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People keep asking me where I learn stuff from. Honestly, YouTube is still one of the best free universities if you follow the right people. My go-to channels: DSA @takeUforward @KunalKushwaha @codestorywithmik System Design @ByteByteGo @gkcs @hnasr DevOps @TechWorldwithNana @AbhishekVeerarma Backend @hnasr @ConceptAndCoding @TECHSCHOOLGURU Frontend @WebDevSimplified @NetNinja @traversymedia Java @Telusko DBMS / OS / CN @GateSmashers @nesoacademy Data Engineering @DataWithDanny @SeattleDataGuy @DataTalksClub Databricks / Spark @Databricks @RockTheJVM Snowflake @SnowflakeDB AI / ML @AndrejKarpathy @statquest @deeplearningai GenAI @LangChainAI @Weights_Biases No course selling. No affiliate links. No sponsorship. Just channels that have genuinely helped thousands of engineers learn and get better. Drop your favorite ones below. I'm always looking for new gems.
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๐Ÿด๐Ÿณ๐Ÿฌ,๐Ÿฌ๐Ÿฌ๐Ÿฌ ๐—ฒ๐—ป๐—ด๐—ฎ๐—ด๐—ฒ๐—บ๐—ฒ๐—ป๐˜๐˜€. But only 0.11% of viewers became followers. Thatโ€™s what I found when analyzing a year of a clientโ€™s social media data. They had posted 450 times and generated 13.2 million impressions. On the surface, everything looked great. But when I broke the data down, most of the performance came from just a few patterns. ๐—ฃ๐—น๐—ฎ๐˜๐—ณ๐—ผ๐—ฟ๐—บ โ†’ TikTok engagement rate: 8.97% โ†’ Facebook engagement rate: 3.46% Yet they were posting equally on both. ๐—™๐—ผ๐—ฟ๐—บ๐—ฎ๐˜ โ†’ Video posts averaged 9.35% engagement โ†’ Text posts averaged 2.85% But both were treated the same in the content calendar. ๐—ง๐—ถ๐—บ๐—ถ๐—ป๐—ด โ†’ Afternoon posts averaged 7.47% engagement โ†’ Midday posts averaged 5.53% Posting times were mostly random. Same team. Same budget. Very different results depending on where, what, and when they posted. But the biggest signal was still that 0.11% follower conversion rate. People were engaging with the content. They just werenโ€™t staying. So the recommendations were straightforward: โ†’ Focus more effort on TikTok โ†’ Make video the default format โ†’ Prioritize afternoon posting โ†’ Boost posts that are already performing Small changes. Much better return. This is the guided project for Cohort 8 of Data with Danny โ€” built entirely in @msexcel . No BI tools. Just clean data and the right questions. #DataAnalytics #SocialMediaAnalytics #Excel #DataWithDanny #Datafam
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Been a while, I joined @iam_daniiell's live class. Today we talked about PowerPoint presentations. We talked about the CRAP design principle. I'm so alive whenever anything about design comes up. ๐Ÿ™‚ #Cohort8 #DatawithDanny #DataAnalytics
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๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿด - ๐—”๐—ด๐—ด๐—ฟ๐—ฒ๐—ด๐—ฎ๐˜๐—ฒ ๐—™๐˜‚๐—ป๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐˜€. Today we dove deep into what actually makes analysts valuable: the ability to summarize data and extract insights. We covered aggregate functions in Excel. Not just what they do, but WHY they matter. ๐—ง๐—ต๐—ฒ ๐—•๐—ฎ๐˜€๐—ถ๐—ฐ๐˜€: โ†’ SUM - Total values โ†’ SUMPRODUCT - Multiplying and summing arrays โ†’ PRODUCT - Multiplying values โ†’ COUNT, COUNTA, COUNTBLANK - Counting numbers, non-empty cells, and blanks โ†’ MIN and MAX - Finding extremes โ†’ AVERAGE - Central tendency These arenโ€™t just formulas. Theyโ€™re how you answer business questions: โ€œWhatโ€™s our total revenue?โ€ โ€œHow many orders did we get?