can achieve massive scale.
Content Overview & Top Creators
The #bi-data-analysis-techniques ecosystem is dominated by short-form video content (Reels), aligning with Instagram's algorithmic preference for video-first distribution. There are 8 distinct accounts contributing to the trending feed. The top creator, @marytheanalyst, has contributed 2 reels with a total viewership of 1,862,262. The top three creators — @marytheanalyst, @aanooook, and @sundaskhalidd — together account for 73.4% of the total views in this dataset. The semantic network of #bi-data-analysis-techniques extends across 6 related hashtags, including #data analysis, #biing, #analysis data, #data analysi. Creators often use these tags together to reach overlapping audiences.
Discoverability & Reach Potential
The discoverability metrics for #bi-data-analysis-techniques indicate an active content ecosystem. The average of 477,896 views per reel demonstrates consistent audience reach. For creators using #bi-data-analysis-techniques, posting consistently with trending audio and relevant angles will help you get noticed.
Analyst Verdict
#bi-data-analysis-techniques demonstrates the hallmarks of a well-performing Instagram hashtag. With an average of 477,896 views per reel, the viewership metrics position this hashtag as a reliable reach driver. Creators like @marytheanalyst and @aanooook are leading the charge, setting viewership benchmarks for the community.
Frequently Asked Questions
Everything about #bi-data-analysis-techniques on Instagram
Global Reels Trends
Explore high-velocity Instagram Reels hashtags currently shaping global discovery.











