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Search results “Data mining oracle database” for the Апрель 2014
Oracle Data Miner 4.0/SQL Developer 4.0 Ext. - New Features
 
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Oracle Data Miner 4.0 New Features demo and presentation
Views: 10989 Charlie Berger
Efficient Algorithms for mining high utility itemsets from transactional databases
 
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Final year project based on data mining
Views: 1223 Surendar B
Data mining within Experian
 
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Bas de Jong Marcus Veen VU Data Mining course 2014 - created at http://goanimate.com/
Views: 303 Marcus Veen
Import Data and Analyze with Python
 
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Python programming language allows sophisticated data analysis and visualization. This tutorial is a basic step-by-step introduction on how to import a text file (CSV), perform simple data analysis, export the results as a text file, and generate a trend. See https://youtu.be/pQv6zMlYJ0A for updated video for Python 3.
Views: 213789 APMonitor.com
data analysis
 
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data analysis - oracle 10g , sql server 2008
Views: 226 R.N.A. Creation
Computer Applications: Integrated Applications
 
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Using Microsoft Office Suite and the Internet, Professor Yunker builds an integrated appl;ication (Word, Excel, PowerPoint) to plan a trip to a foreign city.
Views: 661 professoryunker
Pengimplementasian ETL dan OLAP pada Retail Sales (Drama)
 
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FE-BIDW 2014 Nama : Siti Rohani Ayundari 5211100062 Muhammad Nashief 5211100130 Adimas Indra 5211100131 Krishna Wacana 5211100141 Hafizh Pahlevie 5211000172 Revy Febri A 5211100119 Carissa Cindy 5211100181 Mayangsekar A 5211100189
Views: 109 rohani ayundari
Y-telecom Oracle day
 
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Oracle " Y-telecom has made new record by completing full ERP system in 10 months" Y-telecom's project manager explain the project successful story in Oracle day in Movenpick Sanaa 9/4/2014
Views: 218 leen Amar
LatLonGO®/HERE Technology Benefits
 
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LatLonGO, SAP Mobility, Technology Benefits GIS,SAP,Integration,Mobile GIS,Mobility,Android app,Windows 8 app,Utilities,Telco,Emergency Services,Truck Roll Reduction,SAP Mobility Certification,Smallworld GIS,ESRI,ArcGIS,spatialNET,Open Spatial,Oracle Spatial,ERP,DMS,OMS,CIS,Planned Outage,Unplanned Outage,ERP Work Order,Notification,Equipment,Functional Location,Operations,Dynamic Data Feeds,GeoRSS,Spatial Enterprise,ruggedized,MIL-STD-810 certified,tablet case,NetWeaver Gateway,SAP Plant Maintenance,SAP AG (Organization),SAP ERP (Software),Oracle Database (Software)
Views: 339 we-do-IT
Parsistance Java Mobile (Penyimpanan Data Barang)
 
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TugasUAS_Parsistance Java Mobile (V) Rijalludin Ahmad 1242164 Abu Bakar A H H 1242127 Novi Tri Susanti 1242152
Views: 32 rijalludin ahmad
CSCI-585 : Database System, Spatial Objects Homework demo
 
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This video is a demo of using spatial objects in oracle 11g. Given a map and a set of buildings, whose co-ordinates are fed in the spatial database, we query them by drawing polygons on the screen
Views: 521 Shrikanth Narayanan
Partner Webcast Part 2 -- Oracle Real-Time Decisions (RTD) - 03 Apr 2014
 
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ECEMEA Partner Hub http://blogs.oracle.com/imc Businesses today must have a fast, focused response when something unexpected happens, or risk losing customers and revenue. Top performers know how hard it can be to analyze information that is vast, varied, and often outside the warehouse. Knowing more about your business—and knowing it faster than others—is the best way to power innovation and gain an edge on your competition. Oracle Real-Time Decisions (RTD) combines both rules and predictive analytics to power adaptive solutions for real-time enterprise decision management. It enables real-time intelligence to be instilled into any type of business process or customer interaction while it happens. A high-performance transactional server delivers real-time decisions and recommendations. This server automatically renders decisions within a business process and reveals insights, creating actionable intelligence from data flowing through the process in real time. Part 1: Oracle Endeca Information Discovery http://youtu.be/HMvNlnN5Cp4 [Read More @ https://blogs.oracle.com/imc/entry/partner_webcast_oracle_endeca_information]
Views: 2676 Oracle IMC
Data Mining techniques 2014 - Assignment 1
 