โ€ โ€œWhatโ€™s the average order value?โ€ ๐—–๐—ผ๐—ป๐—ฑ๐—ถ๐˜๐—ถ๐—ผ๐—ป๐—ฎ๐—น ๐—”๐—ด๐—ด๐—ฟ๐—ฒ๐—ด๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€: Then we moved to the power tools: โ†’ COUNTIF - Count cells that meet a condition โ†’ SUMIF - Sum cells that meet a condition โ†’ SUMIFS - Sum with multiple conditions This is where you go from โ€œWhatโ€™s the total?โ€ to โ€œWhatโ€™s the total for THIS specific segment?โ€ ๐—ช๐—ถ๐—น๐—ฑ๐—ฐ๐—ฎ๐—ฟ๐—ฑ๐˜€: We introduced wildcards (* and ?) for pattern matching. Now students can count all customers whose names start with โ€œJohnโ€ or sum all orders containing โ€œPizzaโ€ in the description. ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐˜‚๐—บ๐—บ๐—ฎ๐—ฟ๐—ถ๐˜€๐—ฎ๐˜๐—ถ๐—ผ๐—ป: Finally, we covered PIVOTBY and GROUPBY - dynamic array functions that let you summarize data without pivot tables. Students learned how to group sales by region, category, or time period and calculate totals, averages, or counts instantly. ๐—ง๐—ต๐—ฒ ๐—ฟ๐—ฒ๐˜€๐˜‚๐—น๐˜? Students went from โ€œI can add numbers in Excelโ€ to โ€œI can analyze datasets and answer specific business questions.โ€ Theyโ€™re not just using formulas. Theyโ€™re thinking like analysts. This is what happens when you teach concepts, not just syntax. #DataAnalysis #Excel #DataWithDanny #Datafam
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๐—–๐—น๐—ฎ๐˜€๐˜€ ๐Ÿณ & ๐Ÿด ๐˜„๐—ถ๐˜๐—ต ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿณ: ๐—–๐—”๐—ฆ๐—˜ ๐—ฆ๐˜๐—ฎ๐˜๐—ฒ๐—บ๐—ฒ๐—ป๐˜๐˜€. Today we covered one of the most powerful tools in SQL: CASE statements. This is SQLโ€™s IF-THEN-ELSE. Itโ€™s what separates analysts who can query data from analysts who can solve business problems. ๐—ช๐—ต๐—ฎ๐˜ ๐˜„๐—ฒ ๐—ฐ๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐—ฒ๐—ฑ: โ†’ Simple CASE vs Searched CASE (and when to use each) โ†’ Data categorization (turning raw values into business categories) โ†’ Binary and multi-tier classification โ†’ Handling NULL values properly โ†’ Using CASE in WHERE clauses for complex filtering โ†’ Nested CASE statements (decision trees) โ†’ Multi-column logic (combining multiple conditions) โ†’ Conditional aggregation (the real power move) โ†’ Building executive dashboards in one query ๐—ฅ๐—ฒ๐—ฎ๐—น-๐˜„๐—ผ๐—ฟ๐—น๐—ฑ ๐—ฒ๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ๐˜€: Students learned how to: โ†’ Categorize delivery distances (far, moderate, nearby, very close) โ†’ Calculate late delivery percentages โ†’ Split revenue by customer type โ†’ Analyze delivery performance by time slot โ†’ Build multi-metric dashboards in a single query By the end, they were writing queries like this: SELECT CAST(100.0 * SUM(CASE WHEN delivery_time_minutes > 40 THEN 1 ELSE 0 END) / COUNT(*) AS DECIMAL(10,2)) AS Late_percentage, SUM(CASE WHEN is_repeat_customer = 1 THEN total_amount ELSE 0 END) AS Repeat_customer_revenue FROM Food_Delivery This is the SQL that actually drives business decisions. Students who couldnโ€™t write a CASE statement two hours ago are now building conditional logic that answers real business questions. The growth is insane. #SQL #DataAnalysis #DataWithDanny #Datafam
