Mastering Data Analytics A Comprehensive Guide Data Analytics CD

Slide 1: The slide introduces Mastering Data Analytics: A Comprehensive Guide. State your Company name and begin.
Slide 2: This is an Agenda slide. State your agendas here.
Slide 3: The slide displays Table of contents for the presentation.
Slide 4: The slide renders Table of contents further.
Slide 5: The slide again Table of contents.
Slide 6: This slide provides a brief introduction to data analytics aimed at helping businesses make informed decisions.
Slide 7: This slide renders major reasons highlighting need to implement data analytics and improve business decision making.
Slide 8: This slide highlights statistical facts aimed ta helping businesses make rapid decisions in today’s competitive environment.
Slide 9: This slide outlines major benefits derived by businesses using data analytics to simplify complex problems.
Slide 10: This slide renders application areas of data analytics aimed at helping various industries maximize efficiency and reduce wastage.
Slide 11: This slide highlights metrics aimed at assessing the impact of data analytics on business performance.
Slide 12: The slide again shows Title of contents.
Slide 13: This slide showcase a graphical representation of global data analytics market.
Slide 14: This slide briefs an overview of market segmentation of data analytics at a global level.
Slide 15: This slide continues an overview of market segmentation of data analytics at a global level.
Slide 16: This slide shows major growth drivers promoting increased use of data analytics at a global level to boost business reach.
Slide 17: This slide depicts major growth restraints that may hinder increased use of data analytics to boost sales.
Slide 18: The slide displays Title of contents which is to be discussed further.
Slide 19: This slide provides an introduction to descriptive analytics aimed at analysing past data to optimize future decision making.
Slide 20: This slide highlights benefits of using descriptive analytics aimed at helping businesses meet its goals.
Slide 21: This slide shows steps to conduct descriptive analytics aimed at helping businesses convert complex data into useful resource.
Slide 22: This slide highlights usage areas of predictive analytics aimed ta helping businesses implement the same to optimize performance.
Slide 23: This slide outlines industries using descriptive analytics aimed at improving their performance to achieve long term profitability.
Slide 24: The slide again displays Title of contents.
Slide 25: This slide provides an introduction to diagnostic analytics aimed at analysing past data to optimize future decision making.
Slide 26: This slide outlines benefits of using diagnostic analytics aimed at helping businesses reduce operational inefficiencies.
Slide 27: This slide demonstrates steps to conduct diagnostic analytics aimed at helping businesses convert complex data into useful resources.
Slide 28: This slide highlights techniques to help businesses understand occurrence of any event in the past.
Slide 29: This slide outlines industries using diagnostic analytics aimed at improving their performance to achieve long term profitability.
Slide 30: The slide renders another Title of contents.
Slide 31: This slide provides an introduction to predictive analytics analytics aimed at making future decisions using past data on accurate basis.
Slide 32: This slide outlines benefits of using predictive analytics aimed at helping businesses to meet its long term goals.
Slide 33: This slide renders steps to conduct predictive analytics aimed at helping businesses convert complex data into useful resource.
Slide 34: This slide shows major techniques used by businesses aimed at employing predictive analytics in their operations.
Slide 35: This slide outlines industries using predictive analytics aimed at improving their performance to achieve long term profitability.
Slide 36: This slide continues industries using predictive analytics aimed at improving their performance to achieve long term profitability.
Slide 37: The slide displays Title of contents which is to be discussed further.
Slide 38: This slide provides an introduction to prescriptive analytics aimed at making future decisions using past data on accurate basis.
Slide 39: This slide outlines benefits of using prescriptive analytics aimed at helping businesses to meet its long term goals.
Slide 40: This slide displays major techniques used by businesses aimed at employing prescriptive analytics in their operations.
Slide 41: This slide outlines industries using prescriptive analytics aimed at improving their performance to achieve long term profitability.
Slide 42: The slide again depicts Title of contents.
Slide 43: This slide provides list of major goals to be achieved by business aiming at implementing data analytics.
Slide 44: This slide outlines a table highlighting various data analytics initiates to be undertaken by business for achieving business goals.
Slide 45: The slide again displays Title of contents.
Slide 46: This slide provides an organisation structure of data science team consisting of members involved in data analysis team.
Slide 47: This slide highlights team roles under analytics department aimed at understanding their functioning to achieve business goals and objectives.
Slide 48: This slide shows team roles under analytics department aimed at understanding their functioning to achieve business goals and objectives.
Slide 49: The slide displays Title of contents further.
Slide 50: This slide provides an overview of key data analytics techniques employed by majority of businesses to improve decision making.
Slide 51: The slide displays Title of contents which is to be discussed further.
Slide 52: This slide highlights major benefits of leveraging data mining techniques for businesses aimed at improving their profitability.
Slide 53: This slide presents phases to implement data mining aimed at helping data scientists and analysis to conduct project.
Slide 54: This slide outlines types of data mining techniques aimed at identifying patterns and deriving informative insights.
Slide 55: This slide displays real life applications of data mining in various industries aimed at tailoring services and promoting trust among consumer.
Slide 56: This slide provides a dashboard highlighting use of data mining to improve analysis of social media accounts.
Slide 57: The slide renders Title of contents further.
Slide 58: This slide highlights advantages of using text analytics by businesses aimed at using texts to transform the same into actionable insights.
Slide 59: This slide shows phases to implement text analysis aimed at helping data scientists and analysis to conduct project.
