Top Tweets for #HTTdatachallenge
Everything looks like a priority until you move the benchmark
14/15 #HTTDataChallenge ✅
#FMCGNigeria #SQLAggregations #PostgreSQL

Whelp☹️...
Day 14 of @hertechtrail #HTTDataChallenge task is to retrieve the total sales for each channel from which clients access the company. Highlight high value and low value channels.
#SQLJoinAggregations #DataIntegration

Day 13 of @hertechtrail #HTTDataChallenge task: find customers who have made orders above the average order value.
@phaibooboo @it_is_reel @precy_oma
@Ogbonna42449096 @AtiJoshua
#SQLSubqueries #DataAnalysis

Precision > Volume
Today's focus: SQL Aggregations
Used SUM and AVG to rank revenue generators. Identifying the primary accounts helps to prioritize resources effectively.
Day 12 of #HTTDataChallenge ✅
#FMCGNigeria #DataAnalytics #SQL

Day 10 of the @hertechtrail #HTTDataChallenge is to join two tables and retrieve 3 columns each from them
I joined accounts and orders table, and retrieved 3 columns each using SQL query.
#SQLJoining #DataIntegration

If you can't link customers to revenue, you're flying blind.
Today: Data Integration using SQL JOINS to bridge the 'Accounts' & 'Orders' tables.
Result: 6,912 transactions mapped to names/POCs.
Day11 of #HTTDataChallenge @hertechtrail
#FMCGNigeria #SQL #DataAnalysis

Day 10 of the @hertechtrail #HTTDataChallenge was to retrieve customer names in alphabetical order using SQL query.
SELECT name (retrieves only the name column)
FROM accounts (your customer names are in the accounts table)
ORDER BY & ASC (sorts in ascending order )
#SQLQuery

If the team can't find data quickly, you are losing money.
Day 10 of #HTTDataChallenge: Using SQL to automate the order of the accounts table. No more manual sorting; just clean, searchable results ready for the next business move.
#SQLSorting #DataManipulation #FMCGNigeria

I’m early today😂🤭
Day 9 of the @hertechtrail #HTTDataChallenge task is to retrieve all column from any specific table
I used the commands
SELECT *
FROM region;
Result = 4 rows and 2 columns
SELECT *
FROM accounts;
Result = 351 rows and 7 columns
#SQLQuery #SQLBasics

A busy manager shouldn't have to "study" a chart to find the answer.
For Day 8, I highlighted the top performer: Skechers. Instead of a cluttered graph, I used a clean bar chart to tell the story.
Clarity over clutter, every time.
#HTTDataChallenge #FMCG #SalesAnalysis

Day 8 of the @hertechtrail #HTTDataChallenge and today’s task is to create a bar chart showing brand sales distribution on a shoes dataset.
From the chart you can see that:
Sketcher got $269,169
New Balance $261,632
Adidas $257,039
Reebok $238,827
Puma $233,750
Nike $192,770
👇🏾

Day 7 of @hertechtrail #HTTDataChallenge and today’s task is data validation(making sure that only valid entries make it into the dataset.
I made use of the brand column which only accepts 6 approved brands: Adidas, New Balance, Nike, Puma, Reebok & Sketchers.
👇🏾#DataValidation

Sales over the year are inconsistent,with clear peaks in months like February, July, and October, while months like May and August show lower performance.This shows sales are influenced by timing or seasonal demand rather than steady growth.#HTTDataChallenge
#hertechtrailacademy

Yesterday was Day 6 of the @hertechtrail #HTTDataChallenge (I missed 🫠)
I analyzed sales trend overtime of the shoe data set. This is what stood out for me:
-Q4 is the strongest quarter at $404k
-Q3 is the weakest (August and September went too low)
👇🏾👇🏾 #DataAnalysis

Building on "the what", I dove into the "why“ for Day 6.
• Q3 Revenue dip: Needs mid-quarter restocking.
• Nike: Low volume, top-tier revenue.
• Online: High efficiency.
• UAE: Market leader.
Findings & Solutions in the screenshot
#HTTDataChallenge #RetailAnalysis

Omo, Day 5 of the #HTTDataChallenge tried to be funny with me today 😂
It was a bit of a challenge getting 3 different pivot tables stay consistent while slicing data. But the clarity at the end? Worth it.
Revenue and Units analyzed. We move🥳🥳
#PivotTables #DataAnalysis

Day 4 #HTTDataChallenge: I had to put in a bit of analytics here.
Set a $3k benchmark to find the hidden driving force of the total revenue. It's one thing to see numbers, it's another to see the story they're telling.
#DataAnalytics #LagosTech #WomenInTech

Day 3 of the #HTTDataChallenge @hertechtrail was all about using Excel formulas to to calculate:
Total Sales using =SUM(Revenue_USD)
Found Average Order Value using =AVERAGE(Revenue_USD)
Also calculated Total Units Sold using =SUM(Units_Sold)
#HerTechTrailAcademy #Excel

Day 3 #HTTDataChallenge
Moving past the cleaning phase guys🙌🏼
Transitioned from data cleaning to business metrics today
✅ Calculated Total Sales & AOV
💡Key takeaway: AOV reveals the story behind sales growth
#DataAnalysis #ExcelFormulas #WomenInTech

Day 2 of the #15DaysChallenge @hertechtrail
Cleaned a shoe sales dataset in Excel by checking for duplicates and missing values. Data cleaned and ready ti be analyzed. 📊👟
#HTTDataChallenge #ExcelDataImport #DataCleaning

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