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๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿด ๐—ธ๐—ถ๐—ฐ๐—ธ๐—ฒ๐—ฑ ๐—ผ๐—ณ๐—ณ ๐˜๐—ต๐—ถ๐˜€ ๐˜„๐—ฒ๐—ฒ๐—ธ๐—ฒ๐—ป๐—ฑ. We didnโ€™t jump straight into tools. We laid the foundation first. ๐—ช๐—ต๐—ฎ๐˜ ๐˜„๐—ฒ ๐—ฐ๐—ผ๐˜ƒ๐—ฒ๐—ฟ๐—ฒ๐—ฑ: โ†’ What data actually is - types, structure, and sources โ†’ What data analysis means and what analysts are responsible for โ†’ The different types of analysis (descriptive, diagnostic, predictive, prescriptive) โ†’ The analysis lifecycle - from question to insight โ†’ Challenges analysts face in the real world โ†’ The tools youโ€™ll need to solve problems Then we moved into Excel. Students learned data handling techniques: โ†’ Sort and filter โ†’ Data validation โ†’ Conditional formatting Then we introduced functions and formulas. This is how you build analysts who actually understand what theyโ€™re doing, not just people who know how to click buttons. Foundation first. Tools second. Excited to watch this cohort grow. #DataAnalysis #Excel #DataWithDanny #Datafam
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๐—š๐—ผ๐—ผ๐—ฑ ๐—บ๐—ผ๐—ฟ๐—ป๐—ถ๐—ป๐—ด, ๐—ฒ๐˜ƒ๐—ฒ๐—ฟ๐˜†๐—ผ๐—ป๐—ฒ We just wrapped up our Excel project presentations with Cohort 7. Students were grouped to work on real-world Excel projects. But this wasnโ€™t just about formulas and charts. It was about building the skills that actually matter in the workplace. ๐—ช๐—ต๐—ฎ๐˜ ๐˜๐—ต๐—ฒ๐˜† ๐—น๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ฒ๐—ฑ: โœ… Teamwork & Collaboration Working together, sharing ideas, and solving problems as a team. โœ… Time Management & Deadlines Planning tasks, staying organized, and delivering on time. โœ… Presentation Skills Creating PowerPoint decks and confidently presenting their work to judges. โœ… Product Documentation Documenting their projects clearly and professionally, just like in real companies. These projects pushed students beyond technical skills and into professional readiness. This is what happens when you combine real projects with structure and accountability. Screenshots of their work below. ๐Ÿ‘‡ Thank you @thegoodanalysts .. for gracing this event. Which project was your favorite and why? #DataAnalysis #Excel #DataWithDanny #Datafam
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๐—–๐—น๐—ฎ๐˜€๐˜€ ๐Ÿฑ & ๐Ÿฒ ๐˜„๐—ถ๐˜๐—ต ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿณ: ๐——๐—ค๐—Ÿ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ๐˜†. After teaching students how to design databases (DDL) and populate them (DML), we dove deep into the part everyone actually uses daily: querying data. DQL - Data Query Language. This is where the magic happens. ๐—ข๐—ฝ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ Students learned how to filter and find exactly what they need: โ†’ Arithmetic operators ( , -, *, /) - calculating discounts, totals, profit margins โ†’ Comparison operators (=, >, <, >=, <=) - finding patients above a certain age, bills over a threshold โ†’ Logical operators (AND, OR, NOT) - combining multiple conditions โ†’ LIKE - searching for patterns in names, emails, addresses โ†’ IN & BETWEEN - filtering ranges and specific lists โ†’ IS NULL / IS NOT NULL - finding missing data This isnโ€™t theory. Students used these to answer real questions: โ€œShow me all patients over 45 with unpaid billsโ€ or โ€œFind all visits scheduled this week in the Cardiology department.โ€ ๐—”๐—ด๐—ด๐—ฟ๐—ฒ๐—ด๐—ฎ๐˜๐—ฒ ๐—™๐˜‚๐—ป๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐˜€ Then we moved into summary statistics: โ†’ SUM - total revenue, total payments โ†’ AVG - average consultation fee, average bill amount โ†’ COUNT - number of visits, number of patients โ†’ MIN & MAX - lowest and highest values They learned GROUP BY to break down data by categories: โ€œWhatโ€™s the total revenue per department?โ€ or โ€œHow many patients visited each doctor?