Data Warehouse that Accelerates Information Utilization with its High-speed Information Aggregation

Transcription

1 Data Warehouse that Accelerates Information Utilization with its High-speed Information Aggregation FUJITSU Software Symfoware Analytics Server New Product Enables discovery of new trends/changes thanks to detailed analysis achieved by reducing the processing time required for aggregation to 1/500, making it possible to perform 500 times more analyses. Reduces time required for installation and time required for analysis data preparation by 1/3 and 1/6, respectively, thanks to its integrated data collaboration, processing, storage, and extraction functions. PostgreSQL interface that can link with hundreds of other tools and packages allows customers to use their familiar BI tools as they are. More detailed analysis made possible by this data warehouse will improve the accuracy of your analysis, which will allow you to notice trends and changes that you could not before and accurately assess the situation and respond appropriately. For example, when performing sales analysis with POS data, you can have sales figures by the hour or minute, instead of by the day, for each item and store, enabling you to optimize the product lineup and number of items to be ordered, and consequently leading to an increased sales. Data source RDB CSV Functions required for information utilization are integrated Reduces time for analysis system installation by 1/3* Link Symfoware Analytics Server Process Store Extract Analysis task Supports hundreds of tools, including: - SAP BusinessObjects - Pentaho BI Suite -Tableau - Oracle Business Intelligence - GUI operation allows non-db engineers to process data - Analysis data is ready by simply using a combination of templates 店 Store 舗 process 商 品 Date 日 付 数 Qty 量 ID ID 2014/5/ /5/ /5/ /5/ /5/ Easier preparation of analysis data : : : : Sales data Database extraction By area Sales Improved analysis accuracy Notice trends/changes that you were not aware of Drill down is possible By store Kamata Shiodome Templates Store master Database extraction Compilation CSV storage Kanagawa Tokyo Yokohama By the hour Drill down as needed... Create table Permission Extraction Listing Process Store * Results obtained by Fujitsu

2 Real-time Business Management Efficient and advanced analysis and more accurate predictions in-house practice Decision making for improved performance through real-time analysis/forecast based on massive information inside and outside the company Problem Information Infrastructure Inventory Management Sales Forecast Need to use scattered internal information in a timely manner Need to grasp the status of sales /slow-moving inventory even faster. Daily reporting is too late. Need to take the next measure while predicting the results instead of analyzing sales after completing sales promotion Solution Collect/analyze information across systems /operations in real time Report slow-moving inventory in stores in real time Enable correction of strategies in the middle of sales promotion through accurate sales forecast Effect Faster information analysis, and sophisticated analysis approach Reduced warehousing costs/lost sales opportunities, efficiency in appropriate responses (price reductions, transfer of goods between stores, etc.) Efficient sales promotion, and improved sales Analysis Details Outputs store/merchandise/single-item-level reports immediately, and also enables atypical analysis Predicts success/failure of a sales campaign based on information obtained during the several days following its launch and quickly analyzes the factors. A Real-time information analysis/improved accuracy in sales forecasts Management information visualization template B Building of an advanced prediction/analysis model Internal data In-memory External data CRM Project Inventory ERP applications Marketing Sales C Economic indicators SNS data Real-time collection/unification of information data Fujitsu s Services/Technologies Supporting the Offering A Management information analysis Template by industry/task (Dashboard) B Statistics analysis technology In-memory forecast analysis library Data mining technology C Real-time analysis platform High-speed DWH platform (in-memory/column DBs) Real-time ETL

3 SPATIOWL: A Platform for Behavior Analysis and Mobility Optimization FUJITSU Intelligent Society Solution SPATIOWL Detects and issues alerts for unusual behavior based on real-time behavior analysis of moving objects. Recommends a suitable means of transportation based on analysis and prediction of transportation-related information. SPATIOWL collects and analyzes location, image and audio information on real-time moving objects, such as pedestrians and vehicles, to identify unusual behavior and conditions. SPATIOWL provides people with optimized transportation-related services and care services. Patent Pending Next-Generation On-Demand Mobility Service Elderly Care Service User wants to arrive at the destination by 9:00 am Image Sound Prioritize fastest journey time! Depart 8:40 am (840 yen) Prioritize balance between journey time and travel expenses! Depart 8:30 am (400 yen) Prioritize lowest travel expenses! Depart 8:10 am (220 yen) SPATIOWL Taxi Mode Dispatch SPATIOWL Reservation Dispatch Shared Taxi Mode Scheduled Mini Bus Mode The service can be used by selecting the preferred vehicle from the available options Dispatch Nurse Call Healthcare Check through Electronic Medical Record Homecare Nursing for the Elderly Sensing for Monitoring the Elderly When Sensing detects potential or actual dangerous behavior by elderly persons, it informs the nurse, staff and family at an appropriate time. It enables accurate detection of unusual behavior (e.g. falling, crouching or wandering) by optimizing recognition logic and learning data. Next-Generation On-Demand Mobility Service: Predicts transportation demand and recommends a suitable means of transportation based on user needs. Elderly Care Service: Detects unusual and dangerous behavior with behavior analysis technology that utilizes image data and environmental sounds (e.g. the sound of someone falling out of bed). * Sections in this document marked Patent Pending relate to technologies for which a patent application has been submitted.