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This short video is part of the Data Mining techniques course, showing a succesful application of machine learning and data mining. The main sections of the video were taken from the following links: http://news.discovery.com/ http://www.npr.org/blogs/krulwich/2011/06/01/114075029/flu-attack-how-a-virus-invades-your-body https://www.youtube.com/watch?v=wSmvx1JpeGY - Swine flu - N1H1 animation https://www.youtube.com/watch?v=qBfuVuelkoY- DNA instruction manual https://www.youtube.com/watch?v=w_j0VuJ-J9k - Tracking Influenza Via Twitter Thank You for attention!
Views: 53 Kristina KappaG
Relational Database Concepts
 
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This video by Chan Beauvais is part of Module 4 Data Development in the PACE-IT Data Management Certificate program.
Views: 187 CDMP Community
A Practical Implementation of PPDM's 'What is a Well?'
 
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Steve Cooper discusses best practices for E&P companies, 2013 PPDM Conference in Calgary.
Views: 1076 EnergyIQ
More Data Mining with Weka (1.6: Working with big data)
 
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More Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 6: Working with big data http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/Le602g https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 10560 WekaMOOC
02 Le Data Mart
 
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Qu'est-ce qu'un entrepôt de données, l'étape préliminaire à la création de cubes avec SQL Server Analysis Services
Views: 5341 Rudi Bruchez
11_Entropy Example part2/2
 
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کەمپینی بە کوردی کردنی زانست لە زانکۆی گەشەپێدانی مرۆیی Data Mining - Classification - Entropy
Views: 969 salim hasan
ANITA Lecture - An astronomers introduction to databases and SQL - Paul Hancock
 
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Title: An astronomers introduction to databases and SQL Speaker: Paul Hancock, Curtin University (Paul.Hancock AT Curtin.edu.au) Date: 2pm (AEST) Monday 28th April 2014 Abstract: In the era of big data, the ways in which we store and access data are changing. Despite being at the forefront of big data creation, astronomers are generally way behind on methods to store and access large data sets. The sloan digital sky survey (SDSS) was one of the first truly large data sets encountered in astronomy, and one of the first to embrace new storage and access technologies. The SDSS data are too large and complex to ship en mass, or to process on most users' computers. The solution was to serve the data via a web interface that would allow users to access and download only the subset of data that is relevant to their study. To get the most out of the SDSS data, without incurring large download costs, a user must be proficient in the language of databases -- SQL. As more and more surveys and simulations store their data in databases, astronomers will need to become more familiar with the language of databases in order to make best use of both their data and time. In this talk I will introduce the concept of a database, motivate your need for database technology both on the large and small scale, and give an introduction to SQL. Additional Material: Talk slides are available for download at http://goo.gl/nLEBRW.
Views: Anita Chapter
01 Introduction au décisionnel SQL server
 
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Une présentation des différentes briques de la suite décisionnelle de SQL Server
Views: 1628 Rudi Bruchez
SnowFlake Schema
 
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Walter Carrere
Views: 340 Mineria de Datos
etl testing online training |  online etl testing training in usa,uk,canada
 
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http://hyderabadsys.com/etl-testing-online-training/ Hyderabadsys ETL testing online training online training completely unique & genuine training institution. so we give any one student to software cource 100% genine .Hyderbadsys Data stage online training completely ETL testing online training is that the method for extracting, remodeling and loading great deal of knowledge from one information to a different. ETL testing online training unit varied ways in which of doing it like committal to writing your own processes to the a lot of usually used manner of implementing ETL tools CONTACT US INDIA +91 9030400777 USA +1-347-606-2716 Email: [email protected]
Views: 60 Maik Holzman
The Business Doctor - Database Segmentation
 
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Jeff Miles, The Business Doctor, is a professional business coach based in Perth WA and Sydney NSW. Jeff is known for his results! Just ask his clients. With 30 years of high-level experience in management, profitability, operations, mergers, acquisitions, marketing and business planning, he can find the solutions your business needs. Jeff trains business owners how to stay focused and achieve their goals by giving them essential skills. He will help you to build a clear vision for the future, develop invaluable networking skills, master time management and reduce stress, improve operations and communications, and get the business you've always wanted. In addition to addressing business issues and systems, Jeff takes into account your personal desires, needs and goals. This leads to professional growth and development that gives you the tools to make better and more informed decisions. Jeff Miles: www.thebusinessdoctor.com.au View my client testimonials: www.thebusinessdoctor.com.au/testimonial­s Events Page: www.thebusinessdoctor.com.au/event Perth Mechanic Coach: www.mechaniccoach.com.au Like me on Facebook: www.facebook.com/BizDoctorJeffMiles Follow me on Twitter: www.twitter.com/JeffMilesTBD For business inquiries: [email protected]
Views: 214 Jeff Miles
The Processes of ETL and OLAP in Datawarehouse
 
