KODA.AI’s Post

I became a Data Scientist overnight... I was evaluating our sales process and its effectiveness. After discussing it with #chatgpt, the conversation suddenly escalated to a whole new level! 😮😮 ⚠️⚠️ You may want to turn off "Chat history & training" for this ⚠️⚠️ My approach: 0️⃣ Crunch Lost & Won Data 1️⃣ Analyze deals 2️⃣ Identify key patterns in challenges, use cases & insights 3️⃣ Pinpoint areas for enhancement 4️⃣ Develop actionable strategies Surprisingly, this entire process was completed in under an hour. 🚀 Pinpointing specific areas for our product to better align, 🚀 enhancing client engagement and service delivery, 🚀 and devising innovative strategies previously unexplored. Compared to just me, at least a week... Don't forget to segment your analysis for a more extensive search! 🔪 Track lost deals versus won deals 🔪 Dive into specific deal insights 🔪 Utilize qualitative, quantitative, or both types of data 🔪 Integrate with online resources 🔪 Customize output formats like MindMaps 🔪 Compile detailed reports and more Spoiler! If you are unsure about your prompt, follow these golden rules: 💥 Act like a prompt engineer 💥 Review the following prompt [...] 💥 Optimize it to make it better 💥 Ask me any question before proceeding 🌍 This brings to mind the movie "Her", nudging us one step nearer to its reality. Give it a go and thread together your top practices. #Prompt #BusinessIntelligence #DataAnalytics #SalesStrategy

🌟 The Future of Business Analysis: Embracing AI and Data Science 🌟 ◉ If you are a business analyst and you're reading this in 2024 or later, you won't be able to tackle challenges effectively without AI or Data Science knowledge and skills. When I talk about AI, it's not just about using ChatGPT or other chatbots, nor is it about developing AI applications yourself. Instead, you must read, explore, and understand AI domains, methodologies, models, and technologies, as well as real-world applications. ◉ For data, you need to understand data roles, domains, and skills. Additionally, you must be proficient enough to ask the right questions, create visualizations, and provide insightful answers when wearing your business analyst hat. ◉ In conclusion, As a business analyst, I want to adapt to the evolving landscape of AI and Data Science so that I can contribute effectively to my organization and tackle modern challenges. ◉ Acceptance Criteria: ◦ Given that I am a business analyst, when I explore AI domains and methodologies, I should be able to understand their applications in real-world scenarios. ◦ Given that I need to handle data, when I study data roles and skills, I should be able to perform basic data analysis and visualization. ◦ Given the necessity of AI and Data Science in modern businesses, when I apply this knowledge, I should be able to contribute to AI and Data projects within my organization. #BusinessAnalysis #AI #DataScience #CareerGrowth #FutureSkills #TechTrends #Innovation #BACommunity #DigitalTransformation

Data Analysts make the most of these Generative AI Tools  Generative AI is transforming how data analysts work, making processes faster and more efficient. Here’s a breakdown of some essential AI-powered tools and how they can simplify your analytics workflow: 1. ChatGPT (OpenAI) & Gemini (Google):  These conversational AIs are fantastic for generating code snippets, debugging errors, and explaining complex concepts. They can simplify the process of writing SQL or Python scripts, turning vague ideas into actionable queries. Employ these tools for brainstorming analysis plans, automating repetitive tasks, and even simplifying communication by drafting data narratives. 2. Microsoft Copilot for Excel & Power BI: It automate data wrangling, generate DAX formulas, and suggest meaningful visualizations. It even provides data insights using natural language. Seamlessly integrate Copilot with your existing Excel or Power BI dashboards to speed up your analysis and enhance your reporting capabilities. 3. DataRobot: Automates model building, from data preprocessing to hyperparameter tuning. Useful for those who want to explore predictive analytics without manual coding. It analyzes large datasets, run quick experiments, and present predictive insights to stakeholders, even if you’re not a machine learning expert. 4. Tableau GPT & Einstein Analytics (Salesforce): These tools leverage AI to uncover patterns and deliver predictive insights. Tableau GPT allows you to ask questions about your data and receive detailed answers or visualizations. Perfect for enhancing dashboards with AI-driven insights and automating the discovery of data trends. 5. Dataiku: Combines AutoML capabilities with a collaborative data science environment. Facilitates easier data cleaning, modeling, and deployment. Use its visual interface to manage end-to-end data workflows and integrate with Python or R for advanced analysis when needed. 6. AI-Powered Query Builders (e.g., SeekWell, Akkio): Automates SQL query generation and simplifies database interactions. Converts natural language prompts into database queries. Great for quick insights without having to manually write complex SQL, saving time and minimizing errors. Make sure to Use AI as a support tool but continue honing your problem-solving and analytical skills to handle unique challenges and always validate Outputs, review and refine generated code or insights to ensure accuracy. ♻️ Share if you find this post useful ➕ Follow Muhammad Uzair Adamjee for more daily tips and insights on how to grow in the data field. #GenerativeAI #DataAnalytics #AIForAnalysts #MachineLearning #Productivity #DataScience #AIIntegration

