Training & Development

A learning culture is not built by offering more training. It emerges where curiosity, connection, and purpose intersect. Andrew Barry, in The Curious Lion, describes learning culture as a lotus where several forces overlap. I find this framing helpful because it moves the conversation beyond HR programs and into the fabric of the organization. At the individual level, there is curiosity. People must feel invited to ask questions, challenge assumptions, and explore. Without individual curiosity, learning remains compliance. At the organizational level, there is mission. Learning needs direction. When people understand what the company stands for and where it is going, their curiosity becomes focused rather than scattered. At the relational level, there is human connection. Learning accelerates in environments where people feel safe to speak, experiment, and reflect together. The fourth circle is continuous learning. Learning must be ongoing, not episodic. Not a workshop, but a way of operating. Continuous learning ensures that curiosity, mission, and connection reinforce each other over time rather than fading after the latest initiative. When these circles overlap, deeper elements emerge: Shared vision aligns effort. Shared experiences create collective memory. Shared assumptions shape how reality is interpreted. Shared stories transmit meaning across generations. At the center sits what we call learning culture. Not an initiative, but a pattern of how people think, relate, and evolve together. The question for leaders is not, “Do we offer learning opportunities?” It is, “Do curiosity, mission, and connection truly reinforce each other continuously in our organization?” That is where learning becomes cultural rather than occasional.

Disclosing the full list of datasets used to train IBM LLMs Granite 3.0. This is true transparency - no other LLM provider shares such detailed information about their training datasets. WEB Data - FineWeb: More than 15T tokens of cleaned and deduplicated English data from CommonCrawl. - Webhose: Unstructured web content in English converted into machine-readable data. - DCLM-Baseline: A 4T token / 3B document pretraining dataset that achieves strong performance on language model benchmarks. CODE - Code Pile: Sourced from publicly available datasets like GitHub Code Clean and StarCoderdata. - FineWeb-Code: Contains programming/coding-related documents filtered from the FineWeb dataset using annotation. - CodeContests: Competitive programming dataset with problems, test cases, and human solutions in multiple languages. DOMAIN - USPTO: Collection of US patents granted from 1975 to 2023. - Free Law: Public-domain legal opinions from US federal and state courts. - PubMed Central: Biomedical and life sciences papers. - EDGAR Filings: Annual reports from US publicly traded companies over 25 years. MULTILINGUAL - Multilingual Wikipedia: Data from 11 languages to support multilingual capabilities. - Multilingual Webhose: Multilingual web content converted into machine-readable data feeds. - MADLAD-12: Document-level multilingual dataset covering 12 languages. INSTRUCTIONS - Code Instructions Alpaca: Instruction-response pairs about code generation problems. - Glaive Function Calling: Dataset focused on function calling in real scenarios. ACADEMIC - peS2o: A collection of 40M open-access academic papers for pre-training. - arXiv: Scientific paper pre-prints posted to arXiv. Full author acknowledgement can be found here. - IEEE: Technical content from IEEE acquired by IBM. TECHNICAL - Wikipedia: Technical articles sourced from Wikipedia. - Library of Congress Public Domain Books: More than 140,000 public domain English books. - Directory of Open Access Books: Publicly available technical books from the Directory of Open Access Books. - Cosmopedia: Synthetic textbooks, blog posts, stories, and WikiHow articles. MATH - OpenWebMath: Mathematical text from the internet, filtered from 200B HTML files. - Algebraic-Stack: Mathematical code dataset including numerical computing and formal mathematics. - Stack Exchange: User-contributed content from the Stack Exchange network. - MetaMathQA: Dataset of rewritten mathematical questions. - StackMathQA: A curated collection of 2 million mathematical questions from Stack Exchange. - MathInstruct: Focused on chain-of-thought (CoT) and program-of-thought (PoT) rationales for mathematical reasoning. - TemplateGSM: Collection of over 7 million grade-school math problems with code and natural language solutions. BOOM!

