Poornima Ramaswamy’s Post

📍Let's dive into the world of graphs and numbers togethers as we embark on a data driven journey.📈🛣️ *EDIFY* #Beginningtoday #edify #analyticslearning #xrational #newstart #frombasics XIME Chennai - Official

Key Learnings from the Supercell Data Analytics Workshop. On Monday, I enjoyed taking part in discussions on Data Engineering with Romulo Carvalho, AI & Data Analysis with Yasin Hatiboğlu and Ayush Gupta, and hiring process with Hotloo X.. If you're curious about game data like me, here are some fundamental things you can use when working in the games industry: 1️⃣ Which KPIs in focus? DAU (daily active users), MAU (Monthly active users), Daily Playtime, Daily Amount of Playing Sessions, New Users, Daily Revenue, ARPDDAU (Average Revenue Per Daily Active User), Daily payments. ✏ Insights: — A benchmark for DAU/MAU ratio in the games industry is around 15% - this indicates a healthy game. If it's around 5%, it's time to consider changes. — Interestingly, even events like Eurovision can affect DAU, alongside seasonal trends. 2️⃣ What does the AB Test Lifecycle look like? —> Idea —> Hypothesis —> Plan(Build) —> Test —> Analyse REPEAT ✏ Example Hypothesis: Decreasing the game difficulty will not improve key metrics. 3️⃣ What qualities are important for a candidate? — Hunger to make the world a better place. — Independence and responsibility. — Teamwork and curiosity. A huge thank you to Supercell and Startup Refugees for organising this event. The experience has left me with even more questions and curiosity about data in games, which is fantastic!

📈 Say hello to seamless data visualization with in2in global's fully automated self-service solution! No coding or technical skills required 💻 Stay ahead of the game with our advanced data analytics services and make informed decisions for your business. Try out our self-service data viz solutions today and see the difference it can make for your company's success 🌟 #dataanalytics #datavisualization #analytics #business #services #dataviz #automationtesting #selfserviceanalytics #solutions #helps #startup #startupindia #advancedtechnology

Get ready for an electrifying session at India's largest Data Science community event, 𝐊𝐚𝐠𝐠𝐥𝐞 𝐃𝐚𝐲𝐬! 🎉 We'll be taking the stage to discuss "𝐆𝐞𝐧𝐀𝐈 𝐱 𝐃𝐚𝐭𝐚 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭: 𝐅𝐫𝐨𝐦 𝐓𝐚𝐛𝐥𝐞 𝐭𝐨 𝐓𝐫𝐞𝐧𝐝𝐬." 🌟 Dive into the dynamic world of data and uncover how rock-solid data architecture remains the bedrock of successful AI implementations in this rapidly evolving era. 📊 #KaggleDays #GenAI #DataArchitecture #DataScience #AIRevolution #GenAI

Are you eager to uncover hidden patterns in data, create compelling visual stories, or make strategic data-driven decisions? I can't wait to use these new skills to drive impactful insights and shape informed decisions in my data journey! #alx , Data driven Making, #alx AICE

Is AutoML Replacing Data Scientists? Short answer: No Data Scientists are going to exist. AutoML has some people terrified that it'll phase out data scientists. But fear not, fellow data lovers - your skills will forever be in demand. Sure, AutoML is a fantastic tool. It automates the data preparation process and builds models. But it's still far from perfect. Data Scientists, on the other hand... 1) Understand business 2) Can fix problems without needing code 3) Data can be cleaned manually if needed. 4) They can fill in the gaps where AutoML falls short. There is no doubt that AutoML won’t replace Data scientists. What are your thoughts on AutoML and the future of Data Scientists? Can AutoML eventually replace Data Scientists? Drop your thoughts in the comments section below. #AutoML #Datascientist #Technology #UpSkill #Carrer

🚀 Embrace the Future with Process Automation in Data Engineering & Data Science! 🚀 In the ever-evolving landscape of data engineering and data science, process automation is becoming not just a luxury, but a necessity. This involves leveraging technology to automate repetitive tasks, allowing human intellect to focus on more strategic and innovative endeavors. Here's why it's changing the game: 1. **Increased Efficiency**: Saves invaluable time and minimizes errors, boosting productivity. 2. **Consistency**: Ensures tasks are executed the same way every time, eliminating human error. 3. **Scalability**: Allows handling of exponentially more data and tasks, supporting business growth. 4. **Improved Accuracy**: Follows exact instructions, increasing the reliability of outcomes. ### Key Use Cases: - **Data Pipeline Automation**: Consistent and efficient data processing. - **Test Automation**: Speeds up software testing and bug identification. - **Data Labeling & Annotation**: Enhances machine learning models with precise data input. The journey to picking the right tools and strategies for your needs might seem daunting, but the payoff is immense. At our company, InnoBotZ, we've witnessed firsthand the transformative impact of automated data systems, enhancing not just operational efficiency but also fostering a culture of innovation. 🤔 Have you considered integrating process automation into your data workflows? What challenges and successes have you encountered? Let's discuss the future of automation in data science and how we can leap forward efficiently! 🌟 #ProcessAutomation #DataScience #DataEngineering #InnoBotZ #TechInnovation #FutureOfWork #AutomationTech

Discover the future of data management with AI assisted DataOps. www.quantumics.ai 💻 Workspace Create domain-specific project workspace. ⏮ Data Preparation Wrangle data for analysis by simply adding rules in a drag-drop fashion. 📅 Data Governance Ensure high quality through the complete lifecycle of your data. 📼 Dataset Access to the relevant data in a timely fashion. 👨🔬 Data Engineering Integrate and join variety of datasets for consistent data workflow. 〰 Dashboard Slice and dice your data for actionable insights. 🥠 Data Profile Instant data profiling & statistical analysis. 🚗 Automation Automate your jobs as on when needed. #datanalysis #dataengineer  #data #quantumics #jarvis

It is exciting to see the application of GenAI in business intelligence, reporting, and analytics. However, this underscores the importance of strong data governance, data quality, data cataloging, and data warehousing. It highlights the crucial role of data engineers in this age of GenAI. #dataengineer

I appreciate the opportunity to discuss Indus Net Technologies (INT.) transformative contributions to the Data Science field, showcasing our innovative approaches and commitment to enhancing businesses’ data intelligence portfolios. Special thanks to The Interview World for the engaging conversation on our passion and endeavors. #consultation #indusnet #dataanalytics #datascience #transformation Dipak Singh Devpriya Basu Sreejoni Das Santanu Mukherjee