Fujitsu big-data-software-v1-brochure

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http://www.fujitsu.com/global/services/software/interstage/solutions/big-data/ Customer case uses of Fujitsu's big data software - for traffic, healthcare, retail

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Fujitsu big-data-software-v1-brochure

  1. 1. Fujitsu Big Data Software Use CasesContactWebsite: www.fujitsu.com http://www.fujitsu.com/global/services/software/interstage/solutions/big-data
  2. 2. Fujitsu Big Data Use Cases Using Big Data Opens the Door to New Business Areas The use of Big Data is needed in order to discover trends and predictions, hidden in data generated over the Big Data Usage Scenarios course of daily business activities. Big Data has now reached the stage of practical use through advance- ments in ICT, it has become an extremely important key to opening doors to new business opportunities. Examples of Big Data use that brings about new possibilities in three different business situations with varying Fujitsu supports our customers’ strategic ICT investment and business strategies by providing Big Data business needs. solutions. Improve Mission-Critical Strategic Use of Challenge New Business Areas System Processing Information Systems Three Characteristics of Big Data and Tips for Use With High-Speed Batch With Extraction of New Value from With Real Time Analysis Processing Structured and Unstructured Data There are three main keywords when it comes to using Big Data: volume (large volume data), variety (wide range of data), and velocity (time sensitive data). By dealing with these characteristics, business scenarios can be created, Daily Analysis of The Hottest-Selling Predict Trouble and Take Proactive Distribute Coupons Using Real Time Products Case A Actions Case B Location Analysis Case D deepened, expanded, and changed. By analyzing billions of sales data items for Signs of customer issues now can be A electric coupon delivery service sends all stores through batch processing, each detected quickly by automatically e-mails to customers with recommenda- Volume (Large Volume Data) Variety (Wide Range of Data) Velocity (Time Sensitive Data) store can accurately select the hottest- selling products at a store level. This has extracting patterns from records of past complaints and information on SNS. This tions matched to their tastes derived from their location information, membership Large volumes of data extending Unstructured data such as text and led to an increase in sales. quick response will lead to a higher degree information, and information on nearby into the TB or PB range images Rapid creation of new data of customer satisfaction. stores. Optimize Resource Assignment and Tip for use Tip for use Tip for use Make-To-Stock Production by Reducing Analyze Access Logs for Online Sales and Vehicle On-Board Device Information In the past traditional RDBs have not been Various kinds of unstructured data such as New information created every second such Electronic Report Batch Processing Time Discover New Value Case C Based on Locations and Times Case E able to handle large volume data such as web tweets exchanged on SNS*1, which were as sensor data or location information from Creating electronic reports though batch By performing analysis on a combination of By linking large volumes of traffic access logs and task logs, or if they have, the rarely used in business activities before, or IC tags or smart devices can be processed in tens of millions or billions of data items call history data from call centers, can be real-time. processing, which have thus far been large volume web access logs and purchase information and vehicle information, in would take days to process. Now, these data combined with conventional data and considered an overnight job, can now be histories, the hottest-selling products that terms of location and time, efficient and items can be processed faster than ever analyzed. completed in significantly less time. Data correlate to specific customers, can be safe traffic conditions can now be applied before. can be processed faster and more fre- discovered, and create new business through predicting and ascertaining traffic quently providing businesses with more opportunities. conditions based on actual data. regular and up-to-date information. As a result, resource assignment can be Correlation Analysis Between Diseases Use Comprehensive Health Information Significance of Utilizing Big Data optimized and the accuracy of make-to- and Lifestyles Using Electronic Medical Effectively Case F stock is increased. Records Big Data generated in social or business activities, including information from SNS, sensors or other data was rarely handled By combining and analyzing health By combining lifestyle information with checkup data and medical history data, the by conventional information systems. The use of Big Data is key to the success of businesses in the future. Realize Around-the-Clock System risk of contracting a disease in the future electronic medical records the customer Operation by Concurrent Execution of now can be predicted. This information can In essence using Big Data is about collecting and analyzing various kinds of data generated from business activities. The can now predict lifestyle-related diseases. Online Processing and Batch Processing With an understanding of correlations then be used by healthcare specialists to information from this analysis can then be used to discover new trends or patterns to make business decisions or create new Perform in-memory online processing and between diseases and calorie intakes, step advise patients and