Master the core SQL commands that drive 80% of tasks. This post focuses on practical, real-world applications of SQL for maximum impact. Fundamental SQL Commands 1. 𝗦𝗘𝗟𝗘𝗖𝗧: Retrieving specific data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚏𝚒𝚛𝚜𝚝_𝚗𝚊𝚖𝚎, 𝚕𝚊𝚜𝚝_𝚗𝚊𝚖𝚎, 𝚎𝚖𝚊𝚒𝚕 𝙵𝚁𝙾𝙼 𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛𝚜;    2. 𝗪𝗛𝗘𝗥𝗘: Filtering results        𝚆𝙷𝙴𝚁𝙴 𝚙𝚞𝚛𝚌𝚑𝚊𝚜𝚎_𝚍𝚊𝚝𝚎 >= '𝟸𝟶𝟸𝟹-𝟶𝟷-𝟶𝟷' 𝙰𝙽𝙳 𝚝𝚘𝚝𝚊𝚕_𝚜𝚙𝚎𝚗𝚝 > 𝟷𝟶𝟶𝟶;    3. 𝗚𝗥𝗢𝗨𝗣 𝗕𝗬: Aggregating data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚙𝚛𝚘𝚍𝚞𝚌𝚝_𝚌𝚊𝚝𝚎𝚐𝚘𝚛𝚢, 𝚂𝚄𝙼(𝚜𝚊𝚕𝚎𝚜_𝚊𝚖𝚘𝚞𝚗𝚝) 𝙰𝚂 𝚝𝚘𝚝𝚊𝚕_𝚜𝚊𝚕𝚎𝚜    𝙵𝚁𝙾𝙼 𝚜𝚊𝚕𝚎𝚜    𝙶𝚁𝙾𝚄𝙿 𝙱𝚈 𝚙𝚛𝚘𝚍𝚞𝚌𝚝_𝚌𝚊𝚝𝚎𝚐𝚘𝚛𝚢;    4. 𝗢𝗥𝗗𝗘𝗥 𝗕𝗬: Sorting data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚙𝚛𝚘𝚍𝚞𝚌𝚝_𝚗𝚊𝚖𝚎, 𝚜𝚝𝚘𝚌𝚔_𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚢    𝙵𝚁𝙾𝙼 𝚒𝚗𝚟𝚎𝚗𝚝𝚘𝚛𝚢    𝙾𝚁𝙳𝙴𝚁 𝙱𝚈 𝚜𝚝𝚘𝚌𝚔_𝚚𝚞𝚊𝚗𝚝𝚒𝚝𝚢 𝙰𝚂𝙲;    5. 𝗝𝗢𝗜𝗡: Combining related data        𝚂𝙴𝙻𝙴𝙲𝚃 𝚘.𝚘𝚛𝚍𝚎𝚛_𝚒𝚍, 𝚌.𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛_𝚗𝚊𝚖𝚎, 𝚘.𝚘𝚛𝚍𝚎𝚛_𝚍𝚊𝚝𝚎    𝙵𝚁𝙾𝙼 𝚘𝚛𝚍𝚎𝚛𝚜 𝚘    𝙸𝙽𝙽𝙴𝚁 𝙹𝙾𝙸𝙽 𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛𝚜 𝚌 𝙾𝙽 𝚘.𝚌𝚞𝚜𝚝𝚘𝚖𝚎𝚛_𝚒𝚍 = 𝚌.𝚒𝚍;    Advanced SQL Techniques 1. 𝗦𝘂𝗯𝗾𝘂𝗲𝗿𝗶𝗲𝘀: Nested queries for complex conditions        SELECT product_name, price    FROM products    WHERE price > (SELECT AVG(price) FROM products);    2. 𝗖𝗼𝗺𝗺𝗼𝗻 𝗧𝗮𝗯𝗹𝗲 𝗘𝘅𝗽𝗿𝗲𝘀𝘀𝗶𝗼𝗻𝘀 (𝗖𝗧𝗘): Simplifying complex queries        WITH monthly_sales AS (    SELECT EXTRACT(MONTH FROM sale_date) AS month, SUM(amount) AS total    FROM sales    GROUP BY EXTRACT(MONTH FROM sale_date)    )    SELECT month, total    FROM monthly_sales    WHERE total > 100000;    3. 𝗪𝗶𝗻𝗱𝗼𝘄 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝘀: Calculations across row sets        SELECT    department,    employee_name,    salary,    RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS salary_rank    FROM employees;    4. 𝗖𝗔𝗦𝗘 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁𝘀: Conditional categorization        SELECT    customer_id,    CASE    WHEN lifetime_value > 10000 THEN 'VIP'    WHEN lifetime_value > 5000 THEN 'Premium'    ELSE 'Standard'    END AS customer_segment    FROM customer_data;    Optimization Tips - Use indexes on frequently filtered columns - Avoid SELECT * and only retrieve necessary columns - Use EXPLAIN ANALYZE to understand query execution plans Learning Strategy 1. Start with simple SELECT queries on a sample database 2. Progress to filtering and sorting data 3. Practice joins with multiple tables 4. Explore advanced techniques with real datasets 5. Participate in online SQL challenges and forums By mastering these SQL commands and techniques, you'll be well-equipped to handle a wide range of data analysis tasks efficiently. Regular practice with diverse datasets will solidify your skills. What's your favorite SQL trick for streamlining data ? Share your insights below!

