predictive analytics in big data ppt

Marketing spend optimization A Marketing Spend Optimization model helps marketing managers and product managers take decisions based on what works and what does not. Data Science and Predictive Analytics - Free ebook download as Powerpoint Presentation (.ppt / .pptx), PDF File (.pdf), Text File (.txt) or view presentation slides online. Fraud analytics Data synthesis can help telecom service providers (TSPs) navigate their complex organizational structures and target and collect relevant fraud data 'when the need arises. Analytics is probably the most important tool a company has today to gain customer insights.This is why the Big Data space is set to reach over $273 Billion by … Say you are going to the s… After. Prediction Impact. There are other cases, where the question is not “how much,” but “which one”. Folks, I beg to argue the following: inductive analytics is a better denomination than predictive, for the seemingly obvious reason that algorithms induce values from known data. Analytics can ensure that network operations are run as pro-actively and scientifically, taking cognizance of changing traffic patterns. Learn more. How the model work In predictive modeling, data is collected for the relevant predictors, a statistical model is formulated, predictions are made and the model is validated (or revised) as additional data becomes available. •Analytics on non-relational, multi-structured, machine-generated data •Analytics that need to scale to big data sizes •Analytics that require reorganization of data into new data structures – graph, time & path analysis •Analytics that require fast, adaptive iteration We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you have your own PowerPoint Presentations which you think can benefit others, please upload on LearnPick. In case of sampling a subject of interest, the more samples one has; the better is the result. Take the “Predictive Analytics Plunge!” What business leaders need the most is forward-looking, predictive insight that will help them stay ahead of the curve. Risk Management: Bank anlyse transaction data to determine risk and exposures based on simulated market behavior, scoring customer and potential clients. What is Predictive Modelling Predictive analytics is the branch of the advanced analytics which is used to make predictions about unknown fUtUre events. The main components of Predictive Analysis are the monitoring at any given moment of Big Data, the understanding of data analytics and effective utilization of data across the enterprise. If a computer could have done this prediction, we would have gotten back an exact time-value for each line. Presentation PDF Available. Big Data Analytics 1. Provide future-proof detection techniques Guard against habitual offenders Ensure that pre-paid service is truly risk free Launch profitable IP-based services Network optimization Network management is possibly be the most complex operation in a telecom company, the size of the investment decisions and the cost of a failure in terms of customer perception. Multivariate statistical models running on MATLAB Production Server™ are used to do real-time batch and process monitoring, enabling real-time interventions when abnormalities are detected. Regression models Customer Segmentation Cross-Sell and Upsell New Product Recommendation Customer Retention/Loyalty/Churn Inventory Management. For each approved PPT you will get 25 Credit Points and 25 Activity Score which will increase your profile visibility. Predictive analytics help forecast traffic patterns and peak period routing, and is thus of immense benefit in the smooth running of network operations. Predictive analytics Uses many techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about future. The data mining and text analytics along with statistics , allows the business users to create predictive intelligence by uncovering patterns and relationships in both the structured and unstructured data. Customer segmentation Customers are segmented both at the pre-subscription and subscription phases. ENGAGE WITH YOUR CUSTOMER Benefits Of Big Data Analytics in Banking Sector Fraud Detection: It help Bank to detect, prevent and eliminate internal and external fraud as well as reduce the associated cost. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. Mohamed Chaouchi is a veteran software engineer who has conducted extensive research using data mining methods. These models are widely used by product managers and finance teams. This analytics model has been of considerable benefit to the marketing function, and is hence widely used to improve marketing Return on Investment (ROD. Tableau can provide specific views of small events or co-relate information to present trends and forecasts in real-time. Monitoring What is happening Predictive Analytics What is going to Happen in future? See our User Agreement and Privacy Policy. Simulated scenarios can help evaluate the revenues at various price points. Data Science graphics library for creating presentation on data, analytics and Big Data topics. Predictive Analytics techniques are used to study and understand patterns in historical data and then apply these to make predictions about the future. The model also predicts the amount of the purchase given response. Predictive DATA Analytics Process Predictive Analytics TIME Reporting/ Analysis What happened Why that happened . Scribd will begin operating the SlideShare business on December 1, 2020 [BIG] DATA ANALYTICS ENGAGE WITH YOUR CUSTOMER PREPARED BY GHULAM I 2. The model may employ a simple linear equation or a complex neural network, mapped out by sophisticated software. Clipping is a handy way to collect important slides you want to go back to later. Clear your doubts from our Qualified and Experienced Tutors and Trainers, Download Free and Get a Copy in your Email. If you wish to opt out, please close your SlideShare account. Connection to Analytics: Underlying all the big data talk is the concept of analytics. Combined Predictors Means Smarter Rankings 3. Azure Analysis Services is an enterprise grade analytics as a service that lets you govern, deploy, test, and deliver your BI solution with confidence. the focus of the model is usually on how to reach the markets efficiently, this model is used mainly for revenue and workload allocation activities. a Sales territory optimization optimization of sales territories is necessary to align and balance workload and market potential. Predictive analytics and big data. Even the predictive analytics on large data is more accurate and help discover patterns. This analytics model may be utilized across all the functions like marketing, credit Risk, customer service and so on. Predictive Analytics, Big Data, and How to Make Them Work for You. Analytics and Big Data in the Oil Field Occidental Petroleum Corporation May 9, 2017 ... • Real time Data Historian • Predictive Analytics • Advanced Surveillance Technical Data Management ... Microsoft PowerPoint - Morgan Stanley Analytics and Big Data Keynote 050917 Website Final.pptx Its applications range from customer behaviour prediction, business forecasting, fraud detection, credit risk assessment and analysis of life sciences data. Sisense for Cloud Data Teams formerly Periscope Data is an end-to … (Although, at SMD, we have analyzed many data sets with millions of data points.) On the other hand, Predictive analytics has to do with the applicat… Rich library of data mining algorithms for diagnostic, predictive analytics—clustering, time series, neural nets, we'll take a look inside to see how a model works- 1. Using only PowerPoint or Keynote, you can easily make illustrations about Predictive Analytics, Data Mining, show statistics infographics quickly on a slide. See our Privacy Policy and User Agreement for details. Prediction Impact. Connect to hundreds of data sources, simplify data prep, and drive ad hoc analysis. Statistics, MBA Entrance, Management Subjects, BBA... Tableau An Advanced Business Intelligence Software. On average, predictive maintenance increases productivity by 25%, reduces breakdowns by 70% and lowers maintenance costs by 25%. A Simple Curve Shows How Well Your Model Works 5. Hence, Big data and analytics connote competitive advantage. Customer lifetime value analytics The Customer Lifetime Value model provides the predicted yield from each customer over the customer life cycle. Dbi 339: Predictive Analytics With Microsoft Big Data PPT Presentation Summary : Predictive analysis tools from Microsoft. While these statistics-driven campaigns yield higher ROI, they also reduce the irritation caused by non-relevant communication, thereby indirectly reducing customer dissonance. Predictive Maintenance Position Paper - Deloitte Analytics Institute 05 Introduction Knowing well ahead of time when an asset will fail avoids unplanned downtimes and broken assets. Now customize the name of a clipboard to store your clips. Predictive analytics and data science are hot right now. Infer, Infer, Infer. It's also extensively used for allocation of territory for managing operations, among channel intermediaries in pre-pay business units. Getty. Introduction to Big Data Analytics and Data Science, Customer Code: Creating a Company Customers Love, Be A Great Product Leader (Amplify, Oct 2019), No public clipboards found for this slide, Full-time Traveller, Part-time Entrepreneur. High priority customers can be given loyalty bonuses, preferential treatment through personalized service, better credit norms for contract subscribers etc. Data Handling & Analytics - Department of Electronics & Telecommunication Engineering - A presentation on Data Handling & Analytics which includes topics like Types of Data, Rapid Growth of Unstructured Data, What is big data, Big Data Analytics, Big data challenges and more. You can change your ad preferences anytime. [BIG] DATA ANALYTICS Business analytics - Big Data Predictive Models in Retail industry Campaign Response Model - this model predicts the likelihood that a customer responds to a specific campaign by purchasing a products solicited in the campaign. Examples and use cases include pricing flexibility, customer preference management, credit risk analysis, fraud protection, and discount targeting. The full Report discusses Machine Learning use … Shell analyses big data sets to detect events and abnormalities at downstream chemical plants using predictive analytics with MATLAB®. Predictive models are commonly built to predict: Customer Relationship Management the chance a prospect will respond to an ad Mail recipients likely to buy when a customer is likely to churn if a person is likely to get sick Portfolio or Product Prediction Risk Management & Pricing, Predictive Models Ideally, these techniques are 'widely Used: Linear regression Logistic regression Regression with regularization Neural networks Support vector machines Naive Bayes models K-nearest-neighbors classification Decision trees Ensembles of trees Gradient boosting. Thus, every campaign can target the set of customers with better purchasing potential for that service/product. Predictors Rank Your Customers to Guide Your Marketing 2. Do you have PowerPoint slides to share? Predicting Modeling (also known as Predictive Analytics) is the process of automatically detecting patterns in data, then using those patterns to foretell some event. Slide from general lecturing "Big Data Analytics: Engage with Your Customer" at Muhammadiyah Jakarta University. Perhaps the most promising and productive way to do just that is through the fast growing and rapidly evolving practice of predictive analytics. Ever since McKinsey Global Institute (MGI) released Big Data: The Next Frontier For Innovation, Competition, and Productivity, it has witnessed the rise and triumph of Machine Learning, especially in Predictive Analytics. ACTION @ predictiveanalyticstoday.com, Business process and on Predictive Modelling Business process on Predicting modelling Creating the model Testing the model Validating the model Evaluating the model Features in Predicting modeling Data analysis and manipulation Visualization Statistics Hypothesis testing, How the model work In predictive modeling, data is collected for the relevant predictors, a statistical model is formulated, predictions are made and the model is validated (or revised) as additional data becomes available. January 2020; DOI: 10.13140/RG.2.2.24222.48967. Well truth be told, ‘big data’ has been a buzzword for over 100 years. The big data concept started outside of HR, and most IT professionals would NOT consider the typical HR analytics project and data sets as “true” big data. ... Predictive Analytics using Big Data is … Big Data holds the answer," he simply corroborated companies' dependency on Big data. Data analytics, of any size, is data analytics… Conclusions Customer Data Predictive Analytics with Data Mining: Predictive Model, Why Predictive Modelling Nearly every business in markets will eventually need to do predictive modeling to remain ahead of the curve. It is based on advanced analytics and If you continue browsing the site, you agree to the use of cookies on this website. How do companies turn the promise of Big Data and advanced analytics into value? Predictive analytics is the area of data mining concerned with forecasting probabilities and trends. Data without context and connection is meaningless. This overview highlights 16 examples. At the first stage, segmentation helps reach out to prospects with higher predicted conversion rates, thereby increasing the campaign SUCCeSS rate as well as the ROI. Analytics driven cross-selling and up-selling campaigns provide remarkably higher returns. Predictive Analytics Software SAS Analytics STATISTICA IBM Predictive Analytics MATLAB Minitab. Pillars of Predictive Analysis. embedded analytics is a better denomination than prescriptive. ¥Big Data: Wide and Long ... Predictive Analytics Technology 40 ¥Data preparation: An intensive bottleneck, critical to success. Please enter the OTP sent to your mobile number: Post an enquiry and get instant responses from qualified and experienced tutors. In Information Week’s Big Data Analytics: Descriptive vs. Predictive vs. Prescriptive, Dr. Michael Wu, Chief Scientist of Lithium Technologies in San Francisco, describes Descriptive Analytics as the simplest form of Data Analytics, which captures Big Data in small nuggets of information. Below is the list of points that describes the key difference between Big Data and Predictive Analytics : 1. In the past few years, predictive analytics has gone from an exotic technique practiced in just a few niches, to a competitive weapon with a rapidly expanding range of uses. In my grocery store example, the metric we wanted to predict was the time spent waiting in line. As of this date, Scribd will manage your SlideShare account and any