โ€ ๐—›๐—”๐—ฉ๐—œ๐—ก๐—š ๐—–๐—น๐—ฎ๐˜‚๐˜€๐—ฒ WHERE filters rows before grouping. HAVING filters groups after aggregation. Students learned when to use each: โ€œShow me departments with more than 5 doctorsโ€ or โ€œWhich doctors have average consultation fees above โ‚ฆ30,000?โ€ This is where beginners usually get stuck. Not anymore. ๐—ง๐—ฒ๐˜…๐˜ ๐—™๐˜‚๐—ป๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐˜€ Finally, we covered string manipulation: โ†’ CONCAT - combining first and last names โ†’ UPPER/LOWER - standardizing text โ†’ TRIM - cleaning up messy data โ†’ SUBSTRING - extracting parts of text โ†’ LEN - counting characters Real-world use: cleaning patient names, formatting phone numbers, extracting area codes. ๐—ง๐—ต๐—ฒ ๐—ฟ๐—ฒ๐˜€๐˜‚๐—น๐˜? Students went from โ€œHow do I select data?โ€ to writing complex queries that answer actual business questions. Theyโ€™re not just running SELECT * anymore. Theyโ€™re filtering 20,000 patient records to find exactly what matters. Theyโ€™re calculating revenue by department. Theyโ€™re identifying trends in visit patterns. Theyโ€™re solving real problems. This is what happens when you combine structure, real projects, and hands-on practice. Cohort 8 starts this sunday. Last chance to join. ๐Ÿ”— selar.com/7q7p1y224k ๐Ÿ“ฑ 234 911 028 9203 #SQL #DataAnalysis #DataWithDanny #Datafam
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๐—ช๐—ฒโ€™๐—ฟ๐—ฒ ๐—ธ๐—ถ๐—ฐ๐—ธ๐—ถ๐—ป๐—ด ๐—ผ๐—ณ๐—ณ ๐˜๐—ต๐—ถ๐˜€ ๐˜„๐—ฒ๐—ฒ๐—ธ๐—ฒ๐—ป๐—ฑ. Data with Danny - Cohort 8 starts Friday, January 30th. If youโ€™ve been thinking about it, nowโ€™s the time to decide. This is your last chance to join a structured 4-month program that takes you from complete beginner to job-ready. Excel โ€ข SQL โ€ข Python โ€ข Power BI โ€ข Statistics โœ“ 8 portfolio projects โœ“ 1-on-1 mentorship โœ“ Certificate of completion โœ“ Structured learning path ๐Ÿ“… Starts: Friday, January 30th โฐ Classes: Fri-Sun, 7-9 PM WAT ๐Ÿ’ฐ โ‚ฆ80,000 | $80 Registration closes soon. ๐Ÿ”— selar.com/7q7p1y224k ๐Ÿ“ฑ 234 911 028 9203 Donโ€™t let another cohort pass you by. Screenshots of past student projects below ๐Ÿ‘‡ #DataAnalysis #SQL #Python #PowerBI #DataWithDanny #Datafam
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๐—–๐—น๐—ฎ๐˜€๐˜€ ๐Ÿฏ & ๐Ÿฐ ๐˜„๐—ถ๐˜๐—ต ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿณ: ๐——๐— ๐—Ÿ ๐— ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ๐˜†. Two full sessions. One focus: teaching students how to actually work with data in SQL. We built a complete healthcare clinic database from scratch - patients, doctors, visits, diagnoses, bills, payments. Real tables. Real relationships. Real business logic. Then we dove deep into DML (Data Manipulation Language). ๐—œ๐—ก๐—ฆ๐—˜๐—ฅ๐—ง - ๐—”๐—ฑ๐—ฑ๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ Students learned how to populate databases with real data: โ€ข Single row inserts vs bulk inserts โ€ข Inserting 20 patients with realistic Nigerian names and details โ€ข Adding 13 doctors across 6 departments โ€ข Creating 24 visits with different statuses (completed, scheduled, cancelled) They werenโ€™t just copying syntax. They understood WHY you structure inserts this way. ๐—จ๐—ฃ๐——๐—”๐—ง๐—˜ - ๐— ๐—ผ๐—ฑ๐—ถ๐—ณ๐˜†๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ This is where it got interesting. We taught them how to: โ€ข Update a patientโ€™s phone number (single column) โ€ข Mark visits as completed and add clinical notes (multiple columns) โ€ข Apply 10% senior citizen discounts automatically using JOINs and calculations โ€ข Batch update bills to โ€œOverdueโ€ status based on due dates Students learned the #1 rule: ALWAYS preview with SELECT before you UPDATE. Because one