Louder for the people at the back 🎤 Many organisations today seem to have shifted from being institutions that develop great talent to those that primarily seek ready-made talent. This trend overlooks the immense value of individuals who, despite lacking experience, possess a great attitude, commitment, and a team-oriented mindset. These qualities often outweigh the drawbacks of hiring experienced individuals with a fixed and toxic mindset. The best organisations attract talent with their best years ahead of them, focusing on potential rather than past achievements. Let’s be clear this is more about mindset and willingness to learn and unlearn as apposed to age. To realise the incredible potential return, organisations must commit to creating an environment where continuous development is possible. This requires a multi-faceted approach: 1. Robust Training Programmes: Employers should invest in comprehensive training programmes that equip employees with the necessary skills for their roles. This includes on-the-job training, mentorship programmes, online courses, and workshops. 2. Redefining Hiring Criteria: Organisations should revise their hiring criteria to focus more on candidates’ potential and willingness to learn rather than solely on prior experience or formal qualifications. Behavioural interviews, aptitude tests, and probationary periods can help assess a candidate's ability to learn and adapt. 3. Partnerships with Educational Institutions: Companies can collaborate with educational institutions to design curricula that align with industry needs. Apprenticeship programmes, internships, and cooperative education can bridge the gap between academic learning and practical job skills. 4. Lifelong Learning Culture: Encouraging a culture of lifelong learning within organisations is crucial. Employers should provide ongoing education opportunities and support for professional development. This includes continuous skills assessment and access to resources for upskilling and reskilling. 5. Inclusive Recruitment Practices: Employers should implement inclusive recruitment practices that remove biases and barriers. Blind recruitment, diversity quotas, and targeted outreach programmes can help ensure that diverse candidates are given a fair chance. By implementing these measures, organisations can develop a workforce that is adaptable, innovative, and resilient, ensuring sustainable success and growth.

