Harnessing Prescriptive Analytics For Strategic Insights Powerpoint Presentation Ppt Slides Data Analytics CD V

Slide 1: This slide introduces Harnessing Prescriptive Analytics for Strategic Insights. State your company name and begin.
Slide 2: This is an Agenda slide. State your agendas here.
Slide 3: This slide shows Table of Content for the presentation.
Slide 4: This slide continues showing Table of Content for the presentation.
Slide 5: This slide shows title for topics that are to be covered next in the template.
Slide 6: This slide provides an introduction to prescriptive analytics aimed at making future decisions using past data on accurate basis.
Slide 7: This slide displays a table comparing four types of analytics such as descriptive diagnostic, predictive and prescriptive analytics. The basis of comparison are definition, focus etc.
Slide 8: This slide outlines major arguments explaining requirements of business enterprises to leverage prescriptive analytics aimed at helping the same boost processes.
Slide 9: This slide presents benefits of using prescriptive analytics aimed at helping businesses to meet its long term goals. It covers benefits such as data driven decisions etc.
Slide 10: This slide outlines business applications of prescriptive analytics aimed at helping them gain competitive advantage using better decision making.
Slide 11: This slide displays industries using prescriptive analytics aimed at improving their performance to achieve long term profitability. It covers industries utilising analytics.
Slide 12: This slide shows title for topics that are to be covered next in the template.
Slide 13: This slide showcase a graphical representation of global prescriptive analytics market. It includes present and forecasted values of prescriptive analytics usage globally with key takeaways.
Slide 14: This slide provides an overview of market segmentation of prescriptive analytics at a global level. It covers segmentation analysis based on region, data type, component etc.
Slide 15: This slide displays major growth drivers expected to fuel the growth of global prescriptive analytics market. It covers reasons such as decision making via real time data access etc.
Slide 16: This slide outlines major growth restraints that may hinder increased use of prescriptive analytics to boost sales. It covers arguments such as management of complexities, setup costs etc.
Slide 17: This slide shows title for topics that are to be covered next in the template.
Slide 18: This slide provides a flowchart that illustrates working of prescriptive analytics aimed at helping businesses reach recommended actions via what if scenarios.
Slide 19: This slide outlines list of business goals to be achieved by business using prescriptive analytics tools and techniques. It covers goals related to invenroty levels, route determination etc.
Slide 20: This slide shows title for topics that are to be covered next in the template.
Slide 21: This slide outlines various data collection methods aimed at helping businesses optimize data driven decision making. It covers methods such as observations, interviews etc.
Slide 22: This slide provides an introduction to data integration aimed at helping businesses gather and consolidate data for effective decision making.
Slide 23: This slide displays key steps to conduct data integration aimed at helping businesses combine and collaborate data together. It covers steps such as data requirements etc.
Slide 24: This slide explains extract, transform, load pipeline aimed at helping businesses collect data and store it into warehouse.
Slide 25: This slide explains extract, load, transform pipeline aimed at helping businesses collect data and store it into warehouse. It covers description as well as illustration.
Slide 26: This slide displays data streaming approach for executing data integration aimed at delivering data from source to target destination.
Slide 27: This slide showcases data application integration aimed at helping businesses support operational needs. It covers description as well as illustration explaining working.
Slide 28: This slide explains data virtualization aimed at providing businesses with unified data view by combing the same from various platforms.
Slide 29: This slide shows title for topics that are to be covered next in the template.
Slide 30: This slide provides a table comparing major AutoML tools aimed at helping businesses choose the appropriate one to develop prescriptive model.
Slide 31: This slide shows title for topics that are to be covered next in the template.
Slide 32: This slide provides an introduction to heuristics analysis aimed ta helping businesses derive practical solutions to data problems. It covers description, purpose etc.
Slide 33: This slide outlines key advantages of leveraging heuristic analysis aimed at helping businesses improve decision making. It covers the benefits such as faster decisions etc.
Slide 34: This slide displays major steps to conduct heuristics analysis aimed at helping businesses conduct evaluation and generate meaningful changes.
Slide 35: This slide shows title for topics that are to be covered next in the template.
Slide 36: This slide provides an introduction to simulation analysis aimed ta helping businesses derive best course of action using real world situations.
Slide 37: This slide outlines key advantages of leveraging simulation analysis aimed at helping businesses objectively predict results of the actions before implementation in real world.
Slide 38: This slide displays phases to simulate data aimed at helping businesses understand and solve complex problems. It covers various steps such as form hypothesis, generate random samples etc.