mistake here can change thousands of records. ๐——๐—˜๐—Ÿ๐—˜๐—ง๐—˜ - ๐—ฅ๐—ฒ๐—บ๐—ผ๐˜ƒ๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ We covered the difference between soft delete and hard delete. Soft delete: Mark a record as inactive (IsActive = 0). Data stays in the database. You can recover it. This is what most businesses use. Hard delete: Permanently remove the record. Gone forever. Use with extreme caution. Students practiced both. They learned about foreign key constraints and why you canโ€™t just delete a parent record when child records exist. ๐— ๐—˜๐—ฅ๐—š๐—˜ - ๐—ฆ๐˜†๐—ป๐—ฐ๐—ต๐—ฟ๐—ผ๐—ป๐—ถ๐˜‡๐—ถ๐—ป๐—ด ๐——๐—ฎ๐˜๐—ฎ This is advanced stuff. MERGE lets you INSERT or UPDATE in one operation (also called UPSERT). We created a staging table with department updates from an โ€œexternal system.โ€ Then used MERGE to: โ€ข Update existing departments if they changed โ€ข Insert new departments if they didnโ€™t exist This is exactly how data warehouses and ETL processes work in real companies. ๐—ง๐—ต๐—ฒ ๐—ฟ๐—ฒ๐˜€๐˜‚๐—น๐˜? Students who couldnโ€™t spell โ€œDMLโ€ two weeks ago are now writing queries that handle real business logic. Theyโ€™re applying discounts based on age calculations. Theyโ€™re managing visit workflows. Theyโ€™re synchronizing data between systems. Theyโ€™re thinking like analysts, not just following tutorials. This is what structured learning with real projects looks like. If you want to learn SQL like this, Cohort 8 starts January 30th. Registration: selar.com/7q7p1y224k WhatsApp: 234 911 028 9203 #SQL #DataAnalysis #DataWithDanny #Datafam #DML
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๐—๐˜‚๐˜€๐˜ ๐˜„๐—ฟ๐—ฎ๐—ฝ๐—ฝ๐—ฒ๐—ฑ ๐—–๐—น๐—ฎ๐˜€๐˜€ ๐Ÿฎ ๐˜„๐—ถ๐˜๐—ต ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿณ. They went from โ€œWhatโ€™s an entity?โ€ to building production-ready databases. In one class. ๐—ช๐—ต๐—ฎ๐˜ ๐˜๐—ต๐—ฒ๐˜† ๐—ฐ๐—ฎ๐—ป ๐—ป๐—ผ๐˜„ ๐—ฑ๐—ผ: โ†’ Design 7-table normalized schemas โ†’ Write production DDL โ†’ Create business intelligence views โ†’ Optimize with strategic indexes The speed of growth is insane. Screenshots below. ๐Ÿ‘‡ This is what happens when you have structure, mentorship, and real projects. Cohort 8 starts January 30th. Registration is still open. ๐Ÿ”— Register: selar.com/7q7p1y224k ๐—™๐—ผ๐—ฟ ๐—บ๐—ผ๐—ฟ๐—ฒ ๐—ถ๐—ป๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐˜๐—ถ๐—ผ๐—ป: ๐Ÿ“ง datawithdany@gmail.com ๐Ÿ“ฑ WhatsApp: 234 911 028 9203 #SQL #DataAnalysis #DataWithDanny #Datafam
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๐—ฅ๐—ฒ๐—ด๐—ถ๐˜€๐˜๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ถ๐˜€ ๐˜€๐˜๐—ถ๐—น๐—น ๐—ผ๐—ฝ๐—ฒ๐—ป ๐—ณ๐—ผ๐—ฟ ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿด. Data with Danny starts January 30th. Excel โ€ข SQL โ€ข Python โ€ข Power BI โ€ข Statistics โ€ข Figma โ€ข PowerPoint Whatโ€™s included: โ€ข 8 real-world projects โ€ข 1-on-1 mentorship โ€ข Certificate of completion โ€ข World-class resources ๐Ÿ“… Classes: Friday-Sunday, 7-9 PM WAT ๐Ÿ’ฐ โ‚ฆ80,000 (Nigerians) | $80 (International) Special offer: Pay 50% now, balance later. ๐Ÿ”— selar.com/7q7p1y224k ๐Ÿ“ฑ 234 911 028 9203 Email datawithdany@gmail.com #DataAnalysis #SQL #Python #PowerBI #DataWithDanny #Datafam
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Unlike @ManUtd , ๐Ÿ’€ Datawithdanny Cohort 7 Is back for 2026 Weโ€™re cooking with SQL #Datafam
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If youโ€™re interested in learning all of this and how to use them daily, then enrol in Datawithdanny Cohort 8, it is part of our 4 months program selar.com/7q7p1y224k

