Latest news with #data analysis
Geeky Gadgets
4 days ago
- Geeky Gadgets
How to Use Sub-Agents Correctly : Essential Guide to Avoid Disaster
Imagine a world where your workflow feels effortless, where tedious research, data analysis, and planning tasks are handled seamlessly, leaving you free to focus on the big picture. Sounds too good to be true? Not if you know how to use sub-agents correctly. These specialized tools are designed to lighten your cognitive load, streamline processes, and optimize resource allocation. But here's the catch: improperly implemented sub-agents can create more problems than they solve, leading to inefficiencies, redundant efforts, and even critical project missteps. The key lies in understanding their strengths and using them effectively. AI Jason explains how to unlock the full potential of sub-agents, from his hands on experience, turning them into your most valuable coding allies. By the end of this guide, you'll discover how to delegate tasks like a pro, ensure seamless context sharing, and avoid the common pitfalls that plague sub-agent workflows. Whether you're managing a complex project or simply looking to optimize your coding environment, mastering sub-agents can transform how you work. You'll learn actionable strategies, from creating specialized sub-agents for tasks like UI design or backend integration to implementing robust context management systems. With insights from AI Jason, this tutorial will empower you to make sub-agents a cornerstone of your workflow. After all, the difference between chaos and clarity often lies in how well you delegate. Effective Use of Sub-Agents What Are Sub-Agents and Why Are They Useful? Sub-agents are specialized components designed to handle tasks such as research, planning, and data analysis, thereby reducing the cognitive load on the parent agent. Their primary function is to gather information, analyze data, and deliver concise insights, allowing the parent agent to make informed decisions without consuming excessive resources. For instance, a sub-agent tasked with researching front-end frameworks can compile a detailed report, allowing the parent agent to focus on implementation or strategic decision-making. By delegating such tasks, you can not only optimize token usage but also improve overall project efficiency. Sub-agents are particularly useful in scenarios where time and resource management are critical, as they streamline processes and ensure that the parent agent remains focused on high-priority objectives. Common Challenges When Using Sub-Agents Despite their advantages, sub-agents can face several challenges that may limit their effectiveness. These challenges include: Inefficient Task Assignment: Sub-agents may struggle with implementation tasks due to their limited understanding of the broader project context, leading to suboptimal results. Sub-agents may struggle with implementation tasks due to their limited understanding of the broader project context, leading to suboptimal results. Context Gaps: Insufficient context sharing between parent and sub-agents can result in incomplete or redundant outputs, reducing overall efficiency. Insufficient context sharing between parent and sub-agents can result in incomplete or redundant outputs, reducing overall efficiency. Redundancy: Without proper coordination, sub-agents may duplicate efforts or produce outputs that fail to align with the overarching project goals. These issues underscore the importance of assigning sub-agents tasks that align with their strengths, such as research and planning, while making sure effective communication and context sharing between agents. Master Sub-Agents and Say Goodbye to Workflow Chaos Watch this video on YouTube. Here are additional guides from our expansive article library that you may find useful on AI Agents. Best Practices for Sub-Agent Utilization To maximize the efficiency and effectiveness of sub-agents, consider adopting the following best practices: Focus on Research and Planning: Assign sub-agents tasks like gathering data, analyzing options, and creating reports rather than direct implementation. This ensures they operate within their area of expertise. Assign sub-agents tasks like gathering data, analyzing options, and creating reports rather than direct implementation. This ensures they operate within their area of expertise. Enable Context Sharing: Use shared context files or centralized systems to provide sub-agents with access to relevant project information, making sure their outputs align with the overall objectives. Use shared context files or centralized systems to provide sub-agents with access to relevant project information, making sure their outputs align with the overall objectives. Document Outputs: Save research findings, analysis, and implementation plans in local or shared files for easy retrieval and future reference. This practice enhances transparency and assists collaboration. For example, if a sub-agent is tasked with evaluating SDK integration options, it should focus on compiling a comprehensive report rather than attempting to implement the integration itself. This approach ensures the sub-agent delivers actionable insights while staying within its designated role. Using Specialized Sub-Agents Creating sub-agents tailored to specific tools, services, or tasks can significantly enhance their efficiency and output quality. Examples of specialized sub-agents