subscribers ways they businesses opportunities. batch processing simultaneously creating a counts per day and body weights we can can improve their health. business system that can continually help people adjust their lifestyles to reduce Various Kinds of Data Generated from Business Activities function without going offline or without the risk of disease. Energy Supply and Demand interruption. Optimization Daily Purchase History Collect Analyze Analyze the Flow of Customers for Store Reports By monitoring real time information from System Integration for Improving the Layout Improvement smart meters, including the amounts of Large Volume Improved Efficiency of Sales Activities By combining store camera records electricity generated, sold, and trans- Data Accuracy When integrated, the time required for (customer flow, sex, ages, the time they mitted, energy forecasts for supply and overnight batch processing in the inventory visited) with weather conditions, and sales demand can be optimized. Repair Logistics management system and the sales system data from the POS system, we can analyze History Operation Information is significantly reduced. System integration the optimal store layout. A store can easily Predict Multifunctional Printer Failure Data enables sales activities to be performed and Provide Preventive Maintenance increase sales figures through effective Real Time Faster Cycle efficiently based on accurate inventory layout improvements. By collecting logs of multifunctional levels. printers in real-time and analyzing them Sensors Act Decide against past failures, maintenance can be Social scheduled before parts need to be Media replaced. With a reduction in printing failures, customer satisfaction can be drastically improved. The process allows you to collect various kinds of large volume data, analyze it accurately, make quick decisions and take actions in real time. Using Big Data will become increasingly significant for businesses as they engage in new activities and explore new opportunities. *1 Social Networking Service01 02
  3. 3. Fujitsu Big Data Use Cases Using Big Data Opens the Door to New Business Areas The use of Big Data is needed in order to discover trends and predictions, hidden in data generated over the Big Data Usage Scenarios course of daily business activities. Big Data has now reached the stage of practical use through advance- ments in ICT, it has become an extremely important key to opening doors to new business opportunities. Examples of Big Data use that brings about new possibilities in three different business situations with varying Fujitsu supports our customers’ strategic ICT investment and business strategies by providing Big Data business needs. solutions. Improve Mission-Critical Strategic Use of Challenge New Business Areas System Processing Information Systems Three Characteristics of Big Data and Tips for Use With High-Speed Batch With Extraction of New Value from With Real Time Analysis Processing Structured and Unstructured Data There are three main keywords when it comes to using Big Data: volume (large volume data), variety (wide range of data), and velocity (time sensitive data). By dealing with these characteristics, business scenarios can be created, Daily Analysis of The Hottest-Selling Predict Trouble and Take Proactive Distribute Coupons Using Real Time Products Case A Actions Case B Location Analysis Case D deepened, expanded, and changed. By analyzing billions of sales data items for Signs of customer issues now can be A electric coupon delivery service sends all stores through batch processing, each detected quickly by automatically e-mails to customers with recommenda- Volume (Large Volume Data) Variety (Wide Range of Data) Velocity (Time Sensitive Data) store can accurately select the hottest- selling products at a store level. This has extracting patterns from records of past complaints and information on SNS. This tions matched to their tastes derived from their location information, membership Large volumes of data extending Unstructured data such as text and led to an increase in sales. quick response will lead to a higher degree information, and information on nearby into the TB or PB range images Rapid creation of new data of customer satisfaction. stores. Optimize Resource Assignment and Tip for use Tip for use Tip for use Make-To-Stock Production by Reducing Analyze Access Logs for Online Sales and Vehicle On-Board Device Information In the past traditional RDBs have not been Various kinds of unstructured data such as New information created every second such Electronic Report Batch Processing Time Discover New Value Case C Based on Locations and Times Case E able to handle large volume data such as web tweets exchanged on SNS*1, which were as sensor data or location information from Creating electronic reports though batch By performing analysis on a combination of By linking large volumes of traffic access logs and task logs, or if they have, the rarely used in business activities before, or IC tags or smart devices can be processed in tens of millions or billions of data items call history data from call centers, can be real-time. processing, which have thus far been large volume web access logs and purchase information and vehicle information, in would take days to process. Now, these data combined with conventional data and considered an overnight job, can now be histories, the hottest-selling products that terms of location and time, efficient and items can be processed faster than ever analyzed. completed in significantly less time. Data correlate to specific customers, can be safe traffic conditions can now be applied before. can