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๐—š๐—ผ๐—ผ๐—ฑ ๐—บ๐—ผ๐—ฟ๐—ป๐—ถ๐—ป๐—ด ๐—ด๐˜‚๐˜†๐˜€. Today, I wanna tell you the next step after understanding the concepts of data analysis. And thatโ€™s to learn Excel. Why? Because itโ€™s really easy and very much available. Hereโ€™s what you need to learn to stand out: ๐——๐—ถ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐˜ ๐˜๐˜†๐—ฝ๐—ฒ๐˜€ ๐—ผ๐—ณ ๐—ฐ๐—ฒ๐—น๐—น ๐—ฟ๐—ฒ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐—ฐ๐—ถ๐—ป๐—ด Relative, absolute, mixed - understand when to use each. ๐——๐—ฎ๐˜๐—ฎ ๐—ต๐—ฎ๐—ป๐—ฑ๐—น๐—ถ๐—ป๐—ด ๐˜๐—ฒ๐—ฐ๐—ต๐—ป๐—ถ๐—พ๐˜‚๐—ฒ๐˜€ โ†’ Sort โ†’ Filters โ†’ Conditional formatting โ†’ Data validation ๐—™๐˜‚๐—ป๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐˜€ โ†’ Aggregate functions (SUM, AVERAGE, COUNT for summarization) โ†’ Text and date functions (for data cleaning) โ†’ Conditional functions and logical operators (IF, AND, OR) โ†’ Lookups (XLOOKUP and INDEX-MATCH) โ†’ Error handling functions (IFERROR, IFNA) ๐—ช๐—ต๐—ฎ๐˜-๐—œ๐—ณ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐—ถ๐˜€ Scenario planning, data tables, goal seek. ๐—”๐—ฝ๐—ฝ๐—น๐—ถ๐—ฒ๐—ฑ ๐—ฆ๐˜๐—ฎ๐˜๐—ถ๐˜€๐˜๐—ถ๐—ฐ๐˜€ โ†’ Data Analysis ToolPak โ†’ Correlation โ†’ Regression ๐—˜๐—ง๐—Ÿ ๐—ฝ๐—ฟ๐—ผ๐—ฐ๐—ฒ๐˜€๐˜€ ๐˜‚๐˜€๐—ถ๐—ป๐—ด ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—ค๐˜‚๐—ฒ๐—ฟ๐˜† Extract, transform, load - the foundation of data preparation. ๐——๐—ฎ๐˜๐—ฎ ๐—บ๐—ผ๐—ฑ๐—ฒ๐—น๐—ถ๐—ป๐—ด ๐—ฎ๐—ป๐—ฑ ๐—ป๐—ผ๐—ฟ๐—บ๐—ฎ๐—น๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐˜‚๐˜€๐—ถ๐—ป๐—ด ๐—ฃ๐—ผ๐˜„๐—ฒ๐—ฟ ๐—ฃ๐—ถ๐˜ƒ๐—ผ๐˜ Building relationships, creating data models. ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐—ถ๐˜€ ๐˜‚๐˜€๐—ถ๐—ป๐—ด ๐—ฃ๐—ถ๐˜ƒ๐—ผ๐˜ ๐—ง๐—ฎ๐—ฏ๐—น๐—ฒ๐˜€ ๐—ฎ๐—ป๐—ฑ ๐——๐—”๐—ซ Summarize, analyze, create calculated measures. ๐——๐—ฎ๐˜๐—ฎ ๐˜ƒ๐—ถ๐˜€๐˜‚๐—ฎ๐—น๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐˜‚๐˜€๐—ถ๐—ป๐—ด ๐—ฃ๐—ถ๐˜ƒ๐—ผ๐˜ ๐—–๐—ต๐—ฎ๐—ฟ๐˜๐˜€ Turn your analysis into visual stories. You can learn all this on YouTube for free. Or if you need a structured guide to learn all these and more, enroll for Data with Danny Cohort 8. ๐Ÿ”— selar.com/7q7p1y224k #DataAnalysis #DataEngineering #Excel #LearningInPublic #DataWithDanny #Datafam
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๐—š๐—ผ๐—ผ๐—ฑ ๐—บ๐—ผ๐—ฟ๐—ป๐—ถ๐—ป๐—ด ๐—ด๐˜‚๐˜†๐˜€. Registration still ongoing for Cohort 8. I know yโ€™all love dashboards, so here are some from previous students - as their ๐—ณ๐—ถ๐—ฟ๐˜€๐˜ ๐—ฝ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜๐˜€. ๐Ÿ‘‡ These were built with beginners who started exactly where you are now. ๐—”๐˜ ๐——๐—ฎ๐˜๐—ฎ ๐˜„๐—ถ๐˜๐—ต ๐——๐—ฎ๐—ป๐—ป๐˜†, ๐˜†๐—ผ๐˜‚โ€™๐—ฟ๐—ฒ ๐—น๐—ฒ๐—ฎ๐—ฟ๐—ป๐—ถ๐—ป๐—ด ๐—ณ๐—ฟ๐—ผ๐—บ ๐˜€๐—ผ๐—บ๐—ฒ๐—ผ๐—ป๐—ฒ ๐˜„๐—ต๐—ผโ€™๐˜€ ๐˜๐—ฎ๐˜‚๐—ด๐—ต๐˜ ๐—ผ๐˜ƒ๐—ฒ๐—ฟ ๐Ÿญ,๐Ÿฌ๐Ÿฌ๐Ÿฌ ๐˜€๐˜๐˜‚๐—ฑ๐—ฒ๐—ป๐˜๐˜€. We dive deep into: โ†’ Excel (dashboards, Power Query, Power Pivot, advanced functions) โ†’ SQL (databases, queries, data manipulation) โ†’ Power BI (interactive reports, DAX, visualization) โ†’ Python (data analysis, automation) โ†’ Statistics, Figma, PowerPoint โ†’ And a whole lot more Not just tutorials. Real, portfolio-worthy projects. ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿด ๐˜€๐˜๐—ฎ๐—ฟ๐˜๐˜€ ๐—๐—ฎ๐—ป๐˜‚๐—ฎ๐—ฟ๐˜† ๐Ÿฏ๐Ÿฌ๐˜๐—ต. 4 months. Beginner to job-ready. ๐Ÿ“… Classes: Friday to Sunday, 7-9 PM WAT ๐Ÿ’ฐ โ‚ฆ80,000 (Nigerians) | $80 (International) ๐Ÿ”— Register: selar.com/7q7p1y224k ๐Ÿ“ง datawithdany@gmail.com ๐Ÿ“ฑ WhatsApp: 234 911 028 9203 Letโ€™s build together. ๐Ÿ’ช #DataAnalysis #DataEngineering #Excel #PowerBI #SQL #DataWithDanny #Datafam
