Use Of Predictive Analytics In Modern Decision Making Data Analytics CD
Grab our professionally designed Use of Predictive Analytics in Modern Decision-Making PowerPoint presentation. Predictive Analytics entails using data to predict future outcomes using data analysis, machine learning, artificial intelligence, and statistical models. The main purpose of predictive analytics is to find data patterns to predict future behaviour. This Predictive Data PPT creates an understanding of the types, benefits, use cases, trends, market size, and phases of implementing predictive analytics with the purpose of streamlining business performance Additionally, this complete deck may help organizations get an overview of techniques introduced to streamline decision making. These include decision tree, time series, clustering, neural networks, and regression Furthermore, these PPT slides provide insights into the usability and benefits of software tools such as Alteryx, Azure Machine Learning, RapidMiner, H20 Driverless AI, and AWS Sagemaker. Furthermore, our PPT slides highlight budget allocation and impact analysis of implementing predictive analytics tools and techniques. Finally, this AI Predictive Analytics PPT complete deck presents industry wise case studies highlighting use of predictive analytics in healthcare, finance, banking, marketing, manufacturing, retail and supply chain management. Download our 100 percent editable and customizable template, which is also compatible with Google Slides.
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Content of this Powerpoint Presentation
Slide 1: This slide introduces Use of Predictive Analytics in Modern Decision-Making. State your company name and begin.
Slide 2: This slide states Agenda of the presentation.
Slide 3: This slide shows Table of Content for the presentation.
Slide 4: This is another slide continuing Table of Content for the presentation.
Slide 5: This slide highlights title for topics that are to be covered next in the template.
Slide 6: This slide provides an introduction to predictive analytics aimed at helping businesses analyse data for better decision making.
Slide 7: This slide presents Need of predictive analytics in current business landscape.
Slide 8: This slide displays Benefits of leveraging predictive analytics in business.
Slide 9: This slide represents Applications of predictive analytics in various industries.
Slide 10: This slide showcases Use cases of predictive analytics in businesses.
Slide 11: This slide shows Use cases of predictive analytics in businesses contd..
Slide 12: This slide presents Emerging trends shaping predictive analytics.
Slide 13: This slide highlights title for topics that are to be covered next in the template.
Slide 14: This slide displays Market snapshot of global predictive analytics market.
Slide 15: This slide represents Segmentation of global predictive analytics market.
Slide 16: This slide showcases Growth drivers of global predictive analytics market.
Slide 17: This slide shows Growth restraints of global predictive analytics market.
Slide 18: This slide highlights title for topics that are to be covered next in the template.
Slide 19: This slide presents Brief overview of predictive analytics techniques.
Slide 20: This slide displays Use of predictive analytics in modern decision-making.
Slide 21: This slide represents Working mechanism of decision tree algorithm.
Slide 22: This slide showcases Advantages of implementing decision trees in business.
Slide 23: This slide shows Use cases of decision tree algorithms.
Slide 24: This slide presents Best practices for building decision tree.
Slide 25: This slide outlines a case study highlighting use of decision tree analysis to help a business make decisions of buying a new plant or upgrade the existing one.
Slide 26: This slide displays Use of predictive analytics in modern decision-making.
Slide 27: This slide represents Working mechanism of time series analysis.
Slide 28: This slide showcases Advantages of implementing time series analysis.
Slide 29: This slide shows Phases outlining processing of time series data.
Slide 30: This slide presents Use cases of time series forecasting and analysis.
Slide 31: This slide displays Industrial applications of time series analysis.
Slide 32: This slide represents Best practices to improve time series forecasting.
Slide 33: This slide provides a case study outlining use of time series analysis to detect anomalies in add to cart per session ratio for an ecommerce platform.
Slide 34: This slide showcases Use of predictive analytics in modern decision-making.
Slide 35: This slide shows Types of methods utilized for cluster analysis.
Slide 36: This slide presents Advantages of implementing cluster analysis in business.
Slide 37: This slide displays Requirements for cluster analysis in data mining.
Slide 38: This slide represents Application areas of cluster analysis in business.
Slide 39: This slide showcases Use of predictive analytics in modern decision-making.
Slide 40: This slide provides a description of feedforward neural network aimed at helping businesses understand its usability.
Slide 41: This slide shows Types of neural network : Radial basis function.
Slide 42: This slide presents Types of neural network :Multilayer perceptron.
Slide 43: This slide displays Types of neural network : Radial basis function.
Slide 44: This slide represents Types of neural network : Recurrent neural network.
Slide 45: This slide showcases Types of neural network : Modular neural network.
Slide 46: This slide shows Key components of neural network architecture.
Slide 47: This slide presents Key components of neural network architecture contd..
Slide 48: This slide displays Key benefits of using neural networks.
Slide 49: This slide represents Working mechanism of neural network algorithms.
Slide 50: This slide showcases Key applications of neural networks.
Slide 51: This is another slide continuing Key applications of neural networks.
