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Data Analytics For Beginners | Introduction To Data Analytics | Data Analytics Using R | Simplilearn

This presentation on Data Analytics for Beginners covers all the basics and the concepts that will help you start learning data analytics. You will understand what data analytics and the need for data analytics. Then, you learn the different process steps in data analytics and the essential tools that are used to perform data analytics. Also, you will see a case study on how Walmart uses data analytics for running its business. Finally, we'll do some hands-on demo using linear regression in R to predict sales for the advertising budget. So, let's get started.<br><br>1. What is Data Analytics?<br>2. Steps involved in Data Analytics<br>3. Tools used for Data Analytics<br>4. Data Analytics Applications<br>5. Companies using Data Analytics<br>6. Case Study<br>7. Use Case Demo<br><br>Why become Data Analyst?<br>By 2020, the World Economic Forum forecasts that data analysts will be in demand due to increasing data collection and usage. Organizations view data analysis as one of the most crucial future specialties due to the value that can be derived from data. Data is more abundant and accessible than ever in todayu2019s business environment. In fact, 2.5 quintillion bytes of data are created each day. With an ever-increasing skill gap in data analytics, the value of data analysts is continuing to grow, creating a new job and career advancement opportunities. <br><br>The facts are that professionals who enter the Data Science field will have their pick of jobs and enjoy lucrative salaries. According to an IBM report, data and analytics jobs are predicted to increase by 15 percent to 2.72 million jobs by 2020, with the most significant demand for data analysts in finance, insurance, and information technology. Data analysts earn an average pay of $67,377 in 2019 according to Glassdoor.<br><br>Who should take up this course?<br>Aspiring professionals of any educational background with an analytical frame of mind are best suited to pursue the Data Analyst Masteru2019s Program, including:<br>1. IT professionals<br>2. Banking and finance professionals<br>3. Marketing managers<br>4. Sales professionals<br>5. Supply chain network managers<br>6. Beginners in the data analytics domain<br>7. Students in UG/ PG programs<br><br><br>ud83dudc49Learn more at: https://bit.ly/2x28p0m

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Data Analytics For Beginners | Introduction To Data Analytics | Data Analytics Using R | Simplilearn

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  1. Data Analytics for Beginners Deep Learning frameworks

  2. What’s in it for you? • What is Data Analytics? • Steps involved in Data Analytics • Tools used for Data Analytics • Data Analytics Applications • Companies using Data Analytics • Case Study • Use Case Demo

  3. What is Data Analytics? Deep Learning frameworks What is Data Analytics?

  4. Data Analytics for Beginners Deep Learning frameworks Click here to watch the video

  5. What is Data Analytics? Deep Learning frameworks Data Analytics is the process of exploring and analyzing large datasets to find hidden patterns, unseen trends, discover correlations and valuable insights

  6. What is Data Analytics? Deep Learning frameworks Ways to use Data Analytics

  7. Ways to use Data Analytics Deep Learning frameworks 1 2 3 4 Effective Marketing Efficient Operations Better Customer Service Improved Decision Making

  8. What is Data Analytics? Deep Learning frameworks Steps involved in Data Analytics

  9. Steps involved in Data Analytics Deep Learning frameworks

  10. Steps involved in Data Analytics Deep Learning frameworks 1 Understand the problem 5 2 Interpret the results Data collection 4 3 Data exploration and analysis Data cleaning

  11. Steps involved in Data Analytics Deep Learning frameworks Understand the problem Understand the business problem, define the organizational goals and plan for a lucrative solution 1

  12. Steps involved in Data Analytics Deep Learning frameworks Data Collection Gather the right data from various sources and other information based on your priorities 2

  13. Steps involved in Data Analytics Deep Learning frameworks Data Cleaning Clean the data to remove unwanted, redundant and missing values and make it ready for analysis 3

  14. Steps involved in Data Analytics Deep Learning frameworks Data exploration and analysis Use data visualization and business intelligence tools, data mining techniques and predictive modelling to analyse data 4

  15. Steps involved in Data Analytics Deep Learning frameworks Interpret the results Interpret the results to find out hidden patterns, future trends and gain insights 5