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๐—›๐—ฎ๐—ฝ๐—ฝ๐˜† ๐—ก๐—ฒ๐˜„ ๐—ฌ๐—ฒ๐—ฎ๐—ฟ, #๐——๐—ฎ๐˜๐—ฎ๐—ณ๐—ฎ๐—บ! ๐ŸŽ‰ Welcome to 2026. If youโ€™re ready to finally start your data analytics journey - weโ€™re starting in 30 days. โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” ๐——๐—ฎ๐˜๐—ฎ ๐˜„๐—ถ๐˜๐—ต ๐——๐—ฎ๐—ป๐—ป๐˜† - ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿด ๐—ฆ๐˜๐—ฎ๐—ฟ๐˜๐˜€ ๐—๐—ฎ๐—ป๐˜‚๐—ฎ๐—ฟ๐˜† ๐Ÿฏ๐Ÿฌ๐˜๐—ต, ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ 4 months. Beginner to job-ready. ๐—ช๐—ต๐—ฎ๐˜ ๐˜†๐—ผ๐˜‚โ€™๐—น๐—น ๐—บ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ: ๐—ช๐—ต๐—ฎ๐˜ ๐˜†๐—ผ๐˜‚โ€™๐—น๐—น ๐—ด๐—ฎ๐—ถ๐—ป: โ€ข Excel โœ“ 8 real-world projects โ€ข SQL โœ“ 1-on-1 mentorship โ€ข Python โœ“ Certificate of completion โ€ข Power BI โœ“ World-class resources โ€ข Figma โ€ข PowerPoint โ€ข Statistics โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” ๐Ÿ“… ๐—ฆ๐˜๐—ฎ๐—ฟ๐˜ ๐——๐—ฎ๐˜๐—ฒ: January 30th, 2026 โฐ ๐—–๐—น๐—ฎ๐˜€๐˜€๐—ฒ๐˜€: Friday to Sunday, 7-9 PM WAT ๐Ÿ’ฐ ๐—œ๐—ป๐˜ƒ๐—ฒ๐˜€๐˜๐—บ๐—ฒ๐—ป๐˜: โ‚ฆ80,000 (Nigerians) ๐Ÿ‡ณ๐Ÿ‡ฌ $80 (International) ๐ŸŒ โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” If youโ€™re serious about learning data analytics this year, weโ€™d love to have you. ๐Ÿ”— Register: selar.com/7q7p1y224k ๐—™๐—ผ๐—ฟ ๐—บ๐—ผ๐—ฟ๐—ฒ ๐—ถ๐—ป๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐˜๐—ถ๐—ผ๐—ป: ๐Ÿ“ง datawithdany@gmail.com ๐Ÿ“ฑ WhatsApp: 234 911 028 9203 โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” Hereโ€™s to a great 2026. #DataAnalysis #DataEngineering #Excel #SQL #Python #PowerBI #DataWithDanny #NewYear2026 #Datafam
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๐—›๐—ฎ๐—ฝ๐—ฝ๐˜† ๐—ก๐—ฒ๐˜„ ๐—ฌ๐—ฒ๐—ฎ๐—ฟ, #๐——๐—ฎ๐˜๐—ฎ๐—ณ๐—ฎ๐—บ! ๐ŸŽ‰ Welcome to 2026. If youโ€™re ready to finally start your data analytics journey - weโ€™re starting in 30 days. โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” ๐——๐—ฎ๐˜๐—ฎ ๐˜„๐—ถ๐˜๐—ต ๐——๐—ฎ๐—ป๐—ป๐˜† - ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿด ๐—ฆ๐˜๐—ฎ๐—ฟ๐˜๐˜€ ๐—๐—ฎ๐—ป๐˜‚๐—ฎ๐—ฟ๐˜† ๐Ÿฏ๐Ÿฌ๐˜๐—ต, ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ 4 months. Beginner to job-ready. ๐—ช๐—ต๐—ฎ๐˜ ๐˜†๐—ผ๐˜‚โ€™๐—น๐—น ๐—บ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ: ๐—ช๐—ต๐—ฎ๐˜ ๐˜†๐—ผ๐˜‚โ€™๐—น๐—น ๐—ด๐—ฎ๐—ถ๐—ป: โ€ข Excel โœ“ 8 real-world projects โ€ข SQL โœ“ 1-on-1 mentorship โ€ข Python โœ“ Certificate of completion โ€ข Power BI โœ“ World-class resources โ€ข Figma โ€ข PowerPoint โ€ข Statistics โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” ๐Ÿ“… ๐—ฆ๐˜๐—ฎ๐—ฟ๐˜ ๐——๐—ฎ๐˜๐—ฒ: January 30th, 2026 โฐ ๐—–๐—น๐—ฎ๐˜€๐˜€๐—ฒ๐˜€: Friday to Sunday, 7-9 PM WAT ๐Ÿ’ฐ ๐—œ๐—ป๐˜ƒ๐—ฒ๐˜€๐˜๐—บ๐—ฒ๐—ป๐˜: โ‚ฆ80,000 (Nigerians) ๐Ÿ‡ณ๐Ÿ‡ฌ $80 (International) ๐ŸŒ โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” If youโ€™re serious about learning data analytics this year, weโ€™d love to have you. ๐Ÿ”— Register: selar.com/7q7p1y224k ๐—™๐—ผ๐—ฟ ๐—บ๐—ผ๐—ฟ๐—ฒ ๐—ถ๐—ป๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐˜๐—ถ๐—ผ๐—ป: ๐Ÿ“ง datawithdany@gmail.com ๐Ÿ“ฑ WhatsApp: 234 911 028 9203 โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” Hereโ€™s to a great 2026. #DataAnalysis #DataEngineering #Excel #SQL #Python #PowerBI #DataWithDanny #NewYear2026 #Datafam