90% of SQL interviews are built on these patterns. (If you know them, you're already ahead.) SQL interviews aren’t about syntax. They’re about problem-solving and spotting patterns. If you master these 5 patterns, you won’t just answer questions, you’ll impress with clarity and confidence. 1. 𝐉𝐨𝐢𝐧𝐬 & 𝐃𝐚𝐭𝐚 𝐂𝐨𝐦𝐛𝐢𝐧𝐚𝐭𝐢𝐨𝐧 ↳ Know how to connect multiple tables. ↳ Understand inner, outer, and self joins. ↳ Learn how filtering affects results post-join. 2. 𝐀𝐠𝐠𝐫𝐞𝐠𝐚𝐭𝐢𝐨𝐧𝐬 & 𝐆𝐫𝐨𝐮𝐩 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 ↳ Use GROUP BY to uncover trends. ↳ Add HAVING to filter aggregated results. ↳ Go deeper with nested aggregations. 3. 𝐖𝐢𝐧𝐝𝐨𝐰 𝐅𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬 ↳ Rank rows with ROW_NUMBER, RANK, DENSE_RANK. ↳ Compare values using LAG, LEAD. ↳ Partition data for running totals and comparisons. 4. 𝐒𝐮𝐛𝐪𝐮𝐞𝐫𝐢𝐞𝐬 & 𝐂𝐓𝐄𝐬 ↳ Use subqueries to isolate logic. ↳ Break down complexity with CTEs. ↳ Write recursive queries for hierarchy problems. 5. 𝐐𝐮𝐞𝐫𝐲 𝐋𝐨𝐠𝐢𝐜 & 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧 ↳ Control flow with CASE, COALESCE, NULLIF. ↳ Filter efficiently using WHERE, IN, EXISTS. ↳ Optimize performance with indexes and EXPLAIN. You don’t need to memorize everything. Just understand these patterns deeply. That’s how top candidates stand out. Check out the full breakdown on "𝐇𝐨𝐰 𝐭𝐨 𝐀𝐜𝐞 𝐒𝐐𝐋 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬": https://lnkd.in/dVfhtz3V Remember, practice is the key!! I’ve attached a cheat sheet of the most common SQL functions to help you prep faster. ♻️ Save it for later or share it with someone who might find it helpful! 𝐏.𝐒. I share job search tips and insights on data analytics & data science in my free newsletter. Join 13,000+ readers here → https://lnkd.in/dUfe4Ac6

In 2016, as I was just finding my footing as a #diversity, #equity, and #inclusion practitioner, I read an article titled, "Why Diversity Programs Fail" and learned that DEI work was not as straightforward as I had thought. From hundreds of interviews and 30 years of data from more than 800 US companies, sociologists Frank Dobbin and Alexandra Kalev found that the usual DEI interventions—mandatory diversity training, job tests, and grievance procedures—tended to REDUCE the representation of women, Black, Latine, and Asian managers. They detailed the unintended consequences of companies that deploy these intiatives: resentment and backlash, double standards, retaliation and more. There are many DEI initiatives and programs that work. Dobbin and Kalev found that programs that drive intergroup contact and draw on people's desire to look good meaningfully increase representation. Other research has found that standardizing hiring processes reduces hiring discrimination, developing competency criteria mitigates bias on promotions outcomes and feedback, designing the workday so people spend more time with others different from them lowers prejudice and increases belonging, and so on. But the $9.4-billion dollar DEI industry didn't get as big as it did by focusing on these evidence-based practices. Change management takes time, money, and coordination, and employers are often leery to take this approach unless forced. Instead, companies opt for one-off initiatives that they can breadcrumb their way toward the bare minimum—interventions that, unfortunately, tend to be either wholly ineffective or activate hostility and resentment that turn the clock back. As a solo practitioner in the late 2010s who was offering precisely the one-time trainings and workshops that were in-demand, this was all overwhelming to me. I knew that in my heart this work was important, but I also wanted my tactics to be effective. If I wasn't actually reducing discrimination, increasing retention, supporting thriving, then I wasn't doing my job properly. If the impact lay in adjacent work—coaching leaders to understand the role they had to play, working alongside HR teams to design standardized processes to mitigate bias, supporting employee resource groups to set better boundaries, designing impact measurement and infrastructure to support long-term behavior change, and so on—then I had to go in those directions. DEI is far from dead, but we can't pretend that the performative pre-backlash status quo was the best we had to offer. As I spoke to Vox in a recent article, this is our moment to double down on our impact, not just good intentions. We can't just aspire to design workplaces that are fair, accessible, inclusive, and representative for all; we have to actually demonstrate success, measurably and tangibly. Anti-DEI activists peddle fear. We beat them with hope—and the proof that we're building a better world for everyone than they could imagine.