Slide 39: This slide explains applications of simulation in the realms of business analytics and decision making by testing various scenarios. It covers uses such as testing marketing strategies etc.
Slide 40: This slide shows title for topics that are to be covered next in the template.
Slide 41: This slide provides an introduction to machine learning aimed ta helping businesses derive patterns and connections in the data. It covers description and features of machine learning.
Slide 42: This slide outlines various statistical facts signifying importance of implementing machine learning algorithms in current business landscape.
Slide 43: This slide displays steps to implement machine learning aimed at improving business operations. It covers steps such as project set up, data preparation, modelling and deployment.
Slide 44: This slide highlights workflow of machine learning aimed ta helping businesses adopt the same and improve operations. It covers workflow beginning from data training to model success.
Slide 45: This slide outlines real life applications of machine learning in various industries aimed at tailoring services and promoting trust among consumer.
Slide 46: This slide shows title for topics that are to be covered next in the template.
Slide 47: This slide provides an introduction to artificial intelligence in analytics aimed ta helping businesses derive patterns and connections in the data.
Slide 48: This slide outlines key advantages of leveraging artificial intelligence in analytics aimed at helping businesses objectively predict results of the actions before implementation.
Slide 49: This slide displays applications of AI in data analysis aimed at helping businesses save time and effort. It covers application areas such as generate code or debug errors etc.
Slide 50: This slide shows title for topics that are to be covered next in the template.
Slide 51: This slide provides an introduction to decision tree analysis aimed ta helping businesses improve decision making. It covers description and importance of integrating decision tree analysis.
Slide 52: This slide outlines key advantages of leveraging decision tree analysis aimed at identifying correct solutions to any problem. It covers the benefits such as depicts suitable project etc.
Slide 53: This slide outlines applications of decision tree aimed at helping businesses evaluate prospective growth opportunities. It covers application areas such as marketing, customer retention etc.
Slide 54: This slide displays key steps to develop decision tree aimed at helping businesses derive data insights via effective analysis. It covers steps such as decide idea, add potential decisions etc.
Slide 55: This slide shows title for topics that are to be covered next in the template.
Slide 56: This slide provides an introduction to monte carlo simulation aimed ta helping businesses improve decision making by forecasting outcomes.
Slide 57: This slide outlines key advantages of implementing Monte Carlo simulations aimed at analyzing probable events and assess their likelihood.
Slide 58: This slide provides an illustration highlighting working of monte carlo simulation aimed at analyzing complex processes using random samples.
Slide 59: This slide outlines major applications of Monte Carlo simulations aimed at exploring and optimizing decision making strategies. It covers applications in areas such as AI and ML etc.
Slide 60: This slide shows title for topics that are to be covered next in the template.
Slide 61: This slide provides an introduction to genetic algorithms aimed at stimulating natural selection to find optimal solutions . It covers description and operators of genetic algorithms.
Slide 62: This slide outlines key advantages of implementing genetic algorithms aimed at processing large amounts of data effectively. It covers the benefits such as space search exploration etc.
Slide 63: This slide displays key steps to develop decision tree aimed at helping businesses derive data insights via effective analysis. It covers steps such as decide idea, add potential decisions etc.
Slide 64: This slide highlights real life examples of genetic algorithms aimed at understanding its extensive use at a global level. It covers applications in various firms such as Google, Amazon etc.
Slide 65: This slide displays real life examples of genetic algorithms aimed at understanding its extensive use at a global level. It covers applications in various firms such as Google, Amazon etc.
Slide 66: This slide shows title for topics that are to be covered next in the template.
Slide 67: This slide provides an overview of software tools used in prescriptive analytics to derive best course of action. It covers the overview of tools as well as name of major tools used.
Slide 68: This slide displays an overview of advanced analytic tool Alteryx. It covers details regarding unique selling propositions, customer reviews and pricing plans of Alteryx.
Slide 69: This slide provides an overview of advanced analytic tool Alteryx. It covers details regarding unique selling propositions, customer reviews and pricing plans of Alteryx.
Slide 70: This slide displays overview of Tableau as a data analytics tools providing data visualization features. It covers details of Tableau regarding description, features and pricing plans.
Slide 71: This slide showcases overview of Google Looker as a data analytics tool. It covers details of Google Looker regarding description, unique selling propositions, features and pricing plans.
Slide 72: This slide provides overview of KNIME as a prescriptive analytics tool to help businesses evaluate its usability. It covers details of KNIME regarding description, features etc.
