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Exploratory Data Analysis (EDA) isn’t just a step – it’s a philosophy of letting data reveal its secrets. In 2024, with AI dominating conversations, EDA remains the anchor of trustworthy analytics. 1. The EDA Philosophy (Tukey’s Legacy) Core Principles: 2024 Update: …
The OSEMN framework (Obtain, Scrub, Explore, Model, iNterpret) provides a battle-tested structure for data science projects. Used by 72% of top Kaggle competitors, this 5-step approach ensures nothing gets overlooked. 1. Obtain: Data Acquisition Modern Sources: Pro Tip: Always document data provenance – …
Used by 85% of Fortune 500 data teams, the CRISP-DM process (Cross-Industry Standard Process for Data Mining) remains the gold standard since 1996. Here’s why it’s still relevant in 2024: The 6 Phases Explained 1. Business Understanding 2. Data Understanding 3. Data Preparation (60% of …
structured vs unstructured data? 80% of enterprise data is unstructured (IBM), yet most analytics tools are built for structured formats. Understanding these data types is crucial for modern analytics. 1. Key Characteristics Feature Structured Data Unstructured Data Format Tables (SQL), CSV …
KPI design principles! Not everything that counts can be counted – but a well-designed KPI should be both measurable and meaningful. Here’s how to create KPIs that drive action, not confusion. 1. Aligned to Business Goals (The Golden Rule) 2. Actionable (Triggers Decisions) …
Poor data quality costs businesses $12.9M annually (Gartner). Understanding core data quality dimensions – accuracy, completeness, and timeliness – is the first step to fixing it. 1. Accuracy: Is Your Data Correct? 2. Completeness: Is All Data Present? 3. Timeliness: Is Data Up-to-Date? Data …
The DIKW Pyramid is a framework that shows how raw data transforms into actionable wisdom. Used in analytics, business, and AI, it helps organizations make better decisions. 1. Data (The Foundation) 2. Information (Organized Data) 3. Knowledge (Applied Information) 4. Wisdom (Strategic Use) DIKW Pyramid …
Google Data Studio is the perfect way to create professional dashboards for free. In this guide, you’ll learn how to turn raw data into interactive reports—no coding required! (Visual, step-by-step tutorial with actionable tips.) Why Use Google Data Studio? Google Data …
Introduction Python is the #1 programming language for data analytics (IEEE Spectrum 2024). Its simplicity and powerful libraries make it perfect for cleaning, analyzing, and visualizing data. This guide covers:✔ Why Python for data analytics?✔ Essential Python libraries (Pandas, NumPy, Matplotlib)✔ How to install and set up …
Introduction Choosing between Tableau vs Power BI is a common dilemma for data analysts and businesses. Both tools dominate the business intelligence (BI) market, but they cater to different needs. This 2024 comparison will help you decide by analyzing:✔ Pricing & Licensing✔ Ease of Use✔ Visualization Capabilities✔ Data Connectivity …
