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Lecture 37
- 1. DWH-Ahsan AbdullahDWH-Ahsan Abdullah 11 Data WarehousingData Warehousing Lecture-37Lecture-37 Case Study: Agri-Data WarehouseCase Study: Agri-Data Warehouse Virtual University of PakistanVirtual University of Pakistan Ahsan Abdullah Assoc. Prof. & Head Center for Agro-Informatics Research www.nu.edu.pk/cairindex.asp FAST National University of Computers & Emerging Sciences, IslamabadFAST National University of Computers & Emerging Sciences, Islamabad
- 3. DWH-Ahsan Abdullah 3 Area under studyArea under study
- 4. DWH-Ahsan Abdullah 4 Area under study: MapArea under study: Map Key Markaz 1 Bosan 2 Qadirpurran 3 Multan 4 Makhdum Rashid 5 Mumtazabad 6 Shujabad 7 Hafizwala 8 Jalalpur Pirwala 9 Qasba Marral GraphicsGraphics
- 5. DWH-Ahsan Abdullah 5 Major PlayersMajor Players
- 6. DWH-Ahsan Abdullah 6 Pests & PredatorsPests & Predators Pests Predators Source: United States Department of Agriculture (USDA) GraphicsGraphics
- 7. DWH-Ahsan Abdullah 7 Economic Threshold Level (ETL_A)Economic Threshold Level (ETL_A)
- 8. DWH-Ahsan Abdullah 8 ETL_A: GraphETL_A: Graph Time ETL_A PestPopulation Economic Injury GraphicsGraphics
- 9. DWH-Ahsan Abdullah 9 The needThe need
- 10. DWH-Ahsan Abdullah 10 The need: IT in AgricultureThe need: IT in Agriculture
- 11. DWH-Ahsan Abdullah 11 Agro-InformaticsAgro-Informatics “I.T. sector is at the heart of the economic revival of Pakistan” President of Pakistan, Launching of VU, Mar. 23, 2003. Agriculture is the backbone of our economy, about 70% of the population is dependent on it. IT is an enabler, and has the potential to benefit everyone when applied in Agriculture. IT + Agriculture: A win-win scenario. ALL Goes to graphics
- 12. DWH-Ahsan Abdullah 12 Agro-Informatics: Interesting URLAgro-Informatics: Interesting URL To know more about Agro-Informatics, visit www.nu.edu.pk/cairindex.asp ALL Goes to graphics
- 13. DWH-Ahsan Abdullah 13 How to go about?How to go about?
- 14. DWH-Ahsan Abdullah 14 The 12-step Approach of Shaku AtreThe 12-step Approach of Shaku Atre ALL Goes to graphics
- 15. DWH-Ahsan Abdullah 15 Step-1: Determine User’s needsStep-1: Determine User’s needs
- 16. DWH-Ahsan Abdullah 16 Step-1: Determine Users needsStep-1: Determine Users needs
- 17. DWH-Ahsan Abdullah 17 Steps-2&3: Determine DBMS Sever & Hardware PlatformSteps-2&3: Determine DBMS Sever & Hardware Platform
- 18. DWH-Ahsan Abdullah 18 Step-4: Information & Data ModelingStep-4: Information & Data Modeling Dimensional ModelingDimensional Modeling GraphicsGraphics
- 19. DWH-Ahsan Abdullah 19 Simplified ERDSimplified ERD Step-4: Information & Data ModelingStep-4: Information & Data Modeling Other field inputs such as irrigation, fertilizer etc. not included as data not available GraphicsGraphics
- 20. DWH-Ahsan Abdullah 20Logical & Physical DesignLogical & Physical Design Step-4: Information & Data ModelingStep-4: Information & Data Modeling (optional) KEY WFN: White Fly Nymph WFA: White Fly Adult W: White B: Brown S: Small Larvae L: Large Larvae GraphicsGraphics
- 21. DWH-Ahsan Abdullah 21 Step-5: Construct Metadata RepositoryStep-5: Construct Metadata Repository
- 22. DWH-Ahsan Abdullah 22 Step-5: Surprise caseStep-5: Surprise case -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Jassid WhiteFly_Nymph WhiteFly_Adult Thrip Mite SBW ABW_White_Eggs ABW_Brown_Eggs ABW_Larvae_Small ABW_Larvae_Large PBW_RF PBW_Bolls Correlation Ball Worm ComplexSucking pests SBW: Spotted Ball Worm ABW: Army Ball Worm PBW: Pink Ball Worm If pest population is low, predator population will also be low, because there will be less “food” for predators to live on i.e. pests. GraphicsGraphics
Editor's Notes
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.
- <number> Moore’s law on increase in performance of CPUs and decrease in cost has been surpassed by the increase in storage space and decrease in cost. Secondly as I mentioned earlier the data warehouse has the historical data. And one thing that we have learned by using information is that, “the best predictor of the future is the past”. You use historical data, you then use your insight to how the environment is changing. Because of course you cannot use data extracted from the past. You have to have to bring your insight as to how the environment is changing in order to predict the future accurately. So why would you want data warehouse in an organization? First of all a data warehouse gives a total view of an organization. If you look at the operational system the databases in most environments, the databases are designed around different lines of business. Lets say I am a bank for e.g. a bank will typically have current Accounts. They will have another system for leasing, and another system for managing credit cards and another system for every different kind of business they are in. However, no where they have the total view of the environment from the customers perspective. Because the transaction processing systems are typically designed around functional areas, within a business environment. For good decision making you should be able to integrate the data across the organization. So the idea here is to give the total view of the organization especially from a customer’s perspective within the data warehouse. Consider a bank, which is losing customers, for reasons not known. However, one thing is known that the bank is losing business. Therefore, it is important, actually critical to understand which customers have left you and why they have left. This will give you the ability to predict going forward (in future), which customers will leave you. So we are going to talk about this in the course using data mining algorithms, like clustering, classification, regression analysis etc. This being another example of using historical data to predict the future. So I can predict today, which customers will leave me in the nest 3 months before they even leave. There, can be, and there are whole courses on data mining, but we will just have an applied introduction about data mining in this course.