  16. What is Data Analytics? Deep Learning frameworks Data Analytics Tools

  17. Tools used for Data Analytics Deep Learning frameworks

  18. Tools used for Data Analytics Deep Learning frameworks Python is an object-orientedopen-source programming language that supports a range of libraries for data manipulation, data visualization and data modeling

  19. Tools used for Data Analytics Deep Learning frameworks R is an open-source programming language majorly used for numerical and statistical analysis. It provides a range of libraries for data analysis and visualization

  20. Tools used for Data Analytics Deep Learning frameworks Tableau is a data visualization tool that can create a wide range of visualizations to interactively present the data, build reports and dashboards to showcase insights and trends

  21. Tools used for Data Analytics Deep Learning frameworks Power BI is a business intelligence tool developed by Microsoft that has easy drag and drop functionality and supports multiple data sources with features that make data visually appealing

  22. Tools used for Data Analytics Deep Learning frameworks QlikView provides interactiveanalytics with in-memory storage technology to analyse vast volumes of data and use data discoveries to support decision making

  23. Tools used for Data Analytics Deep Learning frameworks Apache Spark is an open-source data analytics engine to process data in real-time and carry out complex analytics using SQL queries and machine learning algorithms

  24. Tools used for Data Analytics Deep Learning frameworks SAS is a statistical analysis software that can help you perform analytics, visualize data, write SQL queries and build machine learning models to make future predictions

  25. What is Data Analytics? Deep Learning frameworks Data Analytics Applications

  26. Data Analytics Applications Deep Learning frameworks 1 Retail Retailers use data analytics to understand their customer needs and buying habits to predict trends, recommendnewproducts and boost their business

  27. Data Analytics Applications Deep Learning frameworks 2 Health Care Healthcare industries analyse patientdata to provide lifesaving diagnoses and treatment options. They also deal with healthcare plans, insurance information to derive key insights

  28. Data Analytics Applications Deep Learning frameworks 3 Manufacturing Using data analytics, manufacturing sectors can discover new cost saving and revenueopportunities. They can solve complex supply chain issues, labour constraints and equipment breakdowns

  29. Data Analytics Applications Deep Learning frameworks 4 Banking Banking institutions gather and access large volumes of data to derive analytical insights and make sound financial decisions. They find out probable loan defaulters, customer churn out rate and detect frauds intransactions

  30. Data Analytics Applications Deep Learning frameworks 5 Logistics Logistics companies use data analytics to develop new business models, optimize routes, improve productivity and order processing capabilitiesas well as performance management

  31. What is Data Analytics? Deep Learning frameworks Companies using Data Analytics

  32. Companies using Data Analytics Deep Learning frameworks

  33. What is Data Analytics? Deep Learning frameworks Walmart Case Study

  34. Case Study Deep Learning frameworks Walmart is an American multinational retail company with over 11,500 stores in 27 countries and eCommerce websites in 10 countries

  35. Case Study Deep Learning frameworks It has over 2.2 million employees around the world, 1.5 million in the U.S. alone More than 240 million customers shop at Walmart each week online and at its banner stores

  36. Case Study Deep Learning frameworks Walmart collects over 2.5 petabytes of data from 1 million customers every hour To make sense of all this information, Walmart has created Data Café – a state-of-the-art analytics hub

  37. Case Study Deep Learning frameworks Over 200 streams of internal and external data, including 40 petabytes of recent transactional data, can be modelled, manipulated and visualized Walmart constantly analyses over 100 million keywords to know what people near each store are saying on social media

  38. Case Study Deep Learning frameworks • Better management of supply chain • Optimize product assortment • Personalize the shopping experience • Give relevant product recommendation • Optimize and analyze transportation lanes and routes for its fleet of trucks Walmart uses modern tools and technologies to derive businessinsights and improve customersatisfaction

  39. What is Data Analytics? Deep Learning frameworks Use Case Demo – Linear Regression analysis

  40. Use Case Demo Deep Learning frameworks Predict sales based on the advertising expenditure using Linear Regression model in R Newspaper Radio Television

  41. Why R? Deep Learning frameworks Free and open-source software Build different models Data visualization Statistical analysis

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