Chick-fil-A Corporate Support Center’s Post

Over at uPlanner, we prioritize understanding our clients' needs deeply and improve our offering through experience and tenacity. Sebastian Flores, our Chief Data Officer, captures this essence perfectly. Solving problems in academia isn't just about applying technology; it's about interpreting and modeling solutions that truly address customers’ challenges. This philosophy guides us to deliver tailored and effective solutions that make a meaningful difference. #datascience #academicoperations #artificialintelligence

For our DataProphet team and our partners. It’s been a few months in my new role but I wanted to share some of my thoughts with you: As the new CEO of DataProphet, it is with immense pride and a profound sense of responsibility that I take the reins from our visionary founder, Frans Cronje. Our mission is steadfast and more crucial than ever: to partner with major manufacturers around the globe, leveraging our AI-driven expertise to enable manufacturing excellence to forge a sustainable, efficient future. In the heart of South Africa, we continue to flourish under the expertise of a world-class team – a unique blend of mathematicians, data scientists, software architects, and developers. Together, we have transformed complex theories into tangible solutions, shaping the future of heavy industry. Our goal is simple yet ambitious: to make science real in the physical world of manufacturing. The realm of theoretical possibilities is vast, but our focus is on translating this into practical, impactful applications. By integrating AI into the core of manufacturing processes, we are not just predicting outcomes; we are actively influencing them, making a causal impact that resonates through the entire industry. Data is our most potent ally in this journey. With vast quantities of information at our fingertips, we can measure our impact with precision, ensuring that every step we take is informed, deliberate, and effective. This data-driven approach allows us to continuously refine our strategies, ensuring that our partners always stay ahead of the curve. But at DataProphet, we know that results speak louder than words. Our commitment to excellence is measured in tangible outcomes: increased efficiency, reduced waste, and enhanced productivity. These are the metrics that demonstrate our value over time, the real-world results that matter to our partners and the planet. As we move forward, our vision is clear: to be the bridge between the realms of advanced science and practical manufacturing. We are here to make a difference, to ensure that the future of industry is not only more efficient and profitable but also more sustainable and responsible. Together, we are writing a new chapter in the story of manufacturing, one where AI-driven excellence lights the way. At DataProphet, we are not just predicting the future; we are actively creating it, one innovative solution at a time. #ai #manufacturingexcellence #sustainability #esg

🔍"Any time scientists disagree, it’s because we have insufficient data. Then we can agree on what kind of data to get; we get the data; and the data solves the problem. Either I’m right, or you’re right, or we’re both wrong. And we move on." —Neil deGrasse Tyson 🚀💡 Embracing the power of data-driven decisions in the pursuit of knowledge and understanding. 🌐🔬 #Science #DataDriven #NeilDeGrasseTyson #Knowledge #Collaboration

Effective data-driven transformations need go beyond data & tech! 📣 The change needs happen also on the organisational & people side. Companies need to consider the three pillars at the same time: 1) Organisation: clear responsibilities, efficient processes & (data) ownership, 2) People: user involvement, cross-functional collaboration & targeted upskilling, 3) Technology: high data transparency, availability and quality. (the list goes on 😉) Most importantly, use cases need to have a strong business impact. Only then they can serve as a catalyst to drastically improve the power of an organisation. I am happy to see that at the DATA festival so many passionate Data & Analytics drivers embrace this view. Also I feel confirmed that our Zühlke Group approach to data-driven transformations is helping to find answers to the right questions.

"Thrilled to announce the completion of my latest data science project at Cognifyz Technologies 🚀 Grateful for the opportunity to apply advanced analytics and machine learning techniques to solve real-world challenges. Join us as we dive into the savory world of data exploration, unraveling culinary trends, and mapping restaurant hotspots. 📊🍽️ #datascience #cognifyztechnologies #dataanalytics - Exploring numerical and categorical data to calculate statistical measures and uncover distribution patterns. - Identifying top cuisines and cities with the highest restaurant counts, offering insights into regional culinary landscapes. - Utilizing latitude and longitude data for geospatial analysis, visualizing restaurant locations and investigating correlations with ratings. - Analyzing table booking and online delivery services, comparing ratings and exploring availability across different price ranges. - Understanding restaurant pricing dynamics by identifying common price ranges and computing average ratings for each tier. - Engaging in feature engineering to extract novel insights, enriching the dataset new rating methods and calculating rating ratio depending upon several factors and more....