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๐—ง๐—ผ๐—ฑ๐—ฎ๐˜†โ€™๐˜€ ๐˜๐—ต๐—ฒ ๐—น๐—ฎ๐˜€๐˜ ๐—ฑ๐—ฎ๐˜† ๐—ผ๐—ณ ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ. Remember what you told yourself January 1st? โ€œThis is my year.โ€ โ€œIโ€™m finally learning data analytics.โ€ โ€œIโ€™m switching careers.โ€ ๐—›๐—ผ๐˜„ ๐—ฑ๐—ถ๐—ฑ ๐˜๐—ต๐—ฎ๐˜ ๐—ด๐—ผ? If youโ€™re reading this and you didnโ€™t start - itโ€™s not too late. But 2026 wonโ€™t be different unless ๐˜†๐—ผ๐˜‚ make it different. โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” ๐——๐—ฎ๐˜๐—ฎ ๐˜„๐—ถ๐˜๐—ต ๐——๐—ฎ๐—ป๐—ป๐˜† - ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿด ๐—ฆ๐˜๐—ฎ๐—ฟ๐˜๐˜€ ๐—๐—ฎ๐—ป๐˜‚๐—ฎ๐—ฟ๐˜† ๐Ÿฏ๐Ÿฌ๐˜๐—ต, ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ 4 months. Beginner to job-ready. ๐—ช๐—ต๐—ฎ๐˜ ๐˜†๐—ผ๐˜‚โ€™๐—น๐—น ๐—บ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ: ๐—ช๐—ต๐—ฎ๐˜ ๐˜†๐—ผ๐˜‚โ€™๐—น๐—น ๐—ด๐—ฎ๐—ถ๐—ป: โ€ข Excel โœ“ 8 real-world projects โ€ข SQL โœ“ 1-on-1 mentorship โ€ข Python โœ“ Certificate of completion โ€ข Power BI โœ“ World-class resources โ€ข Figma โ€ข PowerPoint โ€ข Statistics โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” ๐Ÿ“… ๐—ฆ๐˜๐—ฎ๐—ฟ๐˜ ๐——๐—ฎ๐˜๐—ฒ: January 30th, 2026 โฐ ๐—–๐—น๐—ฎ๐˜€๐˜€๐—ฒ๐˜€: Friday to Sunday, 7-9 PM WAT ๐Ÿ’ฐ ๐—ฆ๐—ฝ๐—ฒ๐—ฐ๐—ถ๐—ฎ๐—น ๐—ข๐—ณ๐—ณ๐—ฒ๐—ฟ: โ‚ฆ80,000 (Nigerians) ๐Ÿ‡ณ๐Ÿ‡ฌ $80 (International) ๐ŸŒ โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” Stop saying โ€œnext year.โ€ Next year is ๐˜๐—ผ๐—บ๐—ผ๐—ฟ๐—ฟ๐—ผ๐˜„. ๐Ÿ”— Register now: selar.com/7q7p1y224k ๐—™๐—ผ๐—ฟ ๐—บ๐—ผ๐—ฟ๐—ฒ ๐—ถ๐—ป๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐˜๐—ถ๐—ผ๐—ป: ๐Ÿ“ง datawithdany@gmail.com ๐Ÿ“ฑ WhatsApp: 234 911 028 9203 โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” Make 2026 different. Start now. #DataAnalysis #DataEngineering #Excel #SQL #Python #PowerBI #DataWithDanny #2026Goals #Datafam
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๐—ฌ๐—ผ๐˜‚ ๐—ฑ๐—ผ๐—ปโ€™๐˜ ๐—ต๐—ฎ๐˜ƒ๐—ฒ ๐˜๐—ผ ๐—ฏ๐—ฟ๐—ฒ๐—ฎ๐—ธ ๐˜๐—ต๐—ฒ ๐—ฏ๐—ฎ๐—ป๐—ธ ๐˜๐—ผ ๐—น๐—ฒ๐—ฎ๐—ฟ๐—ป ๐—ฑ๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€. Start 2026 with a purpose. ๐ŸŽฏ ๐—ง๐—ต๐—ถ๐˜€ ๐—ถ๐˜€ ๐—ฑ๐—ถ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐˜. ๐—•๐—ฒ๐—ฐ๐—ฎ๐˜‚๐˜€๐—ฒ ๐—ถ๐˜โ€™๐˜€ ๐—ต๐—ฎ๐—ป๐—ฑ๐˜€-๐—ผ๐—ป. The current cohort, on ๐—˜๐˜…๐—ฐ๐—ฒ๐—น ๐—ฎ๐—น๐—ผ๐—ป๐—ฒ - imagine going from zero to performing: โ†’ Regression analysis โ†’ What-if scenarios โ†’ ETL processes โ†’ Statistics and data analytics โ†’ Data visualization ๐—”๐—น๐—น ๐˜„๐—ถ๐˜๐—ต๐—ถ๐—ป ๐˜๐—ต๐—ฒ ๐—ณ๐—ถ๐—ฟ๐˜€๐˜ ๐Ÿฑ ๐˜„๐—ฒ๐—ฒ๐—ธ๐˜€. โšก Thatโ€™s what makes us different. ๐—ช๐—ฒ ๐—ด๐—ผ ๐˜„๐—ฎ๐˜† ๐—ฏ๐—ฒ๐˜†๐—ผ๐—ป๐—ฑ ๐—ฑ๐—ฎ๐˜€๐—ต๐—ฏ๐—ผ๐—ฎ๐—ฟ๐—ฑ๐˜€. โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” ๐——๐—ฎ๐˜๐—ฎ ๐˜„๐—ถ๐˜๐—ต ๐——๐—ฎ๐—ป๐—ป๐˜† - ๐—–๐—ผ๐—ต๐—ผ๐—ฟ๐˜ ๐Ÿด 4 months. Beginner to job-ready. ๐Ÿš€ ๐—ช๐—ต๐—ฎ๐˜ ๐˜†๐—ผ๐˜‚โ€™๐—น๐—น ๐—บ๐—ฎ๐˜€๐˜๐—ฒ๐—ฟ: โœ… Excel โœ… SQL โœ… Python โœ… Power BI โœ… Figma โœ… PowerPoint โœ… Statistics ๐—ช๐—ต๐—ฎ๐˜ ๐˜†๐—ผ๐˜‚โ€™๐—น๐—น ๐—ด๐—ฎ๐—ถ๐—ป: ๐ŸŽฏ 8 real-world projects ๐ŸŽฏ 1-on-1 mentorship from industry experts ๐ŸŽฏ Certificate of completion ๐ŸŽฏ Full access to world-class resources โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” ๐Ÿ“… ๐—ฆ๐˜๐—ฎ๐—ฟ๐˜ ๐——๐—ฎ๐˜๐—ฒ: January 30th, 2026 โฐ ๐—–๐—น๐—ฎ๐˜€๐˜€๐—ฒ๐˜€: Friday to Sunday, 7-9 PM WAT ๐Ÿ’ฐ ๐—ฆ๐—ฝ๐—ฒ๐—ฐ๐—ถ๐—ฎ๐—น ๐—ข๐—ณ๐—ณ๐—ฒ๐—ฟ: โ‚ฆ80,000 (Nigerians) ๐Ÿ‡ณ๐Ÿ‡ฌ $80 (International) ๐ŸŒ โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” ๐Ÿ”— ๐—ฅ๐—ฒ๐—ด๐—ถ๐˜€๐˜๐—ฒ๐—ฟ ๐—ต๐—ฒ๐—ฟ๐—ฒ: selar.com/7q7p1y224k ๐—™๐—ผ๐—ฟ ๐—บ๐—ผ๐—ฟ๐—ฒ ๐—ถ๐—ป๐—ณ๐—ผ๐—ฟ๐—บ๐—ฎ๐˜๐—ถ๐—ผ๐—ป: ๐Ÿ“ง datawithdany@gmail.com ๐Ÿ“ฑ WhatsApp: 234 911 028 9203 โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ” Letโ€™s make 2026 your breakthrough year. ๐Ÿ’ช #DataAnalysis #DataEngineering #Excel #SQL #Python #PowerBI #DataWithDanny #Datafam
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