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Sebuah analogi ETL dan OLAP yang digambarkan melalui permasalahan dalam kehidupan sehari-hari, yaitu dalam bisnis. Semoga memberikan pemahaman yang jelas terkait ETL dan OLAP. Presented by Yusuf Kurnia R. Muh. Idil Haq Amir Emilia Yulisita Devita Swatadani Yoshita
software Retail Minimarket/Toko
 
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software Retail Minimarket/Toko mempunyai fitur : 1.1 Login 1.2 Halaman Utama 6 1.3 Daftar Login Aplikasi (Home -- Daftar Login Aplikasi) 7 1.4 Customer (Master - Customer) 8 1.5 Suplier (Data Master - Suplier) 10 1.6 Kelompok (Data Master -- produk - kelompok) 12 1.7 Kelompok (Data Master -- produk - kelompok) 13 1.8 Merk (Data Master -- produk - merk) 15 1.9 Item List (Data Master -- produk - Item List ) 16 1.10 Cabang (Data Master -- Cabang) 19 1.11 Gudang (Data Master -- Gudang) 21 1.12 Rak (Data Master -- Rak) 22 1.13 Cureency (Data Master -- Cureency) 24 1.14 Jasa Pengiriman (Data Master -- Jasa Pengiriman) 25 1.15 jasa (Data Master --data servis - jasa) 27 1.16 Teknisi (Data Master --data servis - Teknisi) 28 1.17 Default Cabang (system setting-- Default Cabang) 30 1.18 Default Gudang (system setting-- Default Gudang) 31 1.19 Default Kassa (system setting-- Default Kassa) 32 1.20 Metode inventory (system setting-- Default Inventory) 33 1.21 PPN penjualan (system setting-- PPN penjualan) 34 1.22 Stok awal (Transaksi -- warehouse -- stok awal) 35 1.23 Stok awal (Transaksi -- warehouse -- stok awal) 36 1.24 Penambahan stok (Transaksi -- warehouse -- koreksi stok gudang -- tamabah stok) 38 1.25 Pengurangan stok (Transaksi -- warehouse -- koreksi stok gudang -- Kurang stok) 39 1.26 Transfer gudang (Transaksi -- warehouse --Transfer Gudang) 40 1.27 Pengiman surat jalan (Transaksi -- warehouse -- Pengiman surat jalan) 41 1.28 Purchase Order(Transaksi -- Pembelian--Purchase Order) 42 1.29 Penerimaan Barang(Transaksi -- Pembelian-- Penerimaan Barang) 44 1.30 Retur Barang(Transaksi -- Pembelian-- Retur Barang) 45 1.31 Data Stok Store(Transaksi -- Store-- Data Stok Store) 46 1.32 Faktur Penjualan(Transaksi -- Store-- Faktur Penjualan) 47 1.33 Cashier(Transaksi -- Store-- Cashier) 48 1.34 Retur Penjualan(Transaksi -- Store-- Retur Penjualan) 53 1.35 Penerimaan Piutang(Transaksi -- Store-- Penerimaan Piutang) 54 1.36 Order Servis(Transaksi -- Servis-- Order Servis) 55 1.37 Servis Keluar(Transaksi -- Servis Keluar) 56 1.38 Surat Jalan(Transaksi -- Surat Jalan) 57 1.39 Chart Of Account(General Ledger -- Chart Of Account) 58 1.40 Jurnal(General Ledger -- Jurnal) 59 1.41 Pengeluaran Kas(General Ledger -- kas dan bank - Pengeluaran Kas) 60 1.42 Pemasukan Kas(General Ledger -- kas dan bank - pemasukan Kas) 61 1.43 Posting(General Ledger -- Posting) 62 1.44 Buku Besar (General Ledger -- Buku Besar) 63 1.45 Neraca Saldo (General Ledger -- Neraca Saldo) 64 1.46 Laporan Keuangan (General Ledger -- Laporan Keuangan) 66 1.47 Penutupan Periode(General Ledger -- Penutupan Periode) 67 Untuk Pemesanan Software Bisa Kontak Kami : Name : Yohanes Santoso Alamat : Villa Ciomas Indah Blok H/3 No.6 -Bogor Email : [email protected] HP : 085773685687/081318079249 PIN BB : 300A3E54 WEBSITE : www.johansoft.com
Views: 147 Johansoft medialine
BI: Shopping basket analysis
 