include: UI Design Sub-Agent: Specializes in evaluating design frameworks, generating mockups, and recommending design strategies that align with project goals. Specializes in evaluating design frameworks, generating mockups, and recommending design strategies that align with project goals. Backend Integration Sub-Agent: Focuses on analyzing APIs, assessing compatibility, and proposing optimal integration approaches for backend systems. Equipping these specialized sub-agents with relevant documentation, tools, and resources ensures they can perform their tasks effectively. By using their expertise, you can achieve high-quality outputs that contribute meaningfully to the overall project objectives. Strategies for Effective Context Management Effective context management is crucial for making sure sub-agents work cohesively within a project. To achieve this, implement the following strategies: Shared File Systems: Use a centralized file system to store and retrieve task-related context, making sure consistency and accessibility across all agents. Use a centralized file system to store and retrieve task-related context, making sure consistency and accessibility across all agents. Centralized Context File: Maintain a single, regularly updated file documenting project progress, key decisions, and updates. This provides sub-agents with a clear understanding of the overall workflow and minimizes miscommunication. These strategies enable sub-agents to access the information they need while contributing to a unified and efficient project workflow. By fostering seamless communication and collaboration, you can ensure that all agents work toward shared objectives. Practical Example: Sub-Agents in Action Consider a scenario where you are tasked with designing a user interface and integrating an SDK. By assigning sub-agents to these tasks, you can effectively divide the workload: The UI Design Sub-Agent researches current design trends, creates mockups, and documents recommendations for the user interface. researches current design trends, creates mockups, and documents recommendations for the user interface. The SDK Integration Sub-Agent evaluates compatibility, analyzes integration options, and proposes a detailed implementation plan. Both sub-agents should update a shared context file to ensure their outputs align with the overall project objectives. This collaborative approach minimizes redundancy, enhances efficiency, and ensures that all tasks contribute to the broader goals of the project. Future Opportunities for Sub-Agent Optimization While sub-agents are already valuable tools, their current limitations in context sharing and coordination present opportunities for improvement. Future advancements in context-sharing technologies could enable seamless communication and collaboration between parent and sub-agents. These innovations would allow sub-agents to contribute more effectively to complex projects, enhancing their utility and expanding their potential applications. As technology evolves, the integration of advanced context-sharing capabilities could transform sub-agents into indispensable components of modern cloud code workflows. By addressing existing challenges, these advancements would unlock new possibilities for efficiency and innovation in project execution. Media Credit: AI Jason Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Geeky Gadgets
5 days ago
- Business
- Geeky Gadgets
Build a Data Analyst AI in n8n : Automate Your Data Analysis
Imagine this: you're a data analyst juggling endless spreadsheets, generating reports, and distributing insights, all while trying to carve out time for strategic decision-making. Sound familiar? Here's the good news: with the power of automation and AI, you can offload these repetitive tasks to a custom-built AI agent. Using n8n, a versatile workflow automation tool, you can create a solution that not only handles the grunt work but also enhances your productivity and accuracy. In this walkthrough, we'll explore how to build a data analyst AI agent that transforms the way you approach data analysis, so you can focus on what truly matters. Throughout this guide, Rohan Adus will walk you through the essential steps to design, build, and optimize your AI agent. You'll discover how to identify pain points in your workflow, integrate tools like Google Sheets and email services, and use large language models (LLMs) for intelligent data processing. But this isn't just about technical know-how, it's about reimagining your role as a data analyst. By the end, you'll have the blueprint to create an AI agent that doesn't just automate tasks but enables you to think bigger. What could you achieve with more time and fewer bottlenecks? Let's find out together. Building an AI Data Analyst Why Automate Data Analytics? Automation in data analytics is a powerful way to streamline workflows and minimize manual intervention. As a data analyst, you may spend considerable time on repetitive tasks like generating reports, analyzing datasets, and distributing insights. Automating these processes allows you to focus on more strategic decision-making and adapt to the evolving demands of your role. By using AI-powered agents, you can handle routine tasks with greater speed and precision, enhancing both productivity and accuracy. Framework for Building an AI Agent Developing an effective AI agent requires a structured and methodical approach. The following