Greetings connections! I'm thrilled to announce the successful completion of Level 1 tasks at Cognifyz Technologies, where I delved into the captivating world of Data Science. Throughout this journey, my focus was on three pivotal tasks: 📗Task 1: Data Exploration and Preprocessing - Conducted thorough exploration of the dataset to identify its dimensions. - Addressed missing values in each column with appropriate handling techniques. - Executed essential data type conversions for optimal analysis. - Analyzed the distribution of the target variable ("Aggregate rating") to detect any class imbalances. 📘 Task 2: Descriptive Analysis - Calculated fundamental statistical measures (mean, median, standard deviation, etc.) for numerical columns. - Investigated the distribution of categorical variables such as "Country Code", "City", and "Cuisines". - Identified top cuisines and cities boasting the highest number of restaurants. 📙 Task 3: Geospatial Analysis - Visualized restaurant locations on a map utilizing latitude and longitude data. - Explored the distribution of restaurants across various cities or countries. - Investigated potential correlations between restaurant location and its rating. These tasks not only honed my skills but also provided invaluable insights into the intricate landscape of data science. I look forward to applying this knowledge in future endeavors. #cognifyzTechnologies #DataScience #cognifyz #cognifyzTech

"Confessions of Analytics Professionals: The Good, the Bad, and the Data-Driven" 👋 Time for some real talk about analytics. Meet Max, an analyst who's who is going through it at a small startup dot-com. He's not holding back – sharing both the victories and the facepalm moments. We've all been there, right? Grab your coffee ☕ and join Max on a journey into the nitty-gritty. Max's stories will give you fresh perspectives and maybe even a laugh. 🚀 Dive into the messy, enlightening, and always fascinating world of data! Got your own analytics confession? Spill the beans in the comments! Know a fellow data geek who'd vibe with Max? Tag them below! Let's swap stories and keep it real! 📊🔍 #AnalyticsEngineering #dataEngineering #dataliteracy #analytics #dataScience

I first learned about FAIR data in 2019 from Chipo Msengezi, Ruthie Musker and Deborah Yates. Since then, Adrian Philpott, Lucy Brett and I’ve been working with CABI’s EDA team, the Open Data Institute and people from the #AgDev team at the Bill & Melinda Gates Foundation to make these principles practical for improving food security. We will be launching an online “how to do FAIR” later this year. In the meantime adoption of FAIR is slow, and we need solid stats to convince decision-makers. Please, will you share what you have heard? I am really keen to hear stories from the people doing it and reaping the rewards. Case Studies, stats, or lived experience stories - everything is good to receive. Here are the two examples: Efficiency Gains: 20-30% increase in research efficiency and 25% boost in funding efficiency. https://lnkd.in/dDSipkcH Economic Benefits: €10.2 billion annual economic gain in the EU. https://lnkd.in/dkT_rDRi #FAIRForSustainability #FAIR #FAIRData #SoilHealth #FoodSecurity #Sustainability #DataSharing #SoilData #AgTech #Data #DataQuality #DataManagement

Transforming raw data from #poultry samples into comprehensive trends representative of millions of birds each week is a complex mathematical challenge. In the final post of Ancera's Behind the Scenes, our Head of Data Science, Charles Copley describes how Ancera is leading an industry shift from diagnostics to #analytics with accompanying data visualization examples. Read the blog in full at: https://lnkd.in/dHFwbPaU

#CPG at #NRF2024: Helen Davis shares info about how data science sits within Kraft Heinz. Some inside-view fun facts ... 📊 There are 50 data scientists dedicated to her operations organization. 📊 They work as a trio w/their functional leads and IT to feed transactional data into the data lake. 📊 Agile pods go on weekly sprints, reporting out to the cross-functional leadership team on a quarterly basis. ("There has to be some kind of ROI on what we're doing.") 📊 They’re working on a KraftGPT generative AI “Ask Me Anything” app for employees to obtain quick insights into things like, “Why are we selling so much bacon?” #consumergoods #artificialintelligence #generativeAI National Retail Federation