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BI: Shopping basket analysis
Views: 1603 IntroToIS BYU
Choosing Text Enrichment Options in Endeca Integrator ETL
 
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Oracle Endeca Information Discovery Integrator ETL 3.1 provides several options for enhancing unstructured text data. This video reviews the available options and provides recommendations about using each.
Views: 2141 OracleEID
LatLonGO®/HERE Redlining
 
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LatLonGO, SAP Mobility, Redlining,GIS,SAP,Integration,Mobile GIS,Mobility,Android app,Windows 8 app,Utilities,Telco,Emergency Services,Truck Roll Reduction,SAP Mobility Certification,Smallworld GIS,ESRI,ArcGIS,spatialNET,Open Spatial,Oracle Spatial,ERP,DMS,OMS,CIS,Planned Outage,Unplanned Outage,ERP Work Order,Notification,Equipment,Functional Location,Operations,Dynamic Data Feeds,GeoRSS,Spatial Enterprise,ruggedized,MIL-STD-810 certified,tablet case,NetWeaver Gateway,SAP Plant Maintenance,SAP ERP (Software),Android (Software),SAP AG (Organization)
Views: 548 we-do-IT
How to Demo: Read Real-Time Data from Social Media using DataSift
 
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See how PowerExchange for DataSift Can help you extract real-time social data from Social Media. Use PowerExchange for DataSift to read the Twitter data from the stream into a DataSift data object through the Data Integration Service. You can load the extracted data to a target and then use the data for data mining and analysis. Vist the Informatica Marketplace to see the latest Data Integration add-ons, connectors, templates, mappings and apps: http://marketplace.informatica.com/ Connect with us on Facebook: https://www.facebook.com/informaticamarketplace Follow us on Twitter: https://twitter.com/infamarketplace
Views: 1146 InfaMarketplace
Data Awareness & DBA Best Practices - Part 2
 
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Data Awareness & DBA Best practices program to Degree and Diploma students at Stamford College in Malaysia.
Views: 12 Your SQL MAN
Oracle Forms - Five Pillars of Performance
 
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Oracle Forms is here to stay. Love them, hate them or evolve them -- Forms applications are key to your business. As more and more companies upgrade to 11g, they are faced with the additional challenge of improving system performance and stability of their Forms systems. This webinar will help you learn how you can: •Maximize both actual and perceived performance •Identify bottlenecks •Optimize server resource requirements •Minimize network round trips •Quickly identify and resolve performance issues
Views: 205 Correlsense
Accelerating Insights into Action: Better Decisions from Big Data
 
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This forum featured Paul Sonderegger, former Forrester analyst and Big Data strategist from Oracle, and real-world practitioners, Mike Burkes and Rick Detwiler from Toyota Motor Sales, USA, in a discussion about how to make big data pay off by augmenting traditional structured data and relational methods to explore, experiment and innovate with new data, tools and techniques. Tim Stanley of Center for Digital Transformation moderated.
Managing Large Datasets with Python and HDF5 - O'Reilly Webcast
 
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Are you using Python to process large numerical datasets? Over the past few years, the Hierarchical Data Format (HDF5) has emerged as the mechanism of choice for processing, archiving and sharing scientific datasets ranging from gigabytes to terabytes and beyond. With a diverse user base spanning the range from NASA to the financial industry, HDF5 lets you create high-performance, portable, self-describing containers for your data. HDF5's flexibility and speed make it particularly well-suited to analysis in Python. This webcast provides a practical, Python-based introduction to the world of HDF5. This webcast led by Andrew Collette will cover: - The basics of the format - Performance - Best practices for making sharable data files which can be read by colleagues on other platforms About Andrew Collette Andrew Collette holds a Ph.D. in physics from UCLA, and works as a laboratory research scientist at the University of Colorado. He has worked with the Python-NumPy-HDF5 stack at two multimillion-dollar research facilities; the first being the Large Plasma Device at UCLA (entirely standardized on HDF5), and the second being the hypervelocity dust accelerator at the Colorado Center for Lunar Dust and Atmospheric Studies, University of Colorado at Boulder. Additionally, Dr. Collette is a leading developer of the HDF5 for Python (h5py) project. Produced by: Yasmina Greco - Don't miss an upload! Subscribe! http://goo.gl/szEauh - Stay Connected to O'Reilly Media. Visit http://oreillymedia.com Sign up to one of our newsletters - http://goo.gl/YZSWbO Follow O'Reilly Media: http://plus.google.com/+oreillymedia https://www.facebook.com/OReilly https://twitter.com/OReillyMedia
Views: 19597 O'Reilly
Market Basket Analysis Demo
 