be processed faster and more fre- discovered, and create new business through predicting and ascertaining traffic quently providing businesses with more opportunities. conditions based on actual data. regular and up-to-date information. As a result, resource assignment can be Correlation Analysis Between Diseases Use Comprehensive Health Information Significance of Utilizing Big Data optimized and the accuracy of make-to- and Lifestyles Using Electronic Medical Effectively Case F stock is increased. Records Big Data generated in social or business activities, including information from SNS, sensors or other data was rarely handled By combining and analyzing health By combining lifestyle information with checkup data and medical history data, the by conventional information systems. The use of Big Data is key to the success of businesses in the future. Realize Around-the-Clock System risk of contracting a disease in the future electronic medical records the customer Operation by Concurrent Execution of now can be predicted. This information can In essence using Big Data is about collecting and analyzing various kinds of data generated from business activities. The can now predict lifestyle-related diseases. Online Processing and Batch Processing With an understanding of correlations then be used by healthcare specialists to information from this analysis can then be used to discover new trends or patterns to make business decisions or create new Perform in-memory online processing and between diseases and calorie intakes, step advise patients and subscribers ways they businesses opportunities. batch processing simultaneously creating a counts per day and body weights we can can improve their health. business system that can continually help people adjust their lifestyles to reduce Various Kinds of Data Generated from Business Activities function without going offline or without the risk of disease. Energy Supply and Demand interruption. Optimization Daily Purchase History Collect Analyze Analyze the Flow of Customers for Store Reports By monitoring real time information from System Integration for Improving the Layout Improvement smart meters, including the amounts of Large Volume Improved Efficiency of Sales Activities By combining store camera records electricity generated, sold, and trans- Data Accuracy When integrated, the time required for (customer flow, sex, ages, the time they mitted, energy forecasts for supply and overnight batch processing in the inventory visited) with weather conditions, and sales demand can be optimized. Repair Logistics management system and the sales system data from the POS system, we can analyze History Operation Information is significantly reduced. System integration the optimal store layout. A store can easily Predict Multifunctional Printer Failure Data enables sales activities to be performed and Provide Preventive Maintenance increase sales figures through effective Real Time Faster Cycle efficiently based on accurate inventory layout improvements. By collecting logs of multifunctional levels. printers in real-time and analyzing them Sensors Act Decide against past failures, maintenance can be Social scheduled before parts need to be Media replaced. With a reduction in printing failures, customer satisfaction can be drastically improved. The process allows you to collect various kinds of large volume data, analyze it accurately, make quick decisions and take actions in real time. Using Big Data will become increasingly significant for businesses as they engage in new activities and explore new opportunities. *1 Social Networking Service01 02
  4. 4. Fujitsu Big Data Use Cases Use Cases Case Daily Analysis of The Hottest-Selling Products Case Distribute Coupons Using Real Time Location Analysis A Challenge: Increase the number of stores to be analyzed from 500 to the entire chain and expand the profits of the whole group D Challenge: Create new customers, through a new service, that sends e-mails containing recommendations based on the members’ current locations and their tastes Our Solution Parallel Our Solution Execute 10 times more batches processing, in the same amount Distributed Compare customer location information, against membership Complex event of time, by using parallel distributed processing. This will expand Processing information and store information, in real-time, to distribute processing the number of stores that can be analyzed from 500 to the entire e-mails containing appropriate recommendations. Location Information chain. Benefits Membership Store Coupon Information Information Benefits By sending members coupons that suit their taste while in the From a specific area Store By ordering stock based on accurate analyses of the hottest- (500 stores) to the whole country proximity of the nearby stores, the coupon distribution company Automatically select appropriate selling products rather than relying on intuition, the stores can can improve the convenience and satisfaction of the members. Tens of TBs coupons by matching member expand sales and profits with less waste and more efficiency. Peak hours and store information Product master Create new customers for stores and to the system, and attract 1 million items per second By analyzing large volume data repeatedly, the stores can now Sales records customers during off peak seasons. provide their customers with appropriate information based on Real Time marketing intelligence and increase the number of regular customers. Case Predict Trouble and Take Proactive Action Case Vehicle On-Board Device Information Based on Locations and Times B Challenge: Combine and analyze a variety of data to detect