Slide 60: This slide presents types of text analysis techniques aimed at identifying patterns and deriving informative insights.
Slide 61: This slide outlines real life applications of text analytics in various industries aimed at tailoring services and promoting trust among consumer.
Slide 62: This slide continues real life applications of text analytics in various industries aimed at tailoring services and promoting trust among consumer.
Slide 63: This slide illustrates dashboard reporting customer support ticket response time aimed at providing quick solutions to customer issues.
Slide 64: The slide again depicts Title of contents.
Slide 65: This slide outlines various statistical facts signifying importance of implementing machine learning algorithms in current business landscape.
Slide 66: This slide highlights advantages of using machine learning by businesses aimed at revolutionizing business operations.
Slide 67: This slide renders steps to implement machine learning aimed at improving business operations.
Slide 68: This slide highlights workflow of machine learning aimed ta helping businesses adopt the same and improve operations.
Slide 69: This slide highlights types of machine learning methods employed by businesses aimed at predicting outcomes using datasets efficiently.
Slide 70: This slide outlines real life applications of machine learning in various industries aimed at tailoring services and promoting trust among consumer.
Slide 71: This slide continues real life applications of machine learning in various industries aimed at tailoring services and promoting trust among consumer.
Slide 72: The slide again shows Title of contents.
Slide 73: This slide outlines advantages of using time series analysis by businesses aimed at identifying patterns and revolutionizing business operations.
Slide 74: This slide renders key components of time series analysis aimed at helping businesses scrutinize core causes of trends over a period of time.
Slide 75: This slide illustrates a flowchart highlighting methodology of time series analysis aimed at helping businesses in effective data processing.
Slide 76: This slide outlines steps undertaken by businesses aimed at processing time series data and derive insights.
Slide 77: This slide highlights techniques and models of time series analysis employed by businesses aimed at predicting outcomes using datasets efficiently.
Slide 78: This slide outlines real life applications of time series analysis in various industries aimed at tailoring services and promoting data driven operations.
Slide 79: This slide continues real life applications of time series analysis in various industries aimed at tailoring services and promoting data driven operations.
Slide 80: The slide displays Title of contents further.
Slide 81: This slide highlights advantages of using statistical analysis by businesses aimed at identifying patterns and revolutionizing business operations.
Slide 82: This slide outlines steps undertaken to conduct statistical analysis for deriving meaningful insights.
Slide 83: This slide highlights types of statistical analysis employed by businesses aimed at predicting outcomes using datasets efficiently.
Slide 84: This slide outlines real life applications of statistical analysis in various industries aimed compiling and reporting research findings.
Slide 85: The slide renders Title of contents further.
Slide 86: This slide provides an overview of data analytics tools used by business to improve data extraction and generate meaningful insights.
Slide 87: This slide outlines criteria to select appropriate data analytics tools aimed at helping businesses make informed decisions.
Slide 88: This slide provides overview of Tableau as a data analytics tools providing data visualization features.
Slide 89: This slide provides overview of Microsoft Power BI as a data analytics tool.
Slide 90: This slide briefs overview of Google Looker as a data analytics tool.
Slide 91: This slide gives overview of Zoho Analytics as a viable tool for data analysis.
Slide 92: This slide presents overview of Sisense as a viable tool for data analysis.
Slide 93: This slide provides a comparative analysis of data analytics tools aimed at helping businesses make appropriate choices regarding tool selection.
Slide 94: The slide displays Title of contents further.
Slide 95: This slide outlines steps to carry out data collection aimed at contributing to the overall success and reliability of project.
Slide 96: This slide displays key methods to collect data for analysis aimed at deriving major business insights.
Slide 97: This slide outlines best practices to be undertaken by businesses aimed at improving decision making and operations using data collection.
Slide 98: This slide highlights self service analytics providing data access to users to promote strategic initiatives.
Slide 99: This slide provides various methods undertaken by businesses for effectively communicating data analysis outcomes.
Slide 100: The slide shows Title of contents which is to be discussed further.
Slide 101: This slide illustrates a weekly timeline of activities undertaken while implementing data analytics tools and technologies in businesses.
Slide 102: The slide depicts another Title of contents.
Slide 103: The slide illustrates budget allocation towards data analytics tools and activities in form of a pie chart aimed at identifying.
Slide 104: The slide again renders Title of contents.
Slide 105: This slide highlights impact of implementing data analytics on major operations such as sales and operating expenses.
Slide 106: This slide outlines impact of data analytics techniques in pre and post implementation periods aimed at helping businesses make informed decisions.
Slide 107: The slide again shows Title of contents.
Slide 108: This slide outlines major barriers faced by businesses regarding data to make informed decisions and gain competitive advantage.
Slide 109: This slide renders major challenges faced by businesses while implementing data analytics.
Slide 110: The slide again depicts Title of contents.
Slide 111: This slide highlights future trends aimed at boosting data analytics market at a global level.
Slide 112: The slide again displays Title of contents.
Slide 113: This slide represents use case analysis of Airbnb utilizing data analytics to boost business profitability.
Slide 114: This slide shows use case analysis of Netflix utilizing data analytics to boost business profitability.
Slide 115: This slide presents use case analysis of Spotify utilizing data analytics to boost business profitability.
Slide 116: This slide shows all the icons included in the presentation.
Slide 117: This is a Thank You slide with address, contact numbers and email address.