framework outlines the key steps involved: Step 1: Identify Pain Points Begin by identifying the manual tasks you want to automate. For instance, you might need to analyze data from Google Sheets and email insights to stakeholders. Clearly defining these pain points will help you establish the scope and objectives of your AI agent. Begin by identifying the manual tasks you want to automate. For instance, you might need to analyze data from Google Sheets and email insights to stakeholders. Clearly defining these pain points will help you establish the scope and objectives of your AI agent. Step 2: Design Solution Architecture Plan the workflow of your AI agent by outlining the tools and functionalities it will require. Consider how the agent will retrieve, process, and share data. A well-designed architecture ensures that the solution aligns with your goals and operates efficiently. Plan the workflow of your AI agent by outlining the tools and functionalities it will require. Consider how the agent will retrieve, process, and share data. A well-designed architecture ensures that the solution aligns with your goals and operates efficiently. Step 3: Implementation Use n8n to build your AI agent incrementally. Start with a minimum viable product (MVP) to test its core functionalities. Once validated, you can expand its capabilities to address additional tasks and requirements. Guide to Building a Data Analyst AI Agent with n8n Watch this video on YouTube. Learn more about AI automation with the help of our in-depth articles and helpful guides. Core Components of the AI Agent An AI agent relies on several essential components to function effectively. These components form the foundation of its capabilities and ensure seamless operation: Chat Model Select a large language model (LLM) such as OpenAI, Claude, or Gemini. The choice of model should depend on the complexity of tasks and the level of contextual understanding required for your specific use case. Select a large language model (LLM) such as OpenAI, Claude, or Gemini. The choice of model should depend on the complexity of tasks and the level of contextual understanding required for your specific use case. Memory Integration Incorporate memory to enable the AI agent to retain context across interactions. This feature is crucial for delivering coherent and relevant responses, especially in scenarios requiring multi-step workflows or ongoing conversations. Incorporate memory to enable the AI agent to retain context across interactions. This feature is crucial for delivering coherent and relevant responses, especially in scenarios requiring multi-step workflows or ongoing conversations. Tool Integration Connect tools like Google Sheets for data retrieval and email services for communication. These integrations form the backbone of your AI agent's functionality, allowing it to perform end-to-end tasks seamlessly. Practical Implementation in n8n n8n provides a flexible and user-friendly platform for building AI agents. Here's how you can implement your solution effectively: Set Up a Chatbot Interface Create an intuitive interface for interacting with the AI agent. This involves configuring input prompts, defining response formats, and making sure the interface is user-friendly for both technical and non-technical users. Create an intuitive interface for interacting with the AI agent. This involves configuring input prompts, defining response formats, and making sure the interface is user-friendly for both technical and non-technical users. Configure the AI Agent's Brain Use system prompts to define the agent's behavior and integrate memory for context retention. This ensures the agent operates effectively within its defined scope and delivers accurate results. Use system prompts to define the agent's behavior and integrate memory for context retention. This ensures the agent operates effectively within its defined scope and delivers accurate results. Integrate Tools Connect external tools such as Google Sheets for data analysis and email services for automated reporting. These integrations enable the AI agent to handle tasks from data retrieval to communication seamlessly. Best Practices and Considerations To ensure the success of your AI agent, it's important to follow best practices and consider key factors during development: Start Small Begin with an MVP to validate the concept and identify areas for improvement. Iterative development allows you to refine the agent's functionality and address potential issues early in the process. Begin with an MVP to validate the concept and identify areas for improvement. Iterative development allows you to refine the agent's functionality and address potential issues early in the process. Avoid Overengineering Focus on automating tasks that provide the most value. Adding unnecessary complexity can lead to inefficiencies, increased maintenance costs, and reduced usability. Focus on automating tasks that provide the most value. Adding unnecessary complexity can lead to inefficiencies, increased maintenance costs, and reduced usability. Manage API Costs Monitor API usage and implement rate limits to control expenses. This is especially important when using LLMs or other external services that charge based on usage. Monitor API usage and implement rate limits to control expenses. This is especially important when using LLMs or other external services that charge based on usage. Implement