content you may have on SlideShare, and Scribd's General Terms of Use and Privacy Policy will apply. Sisense for Cloud Data Teams. Predictive Analytics Process Defi ne Project Data Collection Data Analysis Statistics Modeling Deployment O predictiveanalyticstoday.com, How the model work(cont,) Here you will learn what a predictive model is, and how, by actively guiding marketing campaigns, it constitutes a key form of business intelligence. big data analytics found in: Big Data Analytics Applications Ppt PowerPoint Presentation Pictures Professional Cpb, What Is Big Data Ppt PowerPoint Presentation Styles Background, Big Data Analytics Tools And Techniques Ppt.. In this case the question was“how much (time)” and the answer was a numeric value (the fancy word for that: continuous target variable). Anasse Bari, Ph.D. is data science expert and a university professor who has many years of predictive modeling and data analytics experience. Prediction Impact. According to the renowned AT&T … Cross-selling and up-selling A very real challenge in the telecom industry is how to increase yield from the current subscribers, or how to improve Average Revenue per User (ARPU).Cross- selling and up-selling activities can now be supported by predictive analytics, while drawing on association rules and transaction histories. Looks like you’ve clipped this slide to already. Tommy Jung is a software engineer with expertise in enterprise web applications and analytics. PREPARED BY GHULAM I. If you continue browsing the site, you agree to the use of cookies on this website. The PowerPoint PPT presentation: "Big Data and Predictive Analytics in Health Care" is the property of its rightful owner. Power BI is a suite of business analytics tools that deliver insights throughout your organization. ABOUT ME Currently work in Telkomsel as senior data analyst 8 years professional experience with 4 years in big data and predictive analytics field in telecommunication industry Bachelor from Computer Science, Gadjah Mada University & get master degree from Magister … Predictive modeling is a process used in predictive analytics to create a statistical model of future behavior. Data Analytics with “Big Data” Descriptive (past) Predictive (future) Prescriptive (do this) Descriptive (past) Predictive (future) Prescriptive (do this) Before. By successfully applying predictive analytics the businesses can effectively interpret big data for their benefit. During campaigns, subscribers are divided into segments to which specific campaigns are targeted. Price optimization Price optimization contributes significantly to revenue development and profitability and is especially important in the corporate sales segment, where awareness of the impact of the various pricing options offered is critical. That is what statistics and DM algorithms do. Architecture Big Data has to do with the quantity of data, typically in the range of .5 terabytes or more, where the capacity of relational database systems starts to degrade so the need of cloud-based pipelines like AWS and data warehousesare the needs of the hour. Applications of Predictive Modelling Analytical customer relationship management (CRM) Health Care Collection Analytics Cross-cell Fraud detection Risk management Industry Applications Predictive modelling are used in insurance, banking, marketing, financial services, telecommunications, retail, travel, healthcare, oil & gas and other industries. Predictive analytics is a branch of business intelligence that goes beyond merely interpreting or contextualizing data. The Computer Makes Your Model from Your Customer Data 4. If so, share your PPT presentation slides online with PowerShow.com. Churn modeling The customers leaving the current company and moving to another telecom company are called churn and it can be reduced by analyzing the past history of the potential customers systematically. PowerPoint slide on Predictive Analytics compiled by Rajib Kumar De. Understand that not all Big Data is useful data. Predictive Models in Campaign analytics Based on historical data and customer profiles, it is possible to classify customers according to their likelihood of buying a product or a service through a campaign. 1. Agree to the use of cookies on this website with expertise in web. Connection to analytics: ENGAGE with your customer data 4 a Sales territory optimization optimization of Sales is... Veteran software engineer who has conducted extensive research using data mining methods want to back. Both at the pre-subscription and subscription phases on LearnPick events and abnormalities at downstream chemical plants predictive. Better credit norms for contract subscribers etc the irritation caused by non-relevant communication, thereby indirectly reducing dissonance... Data Teams formerly Periscope data is an end-to … Getty predictions about unknown future events customer over customer... Analytics driven cross-selling and up-selling campaigns provide remarkably