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[Holy Shit @88888fy]

@pit_u80 لا عاد كلي زق

[Compounding Dividends @CompoundingW]

Financial Modelling Fundamentals

A full training course on financial modeling fundamentals

Here’s what you’ll learn:
• Introduction & Overview
• Income Statement Module
• Balance Sheet Module
• Cash Flow Statement Module

[Kirk Borne @KirkDBorne]

Financial Theory with Python — A Gentle Introduction: https://t.co/iXnTS9R1qB by @dyjh
————
#Finance #DataScience #DataScientist

[V @Mayalovemeow]

Everything he says becomes unforgettable

[ِ @siriusreveur]

وداعًا للحق وأهلًا بالظلم أمام هذا الكم من الجمال

[هاه؟ @whatneedtobsaid]

اويلي عالفيسكارد

[Bojan Radojicic @BojanRadojici10]

"Our close is fine." "We just need better tools." "We are pretty mature, actually." None of that tells you what to fix first.

So I built an assessment that replaces the opinion with a number.

40 questions across 8 dimensions that shape a modern finance function.

→ Close and Reporting
→ Planning and Budgeting
→ Forecasting
→ Data and Systems
→ Analysis and Insight
→ Business Partnering
→ Automation and Technology
→ Team and Capability

For each dimension, you rate your current state from Reactive to Structured to Proactive to Strategic.

The assessment scores your function out of 160 and highlights the areas that need attention first.

In the sample, the assessment returns 105 out of 160, placing the function at the Proactive level. Planning and Forecasting are strengths, while Close and Data & Systems are flagged as priority areas.

That is the point. Not the score. The gaps.

Run it yourself, then have your team complete it separately. The differences between your answers are often where the most valuable conversations start.

If you want this Finance Function Maturity Assessment, just drop a comment and I’ll send it to you.
(Important: follow me so I can DM you!)

[Kirk Borne @KirkDBorne]

11 Python Books in the thread below …

[Kirk Borne @KirkDBorne]

Machine Learning Engineering with Python — Manage the lifecycle of machine learning models using MLOps with practical examples: https://t.co/OcxepDoRoU

𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
🟢Transform your machine learning projects into successful deployments with this practical guide on how to build and scale solutions that solve real-world problems

🔵[2nd edition] Includes a new chapter on generative AI and large language models (LLMs) and building a pipeline that leverages LLMs using LangChain

🟢Delve deep into key machine learning topics, CI/CD, and system design

🔵Explore core MLOps practices, such as model management and performance monitoring

🟢Build end-to-end examples of deployable ML microservices and pipelines using AWS and open-source tools

[Kirk Borne @KirkDBorne]

Python in Excel — Unlock powerful data analysis and automation solutions: https://t.co/cYl3fiRfEQ

[Bojan Radojicic @BojanRadojici10]

A rep closes a big deal at 90-day terms and a large discount. Sales celebrates. Three months later finance is chasing the cash and the margin is gone. Nobody did anything wrong. The two teams were just playing by different rules.

That gap is expensive. The problem is that most companies discuss it without putting a number on it.

So I built a framework that settles it with numbers. Six tools, one file.

→ 𝗖𝗼𝗻𝗳𝗹𝗶𝗰𝘁 𝗠𝗮𝗽. Scores every place the two teams collide by frequency and impact. In the sample file the friction adds up to 138 out of 320, so you know where to start.
→ 𝗦𝗵𝗮𝗿𝗲𝗱 𝗠𝗲𝘁𝗿𝗶𝗰𝘀. The handful of numbers both sides own together, like gross margin, average discount, and cash collected versus invoiced. Neither team can move them alone.
→ 𝗖𝗿𝗲𝗱𝗶𝘁 𝗟𝗶𝗺𝗶𝘁𝘀. Sets each limit by a scored rule, not by whoever pushes hardest. It tells you to increase, hold, or reduce.
→ 𝗣𝗮𝘆𝗺𝗲𝗻𝘁 𝗧𝗲𝗿𝗺𝘀. Prices payment term deviations before approval. A €250k deal moving from 45 to 90 days adds a €2,466 cost.
→ 𝗜𝗻𝗰𝗲𝗻𝘁𝗶𝘃𝗲 𝗗𝗲𝘀𝗶𝗴𝗻. Pays on the full outcome. Revenue, margin, cash collected, and forecast accuracy all carry weight, so nobody wins a bonus by giving away the P&L.
→ 𝗔𝗰𝘁𝗶𝗼𝗻 𝗣𝗹𝗮𝗻. 15 concrete moves, each with an owner and a status. Quick wins first, structural fixes next, incentive changes last.

Download it, run a few of your own deals through it, and bring numbers to the next terms conversation.

If you want this Excel framework, just drop a comment and I’ll send it to you.
(Important: follow me so I can DM you!)

[Kirk Borne @KirkDBorne]

Download from the link in the post below ⤵️

[Kirk Borne @KirkDBorne]

💥Powerful book! ➡️ “Quantitative Portfolio Management: The Art and Science of Statistical Arbitrage” 📈

🌟Available at https://t.co/C2DR8rWxdb

[Nicolas Boucher @BoucherNicolas]

You don't need to be technical to build an executive dashboard in Claude.

You need to know the right ask: "Create a KPI scorecard with revenue, margins, and growth metrics."

100 hacks, all specific prompts you can copy.

🔖 Save this one.

[Holy Shit @88888fy]

@BoucherNicolas Claude
Please send

[Holy Shit @88888fy]

@BojanRadojici10 Claude

[Holy Shit @88888fy]

@BoucherNicolas Claude

[Ali AlOhali - علي العوهلي @alioh]

👋👋

اشتغلت على أداة بسيطة بأسم "توزيعات".
تساعدك تتابع شركات السوق السعودي حسب العائد على التوزيعات. فيها مقارنة بين الشركات، حاسبة لتقدير العائد المتوقع، وتقدر تبني قائمة أسهمك الخاصة وتشاركها.

حاب تجربوها وتشاركوني ملاحظاتكم 🙏
https://t.co/NaFMk6p0yy

#تاسي #الأسهم_السعودية

[PrivateEquityGuy (Mikk Markus) @PrivatEquityGuy]

New episode: The Masters of Private Equity

And what I learned from studying Joe Rice, Warren Hellman, Tully Friedman and the early masters of the buyout business:

1. The best private equity investors develop something many CEOs can’t: pattern recognition from seeing dozens of companies succeed and fail across multiple industries.

2. Joe Rice understood decades ago what almost every private equity firm talks about today: operational value creation. “Don’t just become good at buying companies. Become good at making companies better.”

3. CD&R’s operating partners weren’t consultants sitting around giving advice. They stepped in as interim CEOs in roughly a third of the firm’s investments. If something went wrong, someone on their side of the table could actually run the company.

4. When CD&R carved Lexmark out of IBM, they gave every employee direct or indirect ownership. They weren’t simply changing the capital structure. They were changing how thousands of people thought about the business.

5. “Do the work before the deal. Go beyond the numbers. Be willing to change quickly. Apply the same scrutiny to yourself that you apply to your investments.”

6. Warren Hellman’s rule: Every potential investment should be considered guilty until proven innocent.

7. Markets repeatedly convince investors that the old rules no longer apply. Hellman learned the opposite: great businesses still have lasting franchises, exceptional managers, strong free cash flow and attractive economics.

8. Think like an owner, not an employee. Hellman inherited a simple idea from his great-grandfather: “I don’t run businesses. I own them.”

9. Hellman and Friedman didn’t immediately raise a fund. They worked together first to find out whether the partnership actually worked. Only then did they ask institutional investors for money.