Bahre Hailemariam

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Data Analyst | BI Developer

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About Me

Welcome!
Hi ! I am Bahre Hailemariam Kidanemariam, and I am a Data Analytics.
I focus on creating reports and visualizations for data-forward companies.
I am laser-focused on creating business insights that drive decision making, and I help companies automate reports that connect to all their data.
I have spent 100's of hours developing reports that save time and money.Best,Bahre

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Skills

SQL | Power BI | Excel | Tableau | Python | AI

Featured Projects

Seasonal Sales Trends Analysis using Power BI |SQL server

Replaced a manual process by creating a SQL script and Power BI dashboard to pull and visualize revenue data.

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Emergency Room Patient Flow & Wait Time Optimization by Utilizing Power BI | Excel

Creating Visualization and data driven Insight for Patients Emergency Room visit report.

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Employee Performance & Productivity Analysis Using Power BI and Excel

Creating Dashboard and Report of Employee work habit using Power BI and Excel.

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Analyzing and Manipulation using SQL

Analyzing and Modelling of Anbessa bank database system using MySQL And Excel

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Immigration to Canada from 1980 to 2013

Analyzing and Visualization the Immigration to Canada from 1980 to 2013 using Python

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Data Analytics for Insurance Cost Data Set using Python

Data Wrangling ,EDA and Model Development ad Refinement using Python and notebook

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Furniture sales Overview

Transformation, Pivoting ,analyzing ,visualization and Dashboarding using Excel

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• For more Projects click this

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Professional Certifications

My growing list of proprietary,exam-based certifications.

IBM Data Science Professional Certificate | Issued Jan 13 2025

Become _ a_ Python_Master | Issue 2nd October 2023

Become _ a_ SQL_Master | Issue 24th September 2023

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Seasonal Sales Trends Analysis using Power BI |SQL server management studio 20

Data Cleansing & Transformation (SQL)
To create the necessary data model for doing analysis and fulfilling the business needs defined in the user stories the following tables were extracted using SQL.One data source (sales budgets) were provided in Excel format and were connected in the data model in a later step of the process.Below are the SQL statements for cleansing and transforming necessary data.

DIM_Calendar:

-- Cleansed DIM_Date Table --
SELECT
[DateKey],
[FullDateAlternateKey] AS Date,
--[DayNumberOfWeek],
[EnglishDayNameOfWeek] AS Day,
--[SpanishDayNameOfWeek],
--[FrenchDayNameOfWeek],
--[DayNumberOfMonth],
--[DayNumberOfYear],
--[WeekNumberOfYear],
[EnglishMonthName] AS Month,
Left([EnglishMonthName], 3) AS MonthShort, -- Useful for front end date navigation and front end graphs.
--[SpanishMonthName],
--[FrenchMonthName],
[MonthNumberOfYear] AS MonthNo,
[CalendarQuarter] AS Quarter,
[CalendarYear] AS Year --[CalendarSemester],
--[FiscalQuarter],
--[FiscalYear],
--[FiscalSemester]
FROM
[AdventureWorksDW2022].[dbo].[DimDate]
WHERE
CalendarYear >= 2022

DIM_Customers:

-- Cleansed DIM_Customers Table --
SELECT
c.customerkey AS CustomerKey,
-- ,[GeographyKey]
-- ,[CustomerAlternateKey]
-- ,[Title]
c.firstname AS [First Name],
-- ,[MiddleName]
c.lastname AS [Last Name],
c.firstname + ' ' + lastname AS [Full Name],
-- Combined First and Last Name
-- ,[NameStyle]
-- ,[BirthDate]
-- ,[MaritalStatus]
-- ,[Suffix]
CASE c.gender WHEN 'M' THEN 'Male' WHEN 'F' THEN 'Female' END AS Gender,
-- ,[EmailAddress]
-- ,[YearlyIncome]
-- ,[TotalChildren]
-- ,[NumberChildrenAtHome]
-- ,[EnglishEducation]
-- ,[SpanishEducation]
-- ,[FrenchEducation]
-- ,[EnglishOccupation]
-- ,[SpanishOccupation]
-- ,[FrenchOccupation]
-- ,[HouseOwnerFlag]
-- ,[NumberCarsOwned]
-- ,[AddressLine1]
-- ,[AddressLine2]
-- ,[Phone]
c.datefirstpurchase AS DateFirstPurchase,
-- ,[CommuteDistance]
g.city AS [Customer City] -- Joined in Customer City from Geography Table
FROM
[AdventureWorksDW2022].[dbo].[DimCustomer] as c
LEFT JOIN dbo.dimgeography AS g ON g.geographykey = c.geographykey
ORDER BY
CustomerKey ASC -- Ordered List by CustomerKey

