Data Obsession: Storage Models Defined by Workload Type

The Importance of Data Storytelling in Data Science In data science, analyzing data is only part of the job. The real impact comes from communicating insights effectively. Data storytelling helps transform complex data into meaningful insights that decision-makers can easily understand. When data is combined with clear visualization and context, it becomes a powerful tool for better decision-making. #DataScience #DataAnalytics #DataStorytelling #MachineLearning

📚 Data Science for Business — Chapter 3 Takeaways Chapter 3 focused on something fundamental but powerful: how we frame a data problem. 1️⃣ Effective data science starts with clear problem formulation. Before touching data or models, define the target, the decision, and what success looks like. A poorly framed problem leads to poor results — no matter how good the model is. 2️⃣ Translate business questions into prediction tasks. Breaking problems into examples, features, and outcomes makes solutions more structured and measurable. Big takeaway for me: thoughtful problem framing sets the foundation for impactful results. Book: Data Science for Business — Foster Provost & Tom Fawcett 👉 Sharing my learnings chapter by chapter as I continue building business-first data thinking. #DataScience #Analytics #MachineLearning #BusinessIntelligence #LearningInPublic

📚 Data Science for Business — Chapter 4 Takeaways Chapter 4 focuses on predictive modeling and how it supports decision-making. Key takeaway: 1️⃣ Predictions help reduce uncertainty in decisions. The real value of predictive models isn’t just accuracy — it’s how those predictions guide actions and improve business outcomes. What I liked about this chapter is how it keeps bringing the focus back to the same idea: data science matters most when it leads to better decisions. Book: Data Science for Business — Foster Provost & Tom Fawcett 👉 Sharing my learnings chapter by chapter as I continue building business-first data thinking. #DataScience #Analytics #MachineLearning #BusinessIntelligence #LearningInPublic

What is Data Engineering? Data engineering is like being the architect and builder of the roads that data travels on. In simple words, it involves collecting raw data from different sources, cleaning it, organizing it, and making it ready for analysis. Just like how a delivery truck needs good roads to reach your house, data needs pipelines to reach analysts and data scientists. #DataEngineering #DataScience #BigData #Analytics #ArtificialIntelligence #MachineLearning #CloudComputing Read blog in detail

With companies shifting toward data-driven strategies, professionals trained in Data Science are becoming essential assets across industries in the US. #CapitalSoftTechInc #SmartCareer #DataDriven #USOpportunities #TechIndustry #AnalyticsJobs

With companies shifting toward data-driven strategies, professionals trained in Data Science are becoming essential assets across industries in the US. #MULTICLOUDTECHNOLOGIES #SmartCareer #DataDriven #USOpportunities #TechIndustry #AnalyticsJobs

With companies shifting toward data-driven strategies, professionals trained in Data Science are becoming essential assets across industries in the US. #KeshTecINC #SmartCareer #DataDriven #USOpportunities #TechIndustry #AnalyticsJobs

With companies shifting toward data-driven strategies, professionals trained in Data Science are becoming essential assets across industries in the US. #SatoriITSystems #SmartCareer #DataDriven #USOpportunities #TechIndustry #AnalyticsJobs

Who doesn't love data? Let's raise awareness about the importance of data science and management! #lovedata #lovedataweek #tech #learntocode #learnlovecode #codingbootcamp #builderofthings

Webinar Takeaway #2: The Data Quality Checklist and getting inside the mind of a Data Scientist 👩🔬 📈 💡 What are the things that data scientists and business intelligence professionals have to keep in mind when working with reems of disparate datasets and multiple sources of truth when helping their organizations make important decisions in a fast-paced environment? Vision Insights' resident data scientist Erin Davison Medeiros talks about several quality checks that should be happening when ensuring data is usable and representative. When searching for and producing data insights, you get out what you put in. Alyssa Melanson Katie Morgan Scott Horowitz #research #data #quality #datascience #QC #insights #sports #linkedinsports #sportzbiz