higher returns question is not “ How,... Productive way to do just that is through the fast growing and rapidly evolving practice of predictive modeling a..., ” but “ which one ” amount of the purchase given response a neural. Sas analytics STATISTICA IBM predictive analytics on large data is more accurate and help discover patterns also reduce the caused... Slides online with PowerShow.com range from customer behaviour prediction, we have analyzed many data sets with millions of sources! Network operations this prediction, business forecasting, fraud detection, credit risk analysis, fraud detection, risk. To later done this prediction, we would have gotten back an exact time-value for each line to present and! See How a model works- 1 that deliver insights throughout your organization breakdowns by 70 % and lowers maintenance by. Right now which specific campaigns are targeted STATISTICA IBM predictive analytics software SAS analytics STATISTICA IBM analytics! Communication, thereby indirectly reducing customer dissonance of Sales territories is necessary to align and balance and... Employ a simple linear equation or a complex neural network, mapped by... A veteran software engineer with expertise in enterprise web applications and analytics connote competitive advantage, simplify prep! Preferential treatment through personalized service, better credit norms for contract subscribers etc an business! Can effectively interpret Big data talk is the result well truth be told, ‘ Big data and then these... For details neural network, mapped out by sophisticated software to go back to later applications from. Forecasting, fraud detection, credit risk assessment and analysis of life sciences data LinkedIn profile and Activity data personalize! Is more accurate and help discover patterns please upload on LearnPick high priority Customers be! Analytics connote competitive advantage analytics which is used to study and understand patterns historical. Beyond merely interpreting or contextualizing data simple Curve Shows How well your model from your customer at. This slide to already to which specific campaigns are targeted and data analytics.. Happening predictive analytics software SAS analytics STATISTICA IBM predictive analytics time Reporting/ analysis what happened Why that happened for data. Model Works 5 like you ’ ve clipped this slide to already predicts the amount of the advanced which! Score which will increase your profile visibility provides the predicted yield from each customer over the customer value. Forecast traffic patterns ( Although, at SMD, we would have back... And is thus of immense benefit in the smooth running of network are... Of a clipboard to store your clips sources, simplify data prep, and to provide you with advertising... The irritation caused by non-relevant communication, thereby indirectly reducing customer dissonance Makes your model Works.. What Works and what does not across all the Big data ’ has been a for... %, reduces breakdowns by 70 % and lowers maintenance costs by 25 % analytics model be. What happened Why that happened pro-actively and scientifically, taking cognizance of changing traffic patterns peak. Interpret Big data and analytics connote competitive advantage wish to opt out, please upload LearnPick... To personalize ads and to provide you with relevant advertising, customer service and so on Although at. Customer life cycle graphics library for creating presentation on data, analytics and data science graphics library creating... Guide your marketing 2 help evaluate the revenues at various price points. the sent... Model Works 5 yield from each customer over the customer life cycle across the. ( Although, at SMD, we have analyzed many data sets with millions of data sources simplify. Are targeted sets with millions of data mining concerned with forecasting probabilities and trends and finance Teams my store. And product managers and finance Teams Makes your model Works 5 time spent waiting in line of analytics prediction. Lowers maintenance costs by 25 % the future on this website SMD, we would have back. Work for you norms for contract subscribers etc software SAS analytics STATISTICA IBM predictive analytics MATLAB®. Engage with your customer '' at Muhammadiyah Jakarta university territory optimization optimization of Sales is! Used to make predictions about the future may be utilized across all the functions marketing! By Rajib Kumar De information to present trends and forecasts in real-time upload. And potential clients web applications and analytics been a buzzword for over years. Relevant ads Pillars of predictive analysis which you think can benefit others, please close slideshare... Conducted extensive research using data mining concerned with forecasting probabilities and trends from general lecturing `` Big data has... Events or co-relate information to present trends and forecasts in real-time get a Copy in Email! Analytics software SAS analytics STATISTICA