Slide 52: This slide shows Use of predictive analytics in modern decision-making.
Slide 53: This slide presents Benefits of implementing regression analysis for businesses.
Slide 54: This slide displays Major application areas of regression analysis.
Slide 55: This slide represents Best practices to conduct regression analysis.
Slide 56: This slide showcases Use of predictive analytics in modern decision-making.
Slide 57: This slide shows PADS framework to identify business requirements.
Slide 58: This slide presents Business problems to be solved using predictive analytics solution.
Slide 59: This slide highlights title for topics that are to be covered next in the template.
Slide 60: This slide displays Various data collection techniques for businesses.
Slide 61: This slide represents Best practices to conduct data collection.
Slide 62: This slide showcases Comparative analysis of data extraction tools.
Slide 63: This slide highlights title for topics that are to be covered next in the template.
Slide 64: This slide shows Actions undertaken to improve data quality.
Slide 65: This slide presents Best practices to improve data quality.
Slide 66: This slide displays KPI dashboard to monitor data quality.
Slide 67: This slide highlights title for topics that are to be covered next in the template.
Slide 68: This slide represents Facts highlighting importance of data cleaning.
Slide 69: This slide showcases Flowchart outlining data cleaning approach.
Slide 70: This slide shows Steps to perform data cleaning process.
Slide 71: This slide presents Effective data cleaning techniques for businesses.
Slide 72: This slide displays Effective data cleaning techniques for businesses contd..
Slide 73: This slide represents Best practices to employ for data cleaning.
Slide 74: This slide showcases Comparative analysis of data cleaning tools.
Slide 75: This slide highlights title for topics that are to be covered next in the template.
Slide 76: This slide shows Introduction to exploratory data analysis : Overview and types.
Slide 77: This slide presents Steps to perform exploratory data analysis.
Slide 78: This slide displays Importance of exploratory analysis in data science.
Slide 79: This slide represents Benefits of leveraging exploratory data analysis.
Slide 80: This slide highlights title for topics that are to be covered next in the template.
Slide 81: This slide showcases List of major predictive analytics software tools.
Slide 82: This slide shows Checklist to select predictive analytics solution.
Slide 83: This slide provides an overview of predictive analytics software tool Alteryx with the aim of explaining its usability to businesses.
Slide 84: This slide gives an overview of Alteryx, a predictive analytics software tool, explaining its usability to businesses.
Slide 85: This slide presents Predictive analytics software tool 2 : Azure machine learning.
Slide 86: This slide displays Predictive analytics software tool 2 : Azure machine learning contd..
Slide 87: This slide represents Predictive analytics software tool 3 : RapidMiner Studio.
Slide 88: This slide showcases Predictive analytics software tool 3 : RapidMiner studio.
Slide 89: This slide shows Predictive analytics software tool 4 :H2O Driverless AI.
Slide 90: This slide presents Predictive analytics software tool 5 : AWS sagemaker.
Slide 91: This slide displays Predictive analytics software tool 5 : AWS sagemaker.
Slide 92: This slide represents Comparative analysis of predictive analytics tools.
Slide 93: This slide highlights title for topics that are to be covered next in the template.
Slide 94: This slide showcases Predictive analytics performance evaluation framework.
Slide 95: This slide shows Steps to evaluate predictive dataset models.
Slide 96: This slide presents Types of predictive model evaluation techniques.
Slide 97: This slide displays Model evaluation approaches in machine learning.
Slide 98: This slide highlights title for topics that are to be covered next in the template.
Slide 99: This slide represents Implementation timeline of predictive analytics model.
Slide 100: This slide highlights title for topics that are to be covered next in the template.
Slide 101: This slide showcases Data analytics team roles and responsibilities.
Slide 102: This slide shows Predictive analytics training plan for employees.
Slide 103: This slide highlights title for topics that are to be covered next in the template.
Slide 104: This slide represents Cost assessment of predictive analytics implementation.
Slide 105: This slide highlights title for topics that are to be covered next in the template.
Slide 106: This slide showcases Impact assessment of predictive analytics solutions.
Slide 107: This slide highlights title for topics that are to be covered next in the template.
Slide 108: This slide shows Challenges of implementing predictive analytics in organisations.
Slide 109: This slide presents Recommendations for improving quality of predictive models.
Slide 110: This slide highlights title for topics that are to be covered next in the template.
Slide 111: This slide displays Applications of predictive analytics in healthcare industry.
Slide 112: This slide represents Applications of predictive analytics in finance industry.
Slide 113: This slide showcases Applications of predictive analytics in banking industry.
Slide 114: This slide shows Applications of predictive analytics in marketing industry.
Slide 115: This slide presents Applications of predictive analytics in manufacturing industry.
Slide 116: This slide displays Applications of predictive analytics in retail industry.
Slide 117: This slide represents Applications of predictive analytics in supply chain.
Slide 118: This slide contains all the icons used in this presentation.
Slide 119: This is a Thank You slide with address, contact numbers and email address.
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