📊 Why Data Matters More Than Ever in Today’s World : In a world where every click, swipe, and interaction generates data, it’s clear: data isn’t just numbers—it’s a powerful asset. When analyzed effectively, data reveals insights that drive smart decisions, boost efficiency, and foster innovation. Businesses across industries leverage data to understand customer behavior, optimize processes, and predict future trends. But who’s behind this transformation of raw data into actionable insights? Here’s a quick look at some core data-focused roles and their unique responsibilities: 🔹 Data Analyst – These professionals are storytellers with data. They analyze datasets, identify patterns, and present insights that help businesses make informed decisions. Think of them as detectives uncovering trends and helping organizations take actionable steps. 🔹 Data Scientist – Data scientists take data analysis to the next level. They build complex models, often using machine learning, to predict future outcomes and answer complex business questions. Their work bridges the gap between data analysis and predictive analytics, bringing proactive insights to the forefront. 🔹 Data Engineer – Behind every data-driven insight is a robust data infrastructure. Data engineers are the builders who design, construct, and maintain data pipelines, ensuring that clean and reliable data is accessible to analysts and scientists. They handle the technical backbone of data operations. 🔹 Business Intelligence (BI) Analyst – BI Analysts focus on transforming data into visuals and dashboards that communicate insights at a glance. They often work with tools like Tableau and Power BI, enabling quick, data-informed decisions across all business levels. 🔹 Machine Learning Engineer – These specialists bring advanced algorithms and models into production. They build and deploy machine learning models that can predict trends, recommend products, or automate complex decision-making. 🤖 Can AI Replace These Jobs? Not Entirely. While AI can enhance data analysis and automate certain processes, it cannot fully replicate the creativity, domain expertise, and strategic thinking that data professionals bring to the table. The human touch—understanding context, asking the right questions, and interpreting nuanced insights—remains essential. AI is a tool that amplifies human capabilities, but it can’t replace them entirely. As we move forward, data-driven roles will continue to be vital, balancing the strengths of AI with human insight to create truly impactful solutions. #DataScience #DataJobs #DataAnalyst #AI #MachineLearning #DataEngineer #BusinessIntelligence #CareerInData #jobs #tech 👇 Image was generated using ChatGPT

🚀 **Data Science in 2024: Navigating the Evolving Landscape** 🚀 As we dive into 2024, the data science landscape reveals its new contours, shaped by historical shifts and the latest technological advancements. Let's unwrap the journey from the boom of 2020 to the more specialized, AI-driven world we navigate today. 🔍 **From Boom to Specialization:** The COVID-19 pandemic catapulted many industries online, spiking a 50% increase in demand for data science across healthcare, tech, and finance. The era was marked by ample opportunities for data science enthusiasts. Post-pandemic recalibrations led to a significant shift, from mass hiring to mass layoffs, touching on all corners of the tech world, especially impacting data science and engineering roles. 🤖 **AI's Rising Influence:** The data science domain saw a pivot towards specialized roles such as machine learning engineers and data engineers, moving away from the generalist data scientist. Tools like ChatGPT have not only made AI more accessible but have also streamlined data science workflows, ushering in an era of efficiency and automation. 📈 **The 2024 Landscape:** The stabilization of the job market brings a fresh breeze of opportunities, now skewing towards experienced professionals in specific niches. Python and SQL reign supreme, signaling the undeniable importance of programming skills. The influence of AI is undeniably reshaping roles, making it imperative for professionals to adapt and evolve. 🎯 **Challenges Ahead:** Demonstrating value and ROI remains a pivotal challenge. Specialization, embracing powerful AI tools, and the need to stay abreast with technological developments are the cornerstones for success in this dynamic field. 💡 In conclusion, data science is a field in constant flux, morphing with technological advancements and market demands. The key to thriving? Stay adaptable, lean into specialization, and always be prepared to prove your worth. 👥#DataScience #AI #MachineLearning #TechnologyTrends #CareerDevelopment