4 Real-time Plant Energy Management in-house practice Not only minimizes energy costs, but also enables automatic control based on predicting and forecasting. Maximizes production and improves product quality, yields, safety and health. Fujitsu s solution achieves environmentally friendly and optimal plant and improves external assessment regarding CSR by gathering real-time data on energy consumption inside a plant and by analyzing the data in combination with various pieces of information. Challenge Plant Need to streamline the use of plant resources, including personnel, materials, money and energy Production Need to reduce energy costs and improve production efficiency as well as product quality Safety and health Need to create a safe and healthy plant environment Purchasing Need to consider costs, reliability of supply and environmental performance in purchasing Solution Analysis and automatic control for improving production efficiency while minimizing energy costs; and optimizing plant through the visualization of indicators (quality, costs, delivery time, safety and environmental performance) Effects Minimizing energy costs and automatic control based on predicting and forecasting Significant increase in productivity and improvement in product quality and yields Improved safety and health as well as enhanced assessment regarding CSR Optimal plant analysis performed by using all information Analysis available in a plant Action analysis for optimal plant by gathering together all plant information (production, quality, cost, number of workers, facilities, energy, etc.) Optimization of energy supply and demand Environmental dashboard Energy demand prediction technology Micro-grid technology (Solar power generation, storage batteries and electricity deregulation) Simultaneous display of the field, products and data Facility maintenance service AR integration platform technology Visualization and optimization of plant resources Plant dashboard Significant increase in productivity MES (manufacturing execution system) Production Operation monitoring service Failure prediction technology Installation of a flexible sensor network M2M service Sensing network service

5 Improved Equipment Maintenance by Forecasting Breakdowns Demonstration Only in-house practice Using media data and sensing data for advanced production equipment maintenance Predicts equipment failure based on various data, including image/audio data and sensing data Reduces maintenance costs and improves the operating rate of systems by performing maintenance at the optimal time Equipment Maintenance Plant Operation Production Management Problem Need to reduce maintenance costs by raising the productivity level of equipment maintenance operations performed by workers who relied on their instincts and experience Need to avoid reduction in productivity due to unexpected system shutdown Need to reduce the burden of reviewing production plans due to production line shutdowns Solution Perform maintenance at the optimal time before equipment failure occurs Keep operating systems up to the optimal time for maintenance on the maintenance plan Develop detailed production plans considering the maintenance plan Effect Optimized maintenance costs as a result of reducing the frequency of maintenance Improved product quality and the system operating rate due to reduced incident rates Reduced lost sales opportunities /excess inventory, revised production plans and increased productivity A Installation of flexible wireless sensor network Analysis Details Accurate failure prediction by using sensing data/media data Detects changes in the status of and errors in equipment/systems from pictures, audio, and other media data and sensing data Accurately detects the time of equipment/system failure by using failure prediction technology. B Use of analogue information (appearance /noise) for failure prediction C Building of an advanced failure prediction model A Wireless network technology Sensing network service Fujitsu s Services and Technologies Supporting the Offering B Image/audio/text analysis technology Media data analysis technology acoustic analysis technology text mining technology C Failure prediction/symptom detection technology Failure symptom detection technology Failure prediction technology

6 The Innovation in the Field with Operational Analytics Demonstration Only Fujitsu technology enables required actions to be identified in the event of plant equipment abnormalities by exploiting various types of external data (e.g. equipment status and workers written records). Plant equipment abnormalities and required actions are displayed in real time to the worker in the field through HMDs (Head Mounted Displays). Image/Audio/Text Analysis wearable device Noise, vibration External data Weather, manufacturer Real-time Analysis Audio data Comments Technical know-how Wireless Sensor Network BigData Picture images Operator s movements Senior operator Operator s condition Operator s posture, movement Big Data Analysis Breakdown Forecasting/ Prediction Statistical analysis Water quality Unusual conditions Instruction manual Productivity Hazardous areas Optimized Pharmaceutical agent Maintenance proposed Junior operator Technical traditions Improvement measures Emergency response, potential accident map Fujitsu will introduce a paradigm of various Big Data which is collected from the field. In addition to Fujitsu will bring together how to use Big Data concept on substantial data which accumulated by new strategies, such as on wearable device.

