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Data Analytics From Analytics Shiksha

Enroll in Data analytics courses with Analytics Shiksha to Become a data analyst . Our online classes in data analytics range from beginner to advanced and feature hands-on experience with tools such as Python, SQL, Power BI. We provide industry expert designed courses and projects which focus solely on the real-world practicality of learning so that you walk away job ready. Learn, certify and advance your career with detailed Knowledge. Join a community of passionate learners and take our flexible, inspiring data analytics certification courses today. Begin your pathway to be a professional.

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Data Analytics From Analytics Shiksha

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  1. INTRODUCTION TO DATA ANALYTICS Learn Data Analytics with Analytics Shiksha

  2. WHAT IS DATA ANALYTICS? 02 Data Analytics is the process of analyzing raw data to uncover trends, patterns, and actionable insights. • Examples: • Retail: Analyzing customer purchase patterns to personalize marketing. • Healthcare: Predicting patient outcomes through data analysis. • Finance: Identifying fraudulent transactions using data analytics.

  3. WHY LEARN DATA ANALYTICS? • Growing Demand: The global market for data analytics is rapidly expanding, with companies in every industry seeking data-savvy professionals. • Benefits: • Job Security: Data roles are resilient to automation. • High Earning Potential: Data professionals earn an average of $80,000 to $120,000 annually.

  4. KEY CONCEPTS IN DATA ANALYTICS 04 Data Collection: 01 • Sources: Databases, APIs, IoT devices, social media, web scraping. • Tools: SQL, Python libraries, web scraping tools (e.g., BeautifulSoup). Data Cleaning: 02 • Process: Removing duplicates, handling missing values, normalizing data. • Tools: Python (Pandas, NumPy), Excel, R. Data Analysis: 03 • Techniques: Statistical analysis, correlation analysis, regression models. • Algorithms: Decision Trees, Random Forests, K-Means Clustering.

  5. TYPES OF DATA ANALYTICS 05 • Descriptive Analytics: Summarizes historical data to understand past performance. • Example: Sales reports that show monthly revenue trends. • Predictive Analytics: Uses historical data to make predictions about future events. • Example: Forecasting product demand using past sales data. • Prescriptive Analytics: Recommends actions based on data. • Example: Optimizing inventory levels based on predictive insights. • Diagnostic Analytics: Focuses on identifying the root causes of past outcomes. • Example: Analyzing why a marketing campaign failed to meet expectations.

  6. TOOLS AND TECHNOLOGIES IN DATA ANALYTICS 06 • Excel: Used for basic data manipulation, pivot tables, and charting. • SQL: For database querying, joins, subqueries, and data aggregation. • Python/R: • Python Libraries: Pandas, NumPy, Matplotlib, Seaborn for data analysis and visualization. • R: Best for statistical analysis and complex data manipulations. • Power BI/Tableau: • Power BI: Microsoft’s data visualization tool for building interactive dashboards. • Tableau: Leading BI tool for creating rich visual analytics and data stories.

  7. DATA ANALYTICS IN DIFFERENT INDUSTRIES 07 • Retail and E-commerce: • Applications: Personalized recommendations, customer segmentation, optimizing inventory. • Example: Amazon's recommendation engine. • Healthcare: • Applications: Predicting patient readmission rates, optimizing treatment plans. • Example: Predictive models for identifying high-risk patients. • Finance: • Applications: Fraud detection, risk assessment, portfolio optimization. • Example: Credit score algorithms. • Marketing: • Applications: Customer sentiment analysis, campaign performance tracking. • Example: Google Ads data analysis to optimize ad spending.

  8. 08 ANALYTICS SHIKSHA - WHO WE ARE • Our Mission: Empower students and professionals with the tools to thrive in data analytics, leveraging real-world projects and expert mentorship. • Our Vision: To create the next generation of data-driven problem solvers through innovative, hands-on learning experiences. • Our Values: Quality education, practical skills, and student success.

  9. LEARN DATA ANALYTICS WITH ANALYTICS SHIKSHA 09 • Why Choose Us? • Expertise: Courses led by industry professionals with real-world experience. • Unique Approach: Focus on the "Art of Problem Solving," integrating theory with practical applications.

  10. 10 SUPER 30 DATA ANALYTICS PROGRAM What is Super 30? In large batches, asking doubts can be difficult and slow. With the Super30 Data Analytics Program at Analytics Shikhsa, we ensure personalized attention for every candidate. This approach increases participation and collaboration, fostering great academic outcomes in data analytics.

  11. LET'S TALK TO US • WEBSITE • www.analyticsshiksha.com • PHONE NUMBER • +91 76781 17274 • EMAIL ADDRESS • info@analyticsshiksha.com

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