Slide 73: This slide displays overview of RapidMiner as a prescriptive analytics tool to help businesses evaluate its usability. It covers details of RapidMiner regarding description, features etc.
Slide 74: This slide provides overview of Azure Machine Learning as a prescriptive analytics tool to help businesses evaluate its usability.
Slide 75: This slide presents a comparison of software tools used by businesses to conduct prescriptive analytics for various operations. The basis of features are self service data preparation etc.
Slide 76: This slide shows title for topics that are to be covered next in the template.
Slide 77: This slide illustrates a flowchart outlining process of deploying machine learning model of prescriptive analytics in business enterprise.
Slide 78: This slide provides a deployment table of prescriptive model aimed at highlighting movement of models through various phases. The basis of deployment are stage, start and end date etc.
Slide 79: This slide outlines major practices which can be undertaken by businesses for effective model deployment. It covers practices such as continuous integration, containerization etc.
Slide 80: This slide shows title for topics that are to be covered next in the template.
Slide 81: This slide provides inventory data collected aimed to help businesses evaluate the current scenario. It covers data for costs such as sales data, supplier lead time, shipping etc.
Slide 82: This slide displays a gap analysis highlighting current scenario of KPIs related to inventory management of ecommerce business. It covers list of metrics such as current scenario etc.
Slide 83: This slide provides trends in product demand and supply highlighting errors in inventory management. It covers a graph showing trends in demand and supply levels with key insights.
Slide 84: This slide displays an illustration highlighting application of predictive analytics aimed at helping businesses forecast sales projections.
Slide 85: This slide explains use of inventory software aimed at helping businesses optimize inventory levels using effective analysis. It covers use of BI solution, vendor portal, hardware etc.
Slide 86: This slide outlines analytics strategies aimed at helping businesses optimize inventory ad streamline operations. It covers replenishment optimization, prevent stockouts etc.
Slide 87: This slide provides a dashboard highlighting inventory performance aimed at helping businesses streamline operations. It covers details on sales orders, invoices, order value etc.
Slide 88: This slide shows title for topics that are to be covered next in the template.
Slide 89: This slide highlights team roles under analytics department aimed at understanding their functioning to achieve business goals and objectives.
Slide 90: This slide highlights team roles under analytics department aimed at understanding their functioning to achieve business goals and objectives.
Slide 91: This slide outlines training plan aimed at helping employees learn the basics of prescriptive analytics to streamline its usage in the business enterprises.
Slide 92: This slide shows title for topics that are to be covered next in the template.
Slide 93: This slide provides a table highlighting assessment of various cost heads aimed at effectively implementing prescriptive analytics in a business.
Slide 94: This slide illustrates budget allocation towards prescriptive analytics tools and activities in form of a pie chart aimed at identifying and altering cost arrangements.
Slide 95: This slide shows title for topics that are to be covered next in the template.
Slide 96: This slide showcases graph highlighting impact analysis of prescriptive analytics on businesses via use of major performance indicators. It provides information total revenue etc.
Slide 97: This slide shows title for topics that are to be covered next in the template.
Slide 98: This slide illustrates a KPI dashboard highlighting application of prescriptive analytics to analyze emergency room visits of a hospital. It covers KPIs such as emergency room visits etc.
Slide 99: This slide displays a KPI dashboard highlighting application of prescriptive analytics to analyze website visits and sales. It covers KPIs such as monthly visitors, monthly sales etc.
Slide 100: This slide shows title for topics that are to be covered next in the template.
Slide 101: This slide outlines various areas where prescriptive analytics may be implemented to improve the working of healthcare sector. It covers areas such as treatment plan optimization etc.
Slide 102: This slide displays various areas where prescriptive analytics may be implemented to improve the working of sales and marketing sector.
Slide 103: This slide outlines various areas where prescriptive analytics may be implemented to improve the working of supply chain. It covers areas such as network design etc.
Slide 104: This slide displays various areas where prescriptive analytics may be implemented to improve the working of manufacturing sector. It covers areas such as prescriptive maintenance etc.
Slide 105: This slide outlines various areas where prescriptive analytics may be implemented to improve the working of finance sector. It covers areas such as service optimization etc.
Slide 106: This slide displays various areas where prescriptive analytics may be implemented to improve the working of finance sector. It covers areas such as service optimization etc.
Slide 107: This slide shows all the icons included in the presentation.
Slide 108: This is a Thank You slide with address, contact numbers and email address along with socials.