YERES ♤

Hi, I'm Yeres. I'm documenting my journey from Marine Engineering to Data Analytics Here you'll find: • Excel tips • SQL Projects • Power BI dashboards • Data cleaning • Portfolio updates Follow along!!

@Airways_geek I recommend @Designer_Elo He's good 👍

I need a cracked UI/UX designer 😭😔

@iamjosephukpong @vheeorji22 Yessir!!

@vheeorji22 Power Query is 👑

Do you prefer Excel formulas or Power Query for data cleaning?

@vheeorji22 @delf002 If you haven't, I highly recommend

@delf002 Ok Nice But, have you tried power query ?

@vheeorji22 I prefer power query It's neater and faster And bonus points for having your exact steps noted in a corner

🧵 5 Excel functions every Data Analyst should know before learning Power BI 1. XLOOKUP Better than VLOOKUP. Flexible and cleaner. 2. SUMIFS For conditional calculations. 3. IF / IFS For logical decisions. 4. FILTER Extracts only needed records instantly. 5. TEXTJOIN Combines text dynamically. Master these first. Power BI becomes easier later.

You learn more from fixing bugs than from watching tutorials.

@ccyberzoid This is great news man Congratulations and Good morning!!

Good morning data family! My day starts off with great news, I've applied for a junior data analytics scholarship and I got accepted, It covers a lot about data analytics and it's starting next Friday so wish me luck! It all starts with a dream. #DataAnalytics #DataCommunity

LET ME SEE IF I CAN BREAK IT DOWN SPOTIFY 1. Spotify is able to recommend a right song for you by matching your data, such as age, gender, location etc with people that shares similar data and use the listening history of those people to recommend a song for you. This is Data Science. 2. When Spotify’s internal team tracks which songs are trending by region and artist, build chart or display that ranks artist that’s Data Analytics. OPAY 1. When Opay flags a transfer and warns you the receiver might be a fraudster, that’s Data Science. Their algorithm would have detected several anomalies with the receiving account to conclude that it may be a fraudster. 2. When Opay’s analysts tell stakeholders which product is selling better, why customers are churning, and where revenue growth can come from, that’s Data Analytics. INSTAGRAM 1. You search “bags” once, and suddenly every ad and reel is about bags, that’s Data Science. They have use your recent activity to decide what you're interested in seeing. 2. When Instagram’s team reports the number of premium subscribers per region, or engagement per post, that’s Data Analytics. In short: Data Science predicts and automates. Data Analytics explains and informs.

@OnanefeTGA Not great at all Onanefe! I had work on my system but it spoilt and my hands have been tied all weekend

Been trying somethings left and right, mainly the stuff we tweet about because why not? Hey guys, how was your weekend?

@IamRedeemed170 @AndyjnrUmaru 😂😂

@AndyjnrUmaru In all honesty, A looks like a filling station.

Which Roof do you prefer best for this building? Roof A or B

@halenhargreevs Apex legends Stole so many hours of my life

GAMERS ONLY: Which game has stolen the most hours of your life?

• Power BI After doing all the PROPER, UPPER, X LOOKUPS/MATCH SELECTS, GROUP BY, ETC You need to form this into a cohesive whole in the form of dashboards, intuitive platforms where you can break down the data set for the client. • Python Optional IMO

Thinking about breaking into Data? • Start with Excel Cleaning data and organising it is arguably the first thing an analyst should be conversant with • SQL This works with larger data sets that will typically make excel lag A fundamental skill for analysts

@DabereNnamani Same thing I told someone earlier today. Simplicity beats complexity!! As long as you make sure that the simplified bits are the important bits

5 Data Myths That Need To Die People don’t struggle with data because of the tools. They struggle because they’ve believed the wrong things for too long. Let’s fix a few of them. • Dashboards solve business problems: A dashboard can show you what’s happening. It can’t decide what to do next. Insights create value. Dashboards only present information. • AI replaces analysts: AI can write queries, summarize reports, and automate tasks. It still needs someone to ask the right questions, validate results, and understand the business.

@ezekiel_aleke Great thread!!

"After learning Data Analysis, how can I get a job?" Forget the traditional 9-to-5 grind. If you actually know your tools (Spreadsheet, Power BI, SQL). Here are 10 ways to make cool money as a Data Analyst. 🧵

@OnanefeTGA I used to think that the more things I have on there, the more slicers, more charts, more information makes my work convey more information, but overtime you learn that less is really more. So far the "Less" are the important bits

1. Translate the Technical Jargon Executives don't care about your clean table JOINs, or how optimized your Excel formulas are. ​They care about revenue, retention, and risk. If your insights don't directly speak to one of those three things, reframe them before you present.

A trap we might fall into when learning data analysis is thinking our job ends when we design good looking dashboards. A clean Power BI dashboard means nothing if the business stakeholders can't understand it ​Here is a framework to master the art of data storytelling: 👇

@only1cleveraph @deartrader__ After you don check finish, send am come abeg

@deartrader__ Spin an come my side fes mek I check if e go fit change my life 🥲

Be honest: can this change a trader life forever???

Another quarter to EXCEL

@vheeorji22 I'd apply Cus win or lose, I still gained some experience that will guide my hand next time

If your Excel skills were only average, but your dream job required you to be highly proficient in Excel… Would you still apply or would you take a course first before applying?