signs of issues at an early stage and prevent them becoming serious problems E Challenge: Link large volumes of vehicle on-board device information with other information for efficient and safe driving Our Solution Our Solution Data accompanied by Complex Event Processing Customers location information Analyze text information such as past complaints and the Link large volumes of information including road conditions and Determine current conditions and responses to them, automatically extract patterns that may lead information from the vehicle on-board device, such as locations respond to the conditions in real-time to serious problems, compare them against current situations to Analyze and and times in order to predict traffic congestion from different Customer The machine is hot Predict Probe detect signs of complications, and then take the necessary Consulting Information and radiating heat. angles and analyze fuel efficiency. measures. • Monitor current Link vehicle information, latitudes, longitudes, vehicle speeds Records of Response situations Add information exchanged through SNS to analytic data to • Predict the future etc.., to information that has already analyzed including locations Sensor gain unstructured market information. • Prevent recurrence and times. This will enable traffic conditions to be determined and appropriate traveling routes will feedback to the on-board Data processing Analysis Benefits Condition devices. By adding SNS information and tweets to the analysis, the signs Processed event information is accumulated and reused when Sensor of customer issues can be detected before formal complaints are SNS Number of tweets: Facility Information 200 million/day needed. Information Facility received. Probe Location Map By quickly and accurately analyzing complaints, customer Social Media Preventive Measures Benefits External information (coordinates) Information satisfaction levels are discovered in real-time and any sign of a By predicting traffic conditions based on actual data, the drivers Analyze past information and potential issue can be detected. can now determine roads to avoid congestion, improve fuel predict the future efficiency and prevent dangerous driving. Parallel distributed processing with A higher degree of customer trust is earned along with analysis and prediction minimizing the time taken to respond. Case Analyze Access Logs for Online Sales and Discover New Value Case Use Comprehensive Health Information Effectively C Challenge: Combine analysis results of access logs with purchase history information to expand the business F Challenge: Integrate health information from various sources to help patients and healthcare insurance subscribers promote their health Our Solution Online 200 million 50,000 items Our Solution Prescription Data Checkup Data Vital Statistics shopping site items/month Unstructured (number of products) The Combination of what customers have purchased and what data must be DWH/BI Analyze health information including vital statistics for processed and Number products have been frequently viewed by web users, can provide Access extracted. of subscribers who sign up for this service. This will allow them to insight into potential growth areas. logs accesses understand their current health condition and address future large Tally the number of by age magnitude of accesses by health risks. Benefits data product and age Integrate and analyze individual and general, medical history Information held by health insurance associations Information held by employers Information held by individuals Member 20,000 By performing analysis on a combination of large volumes management DB items/month data, which was previously accessed separately, in a secure of web access logs and purchase histories, hidden hot-selling manner to predict medical benefits in the future. Membership products can be exploited and new business opportunities information Analyze, fuse, explored. and visualize Benefits As there is no need to transfer data to a processing server, New value created by Based on the results of the analysis, the health specialist can 500,000 the data can be analyzed quickly leading to a reduction in items/month fusing information now offer health guidance more objectively and promote the Integrate man-hours. subscribers’ health. Purchase Analysis of history conventional Medical expenditure is a major issue in the health industry and Parallel distributed processing purchase history Product A Product B Product C Product X with analysis and prediction Product name can be normalized by improvements to subscriber’s health.03 04
  5. 5. Fujitsu Big Data Use Cases Use Cases Case Daily Analysis of The Hottest-Selling Products Case Distribute Coupons Using Real Time Location Analysis A Challenge: Increase the number of stores to be analyzed from 500 to the entire chain and expand the profits of the whole group D Challenge: Create new customers, through a new service, that sends e-mails containing recommendations based on the members’ current locations and their tastes Our Solution Parallel Our Solution Execute 10 times more batches processing, in the same amount Distributed Compare customer location information, against membership Complex event of time, by using parallel distributed processing. This will expand Processing information and store information, in real-time, to distribute processing the number of stores that can be analyzed from 500 to the entire e-mails containing appropriate recommendations. Location Information chain. Benefits Membership Store Coupon Information Information Benefits By sending members coupons that suit their taste while in the From a specific