🚀 Exploring the Potential of Power BI and OpenAI: Towards Smarter Data Analysis! 🚀 I am thrilled to share a project we are working on: the integration of Power BI APIs and OpenAI to interpret DAX queries on published models. This solution enables natural language analysis based on data materialized through DAX virtual tables. Here's how it works: ▪ The result of the DAX query is sent to ChatGPT via API along with a customized prompt. ▪ ChatGPT interprets the data and generates the email content. ▪ The email is sent with the automatically generated content, ensuring reliable calculations thanks to the integration with Power BI's semantic model. 🔄 The project is still under development, but the initial results are already promising and pave the way for many future advancements! 🌐 📈 Want to learn how this technology can be applied to your business? Follow me here on LinkedIn and check out the Kubisco page to stay updated with the latest news! 📝 For practical implementations or further information, feel free to contact us at [email protected]. #PowerBI 🌐 #OpenAI 🤖 #Automation #BusinessIntelligence #Kubisco 💡 #Innovation #DAX #API 🔧 #DataScience #MachineLearning 📊 #AI #DataAnalysis

Hello Professionals, Please share resume at [email protected] Role: Salesforce Prompt Engineer (AI chatbots) Location: Remote   Min. Experience: 10+ years   Required skillset: 1. SF, Promopt, Einstein, LWC, Apex   Job summary As a Salesforce Prompt Engineer at Client , you will be responsible for developing, testing, and refining AI-generated text prompts to enhance our Salesforce Einstein AI capabilities. You will collaborate with product teams, data scientists, and content creators to align prompts with company goals and user needs, continuously improving prompt quality and performance. Staying updated with the latest AI and machine learning developments, you will optimize text prompts based on feedback from colleagues, users, and stakeholders. Required Skills Salesforce Prompt Engineer: A Prompt Engineer is responsible for developing, testing, and refining AI-generated text prompts. They work with product teams, data scientists, and content creators to align prompts with company goals and user needs. They also continuously improve prompt quality, performance, and the overall AI prompt generation process. Working collaboratively with cross-functional teams to discuss product development, identify uses of Salesforce Einstein AI, and figure out ways algorithms can make workflows more efficient. Design, create, and refine prompts for Large Language Models (LLMs) utilizing your expertise in Machine Learning. Testing text prompts to make sure they are yielding the desired outcome. Develop effective AI interactions through proficient programming and utilization of playgrounds. Employ techniques to guide and enhance model responses. Integrating AI chatbots, image generators, and coding platforms into the company’s workflows efficiently. Optimizing text prompts based on feedback from colleagues, users, and key stakeholders. Staying up to date with the latest developments in AI and machine learning but not limited to (NLP, Intent Recognition, Entities, Dialogue Flow, Training Data, Context)   Jenson Sebastian Karan Saxena

Excel + ChatGPT: Like Chocolate Cake and Ice Cream, But Better. (A quick guide on how to add ChatGPT functionality to Excel at the end) A groundbreaking partnership is emerging in business analytics. The time-tested spreadsheet titan, Microsoft's Excel, joins forces with OpenAI's ChatGPT, the AI language model powerhouse. The Future of Business Intelligence: This powerful combination enhances productivity and democratizes data analysis, making advanced insights accessible to all levels of an organization. Intuitive Data Interpretation: Complex Excel datasets are transformed into clear, actionable insights through ChatGPT's natural language explanations. Automated, Intelligent Reporting: Real-time data updates in Excel trigger ChatGPT to generate comprehensive, plain-language reports instantly. Conversational Data Queries: Interact with your Excel data using natural language and receive instant, detailed responses from ChatGPT. Users report a 95% reduction in time spent on data interpretation tasks when using ChatGPT alongside Excel, potentially turning hours of work into minutes. Integration of ChatGPT with Excel workflows has been shown to decrease formula errors by up to 80%, significantly improving data accuracy and reliability. Companies utilizing ChatGPT for Excel-related tasks have reported a 300% increase in the number of reports generated per day, drastically improving overall productivity. 92% of non-technical staff report being able to understand complex Excel data when explained by ChatGPT, democratizing data analysis across organizations. Business analysts using ChatGPT for Excel-related queries resolve issues 15 times faster on average, dropping resolution times from hours to minutes. Here is a quick guide on how to add ChatGPT functionality to Excel: Use an API Connection: Sign up for an OpenAI API key In Excel, go to Developer > Visual Basic Create a new module and add VBA code to connect to the ChatGPT API Create functions to send requests and receive responses Use a Third-Party Add-In: Search for "ChatGPT for Excel" add-ins in the Microsoft AppSource Choose an add-in with good reviews Install the add-in directly into Excel Use Power Query: In Excel, go to Data > Get Data > From Other Sources > Blank Query In the Power Query Editor, use M code to connect to the ChatGPT API Create custom functions to interact with ChatGPT Use Office Scripts: Go to the Automate tab > New Script Write a TypeScript script to connect to the ChatGPT API  Create functions to send data to ChatGPT and return responses Use Power Automate: Create a flow that connects Excel with the ChatGPT API Trigger the flow based on Excel events or manually Configure the flow to send Excel data to ChatGPT and return responses #ExcelPlusChatGPT #BusinessIntelligence #ChatGPTAPI #DemocratizesDataAnalysis #ActionableInsights #PowerAutomate