I used to dread negotiations early in my career... Then I realized: Being a strong negotiator isn’t about confrontation. It’s about developing the right frameworks. Here are five game-changing approaches to  negotiate every deal more effectively: 🤝 The 4 Phases Framework (h/t: Roy Lewicki) Great negotiators don’t jump straight to bargaining.  They follow a structured process: • Preparation (lay the groundwork) • Information Exchange (build mutual understanding) • Bargaining (explore potential solutions) • Commitment (secure the agreement) 💪 The BATNA Strategy (h/t: Roger Fisher & William Ury) Your power in any negotiation comes from knowing  your Best Alternative to a Negotiated Agreement (BATNA). It’s your safety net, your source of confidence.  Always define it before you start. 🎯 The Negotiation Matrix (h/t: Lewicki & Hiam) Different situations call for different strategies: • High stakes? Compete. • Building a long-term relationship? Collaborate. • Minor issue? Avoidance might be best. • The relationship is too critical? Accommodate. • Both matter equally? Compromise. 🤔 The Harvard Principled Negotiation Method (h/t: Fisher, Ury & Patton) This is a game-changer: Focus on interests, not positions. Instead of asking what they want, ask why they want it. That’s where real value creation happens. 🎯 The ZOPA Framework (h/t: Fisher & Ury) The Zone of Possible Agreement (ZOPA) is where deals get made. Understanding both sides’ limits helps you identify common ground. Everything else? It's just noise. Key takeaway: The best deals happen when both sides feel heard. And the most successful negotiators aren’t the most aggressive. They’re simply the most prepared. ♻️ Find this valuable? Repost to your network. 💡 Follow Eric Partaker for more on business & leadership.

Most people are taught how to be high performers. But too few are taught how to perform in a team. And that’s a problem, because in most roles, you’re not an individual contributor. You’re part of a larger entity, working with others to build something. Yet, I see founders spend hours refining their product or systems,  But don't devote time to team development. At HomeServe, I approached team performance with purpose,  And it was one of the best decisions I made. Here are 7 tools I’ve used (and still use) to build high-performing teams,  Based on real lessons from building a £4.1bn business: 1️⃣ Start With Why (Simon Sinek) ↳ Before you focus on what or how...get clear on why. WHAT – The product you sell or the service you provide HOW – What makes you different WHY – Your deeper purpose or belief Every great team needs a reason to get out of bed in the morning. 2️⃣ The 70-20-10 Rule (McCall, Lombardo & Eichinger) ↳ How people actually learn on the job: 70% from challenging experiences 20% from coaching and mentoring 10% from formal training Most teams over-invest in training, and under-invest in real development. I'm amazed at how few founders or CEOs have a coach or mentor. 3️⃣ The Trust Triangle (Frances Frei, Harvard) ↳ Trust isn’t built with perks. It’s earned in three ways: Authenticity – Are you real? Logic – Do your decisions make sense? Empathy – Do you care? Without trust, you can’t build speed or loyalty. 4️⃣ The 5 Stages of Team Development (Tuckman Model) 1. Forming – Team gets together 2. Storming – Conflicts surface 3. Norming – Ground rules form 4. Performing – Results roll in 5. Adjourning – Project ends or evolves Don't panic during ‘storming’. It’s necessary friction. 5️⃣ The Johari Window (Luft & Ingham) ↳ Self-awareness is a team sport. Open – You know, they know Hidden – You know, they don’t Blind Spot – They know, you don’t Unknown – No one knows (yet) This helps surface feedback, build confidence, and avoid surprises. 6️⃣ The Energy/Impact Matrix (Inspired by McKinsey) ↳ Map every team member’s impact vs. energy. Use it to: Make smart hiring/firing decisions Spot burnout early Retain high performers High-performing teams don’t tolerate drift. 7️⃣ The RAPID Decision-Making Model (Bain & Company) ↳ High-performing teams make fast, clear decisions. Recommend – Suggest the course of action Agree – Those who must sign off Perform – Executes the decision Input – Provides relevant facts or opinions Decide – Final decision-maker This clears up delays, dropped balls, and blame. Building a great team is about building an environment where talent can actually thrive. I go deeper into team-building in my new book. Order it today: https://lnkd.in/eRYDKXdT ♻️ Repost if you believe team performance should be built, not assumed. And for more on how I scaled teams to build a £4.1bn business, Follow me Richard Harpin.