area Store By ordering stock based on accurate analyses of the hottest- (500 stores) to the whole country proximity of the nearby stores, the coupon distribution company Automatically select appropriate selling products rather than relying on intuition, the stores can can improve the convenience and satisfaction of the members. Tens of TBs coupons by matching member expand sales and profits with less waste and more efficiency. Peak hours and store information Product master Create new customers for stores and to the system, and attract 1 million items per second By analyzing large volume data repeatedly, the stores can now Sales records customers during off peak seasons. provide their customers with appropriate information based on Real Time marketing intelligence and increase the number of regular customers. Case Predict Trouble and Take Proactive Action Case Vehicle On-Board Device Information Based on Locations and Times B Challenge: Combine and analyze a variety of data to detect signs of issues at an early stage and prevent them becoming serious problems E Challenge: Link large volumes of vehicle on-board device information with other information for efficient and safe driving Our Solution Our Solution Data accompanied by Complex Event Processing Customers location information Analyze text information such as past complaints and the Link large volumes of information including road conditions and Determine current conditions and responses to them, automatically extract patterns that may lead information from the vehicle on-board device, such as locations respond to the conditions in real-time to serious problems, compare them against current situations to Analyze and and times in order to predict traffic congestion from different Customer The machine is hot Predict Probe detect signs of complications, and then take the necessary Consulting Information and radiating heat. angles and analyze fuel efficiency. measures. • Monitor current Link vehicle information, latitudes, longitudes, vehicle speeds Records of Response situations Add information exchanged through SNS to analytic data to • Predict the future etc.., to information that has already analyzed including locations Sensor gain unstructured market information. • Prevent recurrence and times. This will enable traffic conditions to be determined and appropriate traveling routes will feedback to the on-board Data processing Analysis Benefits Condition devices. By adding SNS information and tweets to the analysis, the signs Processed event information is accumulated and reused when Sensor of customer issues can be detected before formal complaints are SNS Number of tweets: Facility Information 200 million/day needed. Information Facility received. Probe Location Map By quickly and accurately analyzing complaints, customer Social Media Preventive Measures Benefits External information (coordinates) Information satisfaction levels are discovered in real-time and any sign of a By predicting traffic conditions based on actual data, the drivers Analyze past information and potential issue can be detected. can now determine roads to avoid congestion, improve fuel predict the future efficiency and prevent dangerous driving. Parallel distributed processing with A higher degree of customer trust is earned along with analysis and prediction minimizing the time taken to respond. Case Analyze Access Logs for Online Sales and Discover New Value Case Use Comprehensive Health Information Effectively C Challenge: Combine analysis results of access logs with purchase history information to expand the business F Challenge: Integrate health information from various sources to help patients and healthcare insurance subscribers promote their health Our Solution Online 200 million 50,000 items Our Solution Prescription Data Checkup Data Vital Statistics shopping site items/month Unstructured (number of products) The Combination of what customers have purchased and what data must be DWH/BI Analyze health information including vital statistics for processed and Number products have been frequently viewed by web users, can provide Access extracted. of subscribers who sign up for this service. This will allow them to insight into potential growth areas. logs accesses understand their current health condition and address future large Tally the number of by age magnitude of accesses by health risks. Benefits data product and age Integrate and analyze individual and general, medical history Information held by health insurance associations Information held by employers Information held by individuals Member 20,000 By performing analysis on a combination of large volumes management DB items/month data, which was previously accessed separately, in a secure of web access logs and purchase histories, hidden hot-selling manner to predict medical benefits in the future. Membership products can be exploited and new business opportunities information Analyze, fuse, explored. and visualize Benefits As there is no need to transfer data to a processing server, New value created by Based on the results of the analysis, the health specialist can 500,000 the data can be analyzed quickly leading to a reduction in items/month fusing information now offer health guidance more objectively and promote the Integrate man-hours. subscribers’ health. Purchase Analysis of history conventional Medical expenditure is a major issue in the health industry and Parallel distributed processing purchase history Product A Product B Product C Product X with analysis and prediction Product name can be normalized by improvements to subscriber’s health.03 04

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