DIM_Products:

-- Cleansed DIM_Products Table --
SELECT
p.[ProductKey],
p.[ProductAlternateKey] AS ProductItemCode,
-- ,[ProductSubcategoryKey],
-- ,[WeightUnitMeasureCode]
-- ,[SizeUnitMeasureCode]
p.[EnglishProductName] AS [Product Name],
ps.EnglishProductSubcategoryName AS [Sub Category], -- Joined in from Sub Category Table
pc.EnglishProductCategoryName AS [Product Category], -- Joined in from Category Table
-- ,[SpanishProductName]
-- ,[FrenchProductName]
-- ,[StandardCost]
-- ,[FinishedGoodsFlag]
p.[Color] AS [Product Color],
-- ,[SafetyStockLevel]
-- ,[ReorderPoint]
-- ,[ListPrice]
p.[Size] AS [Product Size],
-- ,[SizeRange]
-- ,[Weight]
-- ,[DaysToManufacture]
p.[ProductLine] AS [Product Line],
-- ,[DealerPrice]
-- ,[Class]
-- ,[Style]
p.[ModelName] AS [Product Model Name],
-- ,[LargePhoto]
p.[EnglishDescription] AS [Product Description],
-- ,[FrenchDescription]
-- ,[ChineseDescription]
-- ,[ArabicDescription]
-- ,[HebrewDescription]
-- ,[ThaiDescription]
-- ,[GermanDescription]
-- ,[JapaneseDescription]
-- ,[TurkishDescription]
-- ,[StartDate],
-- ,[EndDate],
ISNULL (p.Status, 'Outdated') AS [Product Status]
FROM
[AdventureWorksDW2022].[dbo].[DimProduct] as p
LEFT JOIN dbo.DimProductSubcategory AS ps ON ps.ProductSubcategoryKey = p.ProductSubcategoryKey
LEFT JOIN dbo.DimProductCategory AS pc ON ps.ProductCategoryKey = pc.ProductCategoryKey
order by
p.ProductKey asc

FACT_InternetSales:

-- Cleansed FACT_InternetSales Table --
SELECT
[ProductKey],
[OrderDateKey],
[DueDateKey],
[ShipDateKey],
[CustomerKey],
-- ,[PromotionKey]
-- ,[CurrencyKey]
-- ,[SalesTerritoryKey]
[SalesOrderNumber],
-- [SalesOrderLineNumber],
-- ,[RevisionNumber]
-- ,[OrderQuantity],
-- ,[UnitPrice],
-- ,[ExtendedAmount]
-- ,[UnitPriceDiscountPct]
-- ,[DiscountAmount]
-- ,[ProductStandardCost]
-- ,[TotalProductCost]
[SalesAmount] -- ,[TaxAmt]
-- ,[Freight]
-- ,[CarrierTrackingNumber]
-- ,[CustomerPONumber]
-- ,[OrderDate]
-- ,[DueDate]
-- ,[ShipDate]
FROM
[AdventureWorksDW2022].[dbo].[FactInternetSales]
WHERE
LEFT (OrderDateKey, 4) >= YEAR(GETDATE()) -2 -- Ensures we always only bring two years of date from extraction.
ORDER BY
OrderDateKey ASC

Data Model
Below is a screenshot of the data model after cleansed and prepared tables were read into Power BI.This data model also shows how FACTBudget hsa been connected to FACTInternetSales and other necessary DIM tables.

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Emergency Room Patient Flow & Wait Time Optimization by Utilizing Power BI | Excel| Power point

Finding and Insights

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Employee Performance & Productivity Analysis Using Power BI and Excel

Insight from Above Dashboard

Specifically and more details insights and findings

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