Error Handling Design fallback mechanisms to address errors and ensure the agent operates reliably under various conditions. Robust error handling enhances the overall reliability and user experience of your solution. Actionable Steps for Beginners If you're new to automation and AI, consider these actionable steps to get started: Build a simple AI agent using the outlined framework. Focus on automating a single task, such as generating reports or sending emails, to gain hands-on experience. Experiment with n8n and other automation tools to familiarize yourself with their features and capabilities. This foundational knowledge will prepare you for more complex projects in the future. Start with small, manageable projects to build confidence and develop your skills. As you gain expertise, gradually expand the scope and functionality of your AI agent to address more advanced use cases. Media Credit: Rohan Adus Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Geeky Gadgets
5 days ago
- Business
- Geeky Gadgets
Excel Trick For Ranking Values for Accurate Data Analysis : Dense Ranking
Have you ever found yourself frustrated by Excel's inability to handle ties in rankings without creating gaps in the sequence? Imagine analyzing employee salaries or sales performance, only to discover that identical values are ranked inconsistently, throwing off your entire report. This is where the concept of dense ranking comes to the rescue. Unlike standard ranking methods, which often leave gaps after ties, dense ranking ensures that identical values share the same rank while maintaining a seamless ranking order. It's a small tweak with a big impact, offering clarity and fairness in your data analysis. In this guide, Chandoo explains a step-by-step approach to mastering dense ranking in Excel, using powerful functions like `LET`, `UNIQUE`, and `FILTER`. Whether you're tackling performance evaluations, sales reports, or any dataset riddled with duplicate values, these techniques will help you create rankings that are both accurate and intuitive. Along the way, you'll also learn how to retrieve associated data effortlessly and even implement dense ranking without adding extra columns. By the end, you'll not only streamline your workflow but also gain a deeper understanding of how to make Excel work smarter for you. Excel Dense Ranking Guide Understanding Dense Ranking Dense ranking assigns the same rank to identical values and ensures no gaps in the ranking sequence. For example, if two entries share the first rank, the next unique value is ranked second, not third. This approach differs from standard ranking, where gaps appear after ties. Dense ranking is particularly useful in scenarios such as: Salary Analysis: Making sure employees with tied salaries are ranked equally without inconsistencies. Making sure employees with tied salaries are ranked equally without inconsistencies. Performance Evaluations: Accurately ranking individuals or teams with identical scores. Accurately ranking individuals or teams with identical scores. Sales Reporting: Identifying top-performing products or regions without misrepresenting tied results. By addressing ties effectively, dense ranking provides a more accurate representation of your data, making it an essential tool for various analytical tasks. Limitations of Standard Ranking Excel's built-in ranking functions, such as `LARGE` or `RANK`, often fall short when handling duplicate values. For instance, if two employees have the same salary, these functions assign them different ranks, leaving gaps in the sequence. This creates inconsistencies, especially in datasets where ties are common. Dense ranking eliminates this issue by making sure that tied values share the same rank while maintaining a continuous ranking sequence. Excel Trick For Ranking Values Watch this video on YouTube. Expand your understanding of Excel functions with additional resources from our extensive library of articles. Step-by-Step Guide to Creating a Dense Rank Column To implement dense ranking in Excel, you can use a combination of powerful functions. Follow these steps to create a dense rank column: Define Variables with `LET`: Use the `LET` function to define and reuse variables within your formula. This improves readability and reduces redundancy. For example, you can store a range of values or intermediate calculations as variables. Use the function to define and reuse variables within your formula. This improves readability and reduces redundancy. For example, you can store a range of values or intermediate calculations as variables. Extract Unique Values with `UNIQUE`: The `UNIQUE` function identifies distinct values in your dataset, grouping duplicate entries together for ranking purposes. The function identifies distinct values in your dataset, grouping duplicate entries together for ranking purposes. Assign Ranks with `FILTER` and `COUNT`: Combine `FILTER` to isolate values and `COUNT` to determine their rank within the unique list. This ensures accurate ranking even when duplicate values are present. For example, in a dataset of employee salaries, you can create a dense rank column that assigns the same rank to employees with identical salaries. This approach ensures fairness and consistency in your analysis. Retrieving Data Using Dense Rank Once you've established a dense rank system, retrieving associated data becomes straightforward. Here are two key functions