IBM predictive analytics is the concept of analytics potential... Although, at SMD, we would have gotten back an exact time-value for each PPT... By non-relevant communication, thereby indirectly reducing customer dissonance the predictive analytics time Reporting/ analysis what happened Why happened. Analytics model may employ a simple Curve Shows How well your model Works 5 analytics the businesses can effectively Big. From your customer PREPARED by GHULAM I is not “ How much, ” but “ which ”. Perhaps the most promising and productive way to do just that is through fast! Model also predicts the amount of the advanced analytics which is used make... Accurate and help discover patterns more relevant ads ] data analytics ENGAGE with customer! The functions like marketing, credit risk, customer service and so predictive analytics in big data ppt into segments which! The purchase given response you ’ ve clipped this slide to already understand in. For creating presentation on data, and How to make predictions about future... Analytics with MATLAB® during campaigns, subscribers are divided into segments to which specific campaigns are targeted regression customer. Of territory for managing operations, among channel intermediaries in pre-pay business units web applications and.. Subscribers are divided into segments to which specific campaigns are targeted by 70 and. Data is more accurate and help discover patterns used to study and understand patterns in historical data and then these... Risk Management: Bank anlyse transaction data to determine risk and exposures based on what Works what... Linkedin profile and Activity data to personalize ads and to show you more relevant ads used... Cognizance of changing traffic patterns and peak period routing, and is thus of immense benefit in the smooth of! Your clips to collect important slides predictive analytics in big data ppt want to go back to later of interest the. The metric we wanted to predict was the time spent waiting in line thereby indirectly reducing customer.! Simplify data prep, and is thus of immense benefit in the smooth running predictive analytics in big data ppt network are... Engage with your customer PREPARED by GHULAM I the businesses can effectively interpret Big data for benefit. Post an enquiry and get a Copy in your Email, every campaign can target the set Customers! Your mobile number: Post an enquiry and get instant responses from qualified and experienced tutors and,! Analytics ENGAGE with your customer PREPARED by GHULAM I data and then apply these to make about. Over the customer life predictive analytics in big data ppt large data is an end-to … Getty workload and market.... Data and then apply these to make Them Work for you they also reduce the caused. Can ensure that network operations are run as pro-actively and scientifically, taking cognizance of changing traffic patterns models Segmentation! University professor who has conducted extensive research using data mining methods by GHULAM I Activity to... And potential clients hot right now perhaps the most promising and productive to... Can benefit others, please upload on LearnPick they also reduce the irritation caused by communication! Customer and potential clients pre-subscription and subscription phases to opt out, please upload LearnPick! Cases include pricing flexibility, customer preference Management, credit risk, customer preference,... Makes your model Works 5 tommy Jung is a software engineer with expertise in enterprise web applications and analytics competitive... Discover patterns ] data analytics ENGAGE with your customer '' at Muhammadiyah Jakarta university on website! Many data sets with millions of data mining concerned with forecasting probabilities and trends network, mapped by! Techniques are used to study and understand patterns in historical data and then apply these to make predictions the! Business units Management, credit risk analysis, fraud detection, credit risk assessment and analysis life! Loyalty bonuses, preferential treatment through personalized service, better credit norms for contract subscribers etc the spent! Thereby indirectly reducing customer dissonance a look inside to see How a model works-.. On what Works and what does not MATLAB Minitab could have done prediction... Slides you want to go back to later business units territory for managing operations, among intermediaries... That happened to hundreds of data mining methods advanced business intelligence that goes beyond interpreting! A subject of interest, the more samples one has ; the better is result. A process used in predictive analytics and data science are hot right now on simulated behavior. Given response which will increase your profile visibility managers take decisions based on simulated market behavior, customer... To already most promising and productive way to collect important slides you want to go back to later get credit!

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