Imagine...you could have a conversation with your data without knowing about a specific tool.   Recently, OpenAI introduced enhancements to its “Data Analyst” GPT, adding features like interactive tables and charts and integration with Google Drive and Microsoft OneDrive. As a Data and BI enthusiast and project manager in this field, I’m highly excited about these developments because they’re paving the way for a future where data analysis is as intuitive as having a conversation. 🔍💬   These new features allow users to explore and interact with data using natural language, eliminating the need for deep technical expertise of a tool. From loading datasets to generating and customizing visualizations, ChatGPT is breaking down barriers and making data analysis more accessible for everyone. 📊🚀   However, there’s still work to be done — like improving accuracy, stability, handling larger datasets, and offering more interactivity and flexibility. Looking ahead, it would be incredible to see ChatGPT directly connect to backend systems like SQL Server, Snowflake, or other databases, enabling even more seamless data exploration and analysis. 🔗💡   The direction we're heading in is exciting, and I can't wait to see how these tools reshape the way we analyze data and make decisions over the next couple of quarters (yes, it will still need some time, but the direction is promising).   And with out-of-the-box tools like Microsoft Power BI Copilot, Pyramid Analytics, Qlik, Tableau, and others also racing to add natural language features to their products, are we witnessing the rise of a new competitor in the (Analytics / BI) market? 😉✨ #DataAnalysis #AI #ChatGPT #BusinessIntelligence #DataVisualization #OpenAI

🚀 Exciting News! I'm Diving into the "ChatGPT Code Interpreter" Course on Coursera by Jules White! 🚀 Hey, LinkedIn fam! 🌟 I’m currently exploring something game-changing for data analysts and anyone who loves data: the ChatGPT Code Interpreter! Imagine taking raw data, uploading it, and instantly getting deep, actionable insights. That’s what Code Interpreter does—and it’s about to transform how I work with data! 👉 What is ChatGPT Code Interpreter? Think of it as your personal data scientist! 🎩👩💻 It’s a powerful tool within ChatGPT that processes your data files and can generate analyses, visualizations, and even predictive insights. You upload a dataset, type in what you want, and it does the heavy lifting, from running calculations to creating interactive charts. 🌐📊 🔍 My Favorite Use Case: Finding Optimal Sales Times with Heatmaps! As someone who juggles both customer service and data analysis, I’m always looking for ways to optimize product availability. Here’s where Code Interpreter steps in: it can create 10-minute interval heatmaps to show peak sales periods throughout the day! This kind of analysis helps me understand when to bake more items and when to pull back, reducing waste and increasing efficiency. 🍞💸 Imagine being able to instantly visualize the busiest times at work and adjust inventory and staffing accordingly! 🛠️ Here’s How You Can Do It Too: 1. Upload Your Sales Data – For instance, a CSV file with columns for Date, Time, Product, Quantity, and Sales Price. Code Interpreter can handle this easily. 2. Input This Prompt in Code Interpreter: "Create a heatmap for my sales data, showing sales activity in 10-minute intervals throughout the day. I want to see peak and low-demand times." 3. Output – Code Interpreter will generate a beautiful heatmap that highlights high and low sales intervals, helping you see trends and optimize inventory! Why This Use Case is a Game-Changer: -> Saves Time ⏰: No more manual sorting or guesswork. -> Reduces Waste 🌱: Know exactly when to prep fresh items, reducing leftovers. -> Maximizes Profit 💸: Meet demand peaks with just the right amount of product. Why Should You Try It? For anyone in retail, food service, or product management—this is a goldmine of insights! It helps you make data-backed decisions on the fly and makes your job easier and more impactful. Plus, it’s fun watching the Code Interpreter bring your data to life! Let’s make data work for us, not the other way around! 💥 If you’re as excited as I am, give Code Interpreter a try and let me know your experience! #DataAnalysis #AI #MachineLearning #ChatGPTCodeInterpreter #DataDriven #Coursera #ProductivityHack