7 Monitoring Failure Signs Using Acoustic and Vibration Diagnostic AnimoWaveBase: acoustic/vibration analysis/diagnosis solutions New Product Detecting signs of failure through continuous monitoring of acoustic and vibration data for improving the level of preventive maintenance. Reducing costs and optimizing operation rates of facilities by optimizing the timing that maintenance is carried out. Providing a total solution ranging from the selection of sensors to the implementation of new analytical functions on our customers' systems. Enhancing the possibilities of preventive maintenance using acoustic and vibration data obtained from sensors. 1 Optimal selection/placement of sensors on maintenance targets 3 Analysis, visualization and diagnosis Engines, etc. Manufacturing lines/equipment 2 Data collection - Eliminating unnecessary components according to each target and environment - Detecting the most descriptive features using signal processing - Extracting events related to signs of failure and enabling their visualization Maintenance target Location Acoustic/vibration parameters to be monitored Construction machinery and others Railways, automobiles Manufacturing line in general Moving and rotational parts - Engines, motors, V-belts Pumps - Pistons, turbines, rotors Rolling parts - Bearings, shafts, belts Revving sound characteristics -Spectral features Noise features - Rotating speed, period, spacing Smelting Chemical plants, power plants, etc. Pressing machines Electrostatic precipitators (EP) Characteristics of impact sounds - Power, attenuation, frequency characteristics Plants in general Pipelines - Leakage in gas, liquid and other pipe systems Characteristics of sound in fluids - Power, frequency characteristics Bridges and other structures Plants/piping facilities Structures: bridges, tunnels, roads Concrete structures Characteristics of hammering sounds - Power, attenuation, frequency characteristics Selecting and recommending devices Sensors (vibration sensor or microphone, sensitivity, frequency characteristics, operating temperature, watertightness, explosionproofness) M2M unit (amplifier, AD converter, transmission unit, etc.) AnimoWaveBase Solutions, Supporting the Evolution of Preventive Maintenance Designing an optimized analysis/decision method Acoustic/vibration analysis technologies employing our vast signal processing experience Selecting the best combination of acoustic and vibration analysis according to the target Implementing into current systems and services A wealth of implementation experience (middleware/cloud) Flexible acoustic/vibration diagnosis solutions according to existing systems/services Animo Limited is the first venture company founded by Fujitsu Limited. Animo develops and provides multimedia software, services and solutions with "Sound and Voice" as core technologies. If you need further information, please contact address below. sales@animo.co.jp

8 M2M Solution for Collection and Utilization of Sensing Data FUJITSU Managed Infrastructure Service FENICS Ⅱ M2M Service New Product Demonstration Only in-house practice Enables prediction of facility failures as well as maintenance through the use of sensing data collected via M2M. Enables easy and secure construction of a dedicated M2M network using the FENICS Ⅱ M2M-GW, a telecommunications device originally developed by Fujitsu. Fujitsu offers services for collecting and utilizing information from devices scattered in remote places. Total M2M services are available, including telecommunications devices, networks and an M2M service platform (cloud). A variety of M2M service platform features are available, including the central of telecommunications devices and application linkage. Telecommunications device FENICS Ⅱ M2M service Telecommunications device Existing broadband (SSL-VPN) Access authentication Telecommunications device Data accumulation BI tool Big data analysis service Maintenance service Devices targeted for (inside LAN) Mobile network API M2M service platform (Fujitsu data center) Customers applications Business applications Features of FENICS Ⅱ M2MーGW Diverse network connections are available, including connections to mobile devices, broadband and end-users existing networks (optional adaptors are required for mobile connections). Solves address issues and security issues that present difficulties in enabling a variety of different network connections. Patent pending No need for individual development (we are also planning to offer support for add-on development). The FENICS II M2M service enables the central of M2M-GW. Ethernet 2 ports; RS232C 1 port Size: 141 mm (W) 77 mm (D) 30 mm (H) * Products marked with Patent pending in this document include technologies for which patent applications have been filed.