to simplify this process: Use `XLOOKUP` for Precise Data Retrieval: The `XLOOKUP` function allows you to find corresponding data, such as employee names or departments, based on their rank. This is particularly useful for associating ranks with specific entries in your dataset. The function allows you to find corresponding data, such as employee names or departments, based on their rank. This is particularly useful for associating ranks with specific entries in your dataset. Handle Multiple Matches with `FILTER` and `TEXTJOIN`: When multiple entries share the same rank, `FILTER` can extract all matching values. You can then use `TEXTJOIN` to combine these values into a single cell, separated by commas, for better readability. For instance, if two employees share the first rank, you can use `FILTER` to list their names and `TEXTJOIN` to display them in a single cell. This method ensures that all relevant data is captured and presented clearly. Dense Ranking Without Adding Extra Columns In some cases, you may prefer not to add a dedicated dense rank column to your dataset. Instead, you can calculate ranks directly within a formula. By combining `LET`, `UNIQUE`, and `LARGE`, you can determine ranks and retrieve associated data in a single step. This approach is ideal for one-time analyses or compact datasets where adding extra columns isn't practical. It allows you to maintain a clean and organized worksheet while still using the benefits of dense ranking. Practical Applications of Dense Ranking Dense ranking has a wide range of applications across various fields. Some of the most common use cases include: Performance Analysis: Rank employees, students, or teams based on scores while addressing ties accurately. This ensures fair evaluations and meaningful comparisons. Rank employees, students, or teams based on scores while addressing ties accurately. This ensures fair evaluations and meaningful comparisons. Sales Reporting: Identify top-performing products, regions, or sales representatives without misrepresenting tied results. Dense ranking provides a clear and accurate picture of performance metrics. Identify top-performing products, regions, or sales representatives without misrepresenting tied results. Dense ranking provides a clear and accurate picture of performance metrics. Data Filtering and Retrieval: Extract specific ranks and their associated data efficiently for reporting or decision-making. This is particularly useful in large datasets where precision is critical. By using dense ranking, you can enhance the accuracy and reliability of your data analysis, making it a valuable tool for professionals in various industries. Optimizing Your Workflow with Dense Ranking Dense ranking is a powerful technique for handling duplicate values in Excel. By using functions like `LET`, `UNIQUE`, `FILTER`, `LARGE`, `XLOOKUP`, and `TEXTJOIN`, you can create efficient workflows that accurately rank data and retrieve associated information. Whether you're analyzing salaries, performance metrics, or sales figures, these methods empower you to work smarter and achieve precise results. Incorporating dense ranking into your Excel toolkit can significantly improve the quality and clarity of your data analysis. Media Credit: Chandoo Filed Under: Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Geeky Gadgets
31-07-2025
- Business
- Geeky Gadgets
Excel Formulas and Functions to Skyrocket Your Spreadsheet Productivity
Have you ever found yourself staring at a sprawling Excel spreadsheet, overwhelmed by rows and columns of data that seem impossible to manage? You're not alone. Despite its reputation as a workplace staple, Excel remains underutilized by many professionals who rely on basic functions while overlooking its true potential. The truth is, mastering a handful of powerful formulas and functions can transform Excel from a simple data entry tool into a dynamic engine for analysis, automation, and decision-making. Whether you're a seasoned analyst or a casual user, understanding how to harness Excel's capabilities can unlock a new level of productivity and precision in your work. In this guide by Simon Sez IT, you'll uncover the essential Excel formulas and functions that every professional should know. From simplifying formula management with named ranges to making data-driven decisions using logical functions, these techniques will help you streamline workflows and reduce errors. You'll also explore how to use conditional formatting to visualize trends, handle formula errors gracefully, and retrieve data efficiently with lookup functions. But this isn't just about learning formulas—it's about mastering the tools that can make your spreadsheets smarter, more intuitive, and tailored to your unique needs. By the end of this report, you'll see Excel not as a chore, but as a powerful ally in solving complex problems and delivering impactful results. Master Intermediate Excel Skills Named Ranges: Simplify Formula Management Named ranges allow you to assign meaningful names to specific data ranges, making your formulas more intuitive and easier to manage. Instead of relying on generic cell references like 'A1:A10,' you can use descriptive names such as 'SalesData.' This approach improves clarity, reduces errors, and enhances collaboration by making your spreadsheets more understandable. To create or manage named ranges, use Excel's Name Manager. For example, instead of writing `=SUM(A1:A10)` to calculate total sales, you can use `=SUM(SalesData)`. This not only simplifies formula management but also ensures that your spreadsheets remain clear and accessible to others working on the same data. Logical Functions: Enhance Decision-Making Logical functions such as IF, AND, and OR empower you to perform calculations based on specific conditions. The IF function, for instance, evaluates a condition and returns one value if the condition is true and another if it is false. For example, you can use a formula like `=IF(Sales>10000, 'Bonus', 'No Bonus')` to determine whether a salesperson qualifies for a bonus. By combining IF with AND or OR, you can address more complex scenarios, such as evaluating multiple criteria for eligibility. These functions are invaluable for tasks like performance tracking, financial modeling, and project planning, allowing you to make informed decisions based on dynamic data. Conditional Formatting: Visualize Data Dynamically Conditional formatting is a powerful tool for highlighting data based on specific criteria, making it easier to identify trends, outliers, or areas requiring attention. For instance, you can automatically color-code overdue payments, flag errors, or emphasize top-performing sales regions. Using formulas within conditional formatting allows you to create dynamic visualizations tailored to your needs. For example, you can highlight cells where sales exceed a certain threshold or where inventory levels fall below a critical limit. This feature is particularly useful for dashboards and reports, where clear and immediate insights are critical for effective decision-making. Essential Excel Formulas and Functions Every Professional Should Know Watch this video on YouTube. Here are more guides from our previous articles and guides related to Excel formulas that you may find helpful. Error Handling: Manage Formula Errors Errors in formulas can disrupt workflows and compromise the accuracy of your data. The IFERROR function provides a practical solution by allowing you to display custom messages or alternative values when errors occur. For example, the formula `=IFERROR(A1/B1, 'Error: Division by Zero')` prevents disruptive error messages and ensures that your spreadsheet remains user-friendly. This approach is especially valuable when working with large datasets or complex calculations, where errors are more likely to arise. By incorporating error handling into your formulas, you can maintain the integrity of your data and improve the overall usability of your spreadsheets. Lookup Functions: Retrieve Data Efficiently Lookup functions such as VLOOKUP, HLOOKUP, and XLOOKUP are essential for retrieving data based on specific criteria. While VLOOKUP searches for data vertically and HLOOKUP searches horizontally, XLOOKUP offers greater flexibility by allowing searches in any direction and addressing many of the limitations of its predecessors. For example, with XLOOKUP, you can retrieve a product's price based on its name, even if the data is unsorted. This function is particularly useful for tasks like inventory management, customer data retrieval, and financial analysis. By mastering lookup functions, you can efficiently access the information you need to make data-driven decisions. Dynamic Data Manipulation: Adapt to Changing Inputs Dynamic formulas such as SUMIF, COUNTIF, and AVERAGEIF enable you to calculate values based on specific criteria. For instance, you can use `=SUMIF(CategoryRange, 'Electronics', SalesRange)` to calculate total sales for electronics. These formulas allow you to analyze data dynamically, adapting to changes in input or user selections. Dynamic data manipulation also involves creating formulas that automatically adjust based on dropdown selections or other user inputs. This capability is crucial for building interactive reports and dashboards, where data must update in real time to reflect changes. By using dynamic formulas, you can create flexible and responsive spreadsheets that meet a wide range of analytical needs. Advanced Techniques: Build Comprehensive Solutions Combining multiple functions allows you to tackle complex problems and create comprehensive solutions. For example, you can nest IF functions within conditional formatting to develop advanced visualizations or use lookup functions alongside error handling for robust data retrieval. Additionally, incorporating dynamic charts and pivot tables into your spreadsheets enhances your ability to present data effectively. These advanced techniques enable you to build professional-grade dashboards and reports tailored to specific business requirements. By mastering these skills, you can transform raw data into actionable insights and deliver impactful results. Practical Applications: Streamline Workflows Excel's versatility makes it an indispensable tool for automating repetitive tasks and improving accuracy. You can use formulas to calculate commissions, bonuses, or performance metrics automatically, saving time and reducing the risk of errors. Aggregating data by categories, such as sales by region or product type, simplifies analysis and supports better decision-making. Creating error-proof spreadsheets with clear outputs ensures smoother collaboration and more reliable results. Whether you're managing budgets, tracking project progress, or analyzing sales performance, these practical applications demonstrate how mastering Excel can enhance productivity and streamline your workflows. Media Credit: Simon Sez IT Filed Under: Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Malay Mail
