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Sales KPIs

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  SALES KPI TO ACHIEVE BUSSINESS GOALS     TO BOOST SALE   ·           Year-over-year sales YoY Sale) ·           Conversion rate (CR) ·           Average order value (AOV) ·           Basket size     TO STRENGTHEN CUSTOMER EXPERIENCE   ·           conversion rate (CR) ·           average order value (AOV) ·           basket size ·           customer retention rate (CRR)     TO Reduce stock-outs   ·           Inventory turnover (ITR) ·           Sell-through rate (STR) ·           Shrinkage     TO Optimize profits   ·           Cost of goods sold (COGS) ·           Gross profit (GP) ·           Net profit (NP) ·           RETURN ON SALE (RoS) ·           Gross margins return on investment (GMROI)     A FEW SALES KPI EXPLAINED IN SHORT   COGS   Measuring your COGS is essential to achieving  profitability . If you know how much you spent to acquire or produce your products, you can set prices that are  competitive , but that also offset your expenses.   average order valu
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Data Analyst Vs Business Analyst Vs Data Engineer Vs BI Specialist

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  Data Science - Complete Track • Step 1 - Identify the business problem/value addition/question – ( Data Insights ) this has to be the starting point. • Step 2 - Data availability ( Data Governance ) - Have the structure of your data set defined – The real challenge starts here-                o Do we have the data?                o Do we have access to the required data? • Step 3 -Getting Data ( Data Mining / Data Pipeline ) – How to collect the data from different sources in the system • Step 4 - Data preparation (ETL / ELT) – Once you have data there will be lot of cleaning and preparation required, reduce/increase/combine/split the predictors, determine and eliminate outliers, populate missing values convert few categorical variables into numerical etc. • Step 5 –Exploratory Data Analysis (EDA) – In this step we do descriptive and diagnostic analysis of the existing data. We build multiple graphs that give us direction towards the next steps of predictive analytics. We migh
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Essentials You Need to Know Before Investing in Stocks

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  COMPANY FUNDAMENTALs information such as  PROFITABILITY, REVENUE, ASSETS, LIABILITIES, DEBT, AND GROWTH POTENTIAL are considered fundamentals COMPANY FINANCIALs CURRENT RATIO = CURRENT ASSETS / CURRENT LIABILITIES DEBT RATIO = TOTAL LIABILITIES / TOTAL ASSETS RETURN ON ASSETS RATIO = NET INCOME / TOTAL ASSETS RETURN ON EQUITY RATIO = NET INCOME / SHAREHOLDER’S EQUITY DIVIDEND YIELD RATIO = DIVIDEND PER SHARE / SHARE PRICE EPS = EARNINGS PER SHARE RATIO = NET EARNINGS / TOTAL SHARES OUTSTANDING PE = PRICE-EARNINGS RATIO = SHARE PRICE / EARNINGS PER SHARE COMPANY PAYOUTs DIVIDEND, BONUS, RIGHTS A payout is the share of profits that a listed company will pay its shareholders. If the payout set out in the company’s shareholder remuneration policy is 50%, the company will distribute half of its net profits among its shareholders.  A dividend is cash paid to shareholders for their share in the company's profits.  A share buyback and the subsequent cancellation of shares are w
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NVIDIA DGX B200

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  Nvidia turns up the AI heat with 1,200W Blackwell GPUs AI's power and thermal demands hit home Nvidia doubles up on GPU compute with second-gen Superchips According to Nvidia its DGX B200 chassis with eight B200 GPUs will consume roughly 14.3kW – something that's going to require roughly 60kW of rack power and thermal headroom to handle. Blackwell's full potential will require switching over to liquid cooling. In a liquid-cooled configuration, Nvidia says the chip can output 1,200W of thermal energy when pumping out the full 20 petaFLOPS of FP4. While Nvidia may dominate the AI infrastructure market, it's hardly the only name out there. Heavy hitters like Intel and AMD are rolling out Gaudi and Instinct accelerators. The B200 "Blackwell" is the largest chip physically possible using existing foundry tech, according to its makers. The chip is an astonishing 208 billion transistors , and is made up of two chiplets, which by themselves are the largest
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DATA ENGINEER CERTIFICATIONS

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a { text-decoration: none; color: black; }   WHAT DATA ENGINEERs DO? Data engineers work in a variety of settings to build systems that: Collect, Manage, and Convert Raw Data into usable information for Data Scientists and Business Analysts to Interpret. RECOMMENDED CERTIFICATIONs FUNDAMENTALS AND CAREER CERTIFICATION from IBM ETL and Data Pipelines with Shell, Airflow and Kafka from IBM TECHNOLOGY CERTIFICATIONs: Microsoft Certified: Azure Fundamentals PRE-REQUISITES: Infrastructure management. Database management. Software development. AWS Certified Data Engineer Associate 2024 - Hands On! from UDEMY AWS Certified Data Engineer - Associate AWS RECOMMENDS: 2-3 years of experience in data engineering 1-2 years of hands-on experience with AWS services
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DATA ANALYST TRACK

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  1) SPREADSHEETs SKILLs DATA IMPORT ( CSV / JSON / REVERSE ETL / ODBC ) WEB DATA SCRAPING ( CHROME / GOOGLE SHEET / REGEX ) DATA CLEANING / PREPARATION ( EXCEL / GOOGLE SHEET ) DATA FORMATING 2) DATABASES AND SQL CONCEPTS SELECT CLUASES WHERE CLAUSES JOIN CLAUSES GROUP BY CLAUSES 3) DATA ANALYTICS AND BI TOOLs DATA MODELING ( STAR SCHEMAs, ERDs ) DATA CALCULATIONs DATA VISSUALIZATION ( POWER BI / TABLEAU PUBLIC / GOOGLE LOOKER STUDIO / QLIK ) 4) BUSSINESS MATHEMATICS AND STATISTICS ACCOUNTING AND FINANCE BASICS BASIC STATISTICS ( TYPE OF CHARTs / AGGREGATIONs ) HYPOTHESIS TESTING ( DRAW CONCLUSIONS FROM SAMPLE DATA ) BUSSINESS MODELING ( B2B , B2C etc ) 5) CODING SKILLs PYTHON AND R ( POSIT.CLOUD ) DATA CLEANUP BY SQL ( GOOGLE BIGQUERY  CLOUD SQL )    VIDEO LINK - 1   |  VIDEO LINK - 2 STATISTICAL CALCULATIONs MACHINE LEARNING  LIBRARIES AND DATA VISSUALIZATION 6) BUSSINESS APPLICATIONs EMAIL CLIENTs for MARKETTING ( MS OUTLOOK / SLACK ) PRESENTATIONs ( MS POWERPOINT / GOOGLE SLID
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KEY PERFORMANCE METRICS FOR BANKS

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Leadership starts with access to the right information to make intelligent decisions and drive a  data culture . The average bank spends an excessive number of hours per month assembling financial performance reports, then updating, distributing, and  interpreting data . Bank should consider a  performance management tool  designed to automate the entire process, empowering to do less administrative work compiling data and reports, and more time making  data-driven decisions  that impact bottom-line success. Impactful strategic decisions  then start with understanding current performance strengths and areas of improvement by tracking the right mix of key performance metrics for banks metrics and bank KPIs. METRICS: 1. LDR Loans/Deposits Ratio (LDR) – Expressed as a percentage, LDR is used to assess a bank's liquidity by comparing a bank's total loans to its total deposits for the same period. If the ratio is too high, it means that the bank may not have enough liquidity to
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