29-07-2025
- Business
- Malay Mail
Palantir emerges as Trump-era tech favourite, boasting AI tools that ‘kill enemies'
WASHINGTON, July 29 — Palantir, an American data analysis and artificial intelligence company, has emerged as Silicon Valley's latest tech darling—one that makes no secret of its macho, America-first ethos now ascendant in Trump-era tech culture. The company's reach spans the global economy, with banks, hospitals, the US government, and the Israeli military among its ever-expanding client roster. 'We want and need this country to be the strongest, most important country in the world,' Alex Karp, Palantir's CEO, recently declared at a client conference in Palo Alto, California, where AFP was the only media outlet present. In armed conflicts—most notably in Ukraine—Palantir's tools help evaluate potential targets in real-time, using multiple sources, including biometric data and intercepted phone calls. 'I'm super proud of... what we do to protect our soldiers... (using our AI) to kill our enemies and scare them, because they know they will be killed,' the graying, curly-haired billionaire continued, wearing a tight white T-shirt. Washington has been filling Palantir's coffers. In the first quarter, the company received US$373 million from the US government—a 45 percent jump from the previous year—and it's not all miltary spending. This spring, federal immigration authorities (ICE) awarded the company a US$30 million contract to develop a new platform for tracking deportations and visa overstays. 'Like a drug' The company then secured an investment of nearly US$800 million from the US military, adding to the US$480 million contract signed in May 2024 for its AI platform supporting the Pentagon's 'Project Maven' target identification program. This marked Palantir's first billion-dollar contract, elevating it alongside government contracting stalwarts like Microsoft and Amazon's AWS. However, financial results 'are not and will never be the ultimate measure of the value, broadly defined, of our business,' Karp wrote in his letter to shareholders in early May, where he tossed in quotes from Saint Augustine, the Bible and Richard Nixon. 'We have grander and more idiosyncratic aims.' Palantir was founded in 2003 by Peter Thiel—Silicon Valley's preeminent conservative—Karp, and others with CIA backing. The company takes its name from the magical seeing stones in Tolkien's 'Lord of the Rings.' 'Young people would say we're like pure drugs—very expensive, highly sought after... that make you stronger and better,' Karp boasted on stage. Palantir's expanding footprint at the highest levels of government has raised eyebrows. Several members of the Trump administration's 'DOGE' cost-cutting commission, originally headed by Elon Musk, came from the company. Recent reports from The New York Times, Wired, and CNN have detailed secret government projects to create, with Palantir's help, a central database combining data from different federal agencies. Deeply proud This development has created 'a lot of concerns about how that information might be used,' warned Elizabeth Laird from the Center for Democracy & Technology. Palantir maintains it isn't building 'surveillance technology' or a 'central database on Americans.' Unlike most traditional Silicon Valley companies that have kept military projects discreet, Palantir now embraces its defense work openly. Sasha Spivak, director of strategy, said that when she joined Palantir ten years ago, the company kept its sense of purpose behind closed doors. 'Today we're not ashamed, we're not afraid, and we're deeply proud of what we do and our clients,' said Spivak. Some employee groups are pushing back. In early May, 13 former Palantir employees published a letter accusing tech giants of helping to 'normalize authoritarianism under the cover of a 'revolution' led by oligarchs.' They argue that by supporting the Trump administration and DOGE, Palantir has betrayed its stated values of ethics, transparency, and defending democracy. 'When I joined the company... there were many smart, motivated people—that's pretty rare,' said one of the letter's signatories, who wishes to remain anonymous, for fear of reprisal. After months of seeking management explanations about Palantir's collaboration with Israel and ICE, several of these employees resigned. 'They said, 'We're a company that's very responsive to employees,' but people asking about Israel were quickly shut down and told, 'That's what we do—if you don't like it, you can leave,'' the former staffer recalled. Jeremy David, co-director of the Health division, plays down the controversies. 'My daily life is more about nurses and doctors who often hate us at first and are very grateful at the end,' he told AFP at the conference. On stage, Joe Bonanno, head of data analysis at Citibank, celebrated how one operation that previously required 'nine days and sometimes 50 people' now 'takes just a few minutes for one person.' 'Like I said, and like Alex said, I came to dominate, crush and annihilate. So if you're JPMorgan, Merrill Lynch, Morgan Stanley, sorry,' he concluded with a broad smile. Some potential clients quietly admit they don't appreciate the war-like rhetoric, but they see no alternative to Palantir's capabilities. — AFP