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Convenience stores are more profitable if they have the resources to complete market basket analysis. Watch this 3 minute video on how easy it is with the right tool.
Views: 816 BusinessImpactInc
student analytics
 
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-- Created using PowToon -- Free sign up at http://www.powtoon.com/ . Make your own animated videos and animated presentations for free. PowToon is a free tool that allows you to develop cool animated clips and animated presentations for your website, office meeting, sales pitch, nonprofit fundraiser, product launch, video resume, or anything else you could use an animated explainer video. PowToon's animation templates help you create animated presentations and animated explainer videos from scratch. Anyone can produce awesome animations quickly with PowToon, without the cost or hassle other professional animation services require.
Views: 27 Rohan Pandhram
Building Mini Data Warehouse - Creating Cube Final Step #6
 
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1. Create and Design Cube. 2. Deploy and Execute Cube. 3. Verify Cube. http://www.maheshbhagat.tk http://www.fb.com/mymahesh11 https://twitter.com/mymahesh11
Views: 2825 Mahesh Bhagat
Instalacion de instancia SQL
 
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instalación de una nueva instancia, configuración de alias, puertos, y encriptacion de base de datos y autenticacion a través del directorio activo en windows server 2008. elaborado por estudiantes de la Carrera de Licenciatura en Computación de la Universidad Gerardo Barrios
PERFORMANCE AND COST EVALUATION OF AN ADAPTIVE ENCRYPTION ARCHITECTURE FOR CLOUD DATABASE SERVICES
 
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Gagner Technologies offers M.E Projects based on IEEE 2013. Final Year Projects, M.E Projects 2014-2015, mini Projects 2014-2015, Real Time Projects, Final Year Projects for BE ECE, CSE, IT, MCA, B TECH, ME, M SC (IT), BCA, BSC CSE, IT IEEE 2014 Projects in Data Mining, Distributed System, Mobile Computing, Networks, Networking. IEEE 2014 - 2015 Projects. Final Year Projects at Chennai, IEEE Software Projects, Engineering Projects, MCA Projects, BE Projects, JAVA Projects, J2EE Projects, .NET Projects, Students Projects, Final Year Student Projects, IEEE Projects 2014-2015, Real Time Projects, Final Year Projects for BE ECE, CSE, IT, MCA, B TECH, ME, M SC (IT), BCA, BSC CSE, IT, software Engineering For more details Contact: Gagner Technologies, No: 1, South Dhandapani Street (Opp to T.Nagar bus depot), T.Nagar, Ch=17. Contact: 8680939422, 044 24320908. 9962221452 Mail Id: [email protected]
Views: 180 Gagner Technologies
Yves Hilpisch - Eurex Tutorial - Interactive Financial Analytics
 
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PyData London 2014 - View Yves' slides here: http://www.hilpisch.com/YH_PyData_Eurex_Tutorial.html Today's financial market environment demands for ever shorter times-to-insight when it comes to financial analytics tasks. For the analysis of financial times series or for typical tasks related to derivatives analytics and trading, Python has developed to the ideal technology platform. Not only that Python provides powerful and efficient libraries for data analytics, such as NumPy or pandas. With IPython there is a tool and environment available that facilitates interactive, and even real-time, financial analytics tremendously. The tutorial introduces into IPython and shows, mainly on the basis of practical examples related to the VSTOXX volatility index, how Python and IPython might re-define interactive financial analytics. Quants, traders, financial engineers, analysts, financial researchers, model validators and the like all benefit from the tutorial and the new technologies provided by the Python ecosystem. BACKGROUND For background information see the Python-based "VSTOXX Advanced Services" and the related backtesting applications: http://www.eurexchange.com/vstoxx/ http://www.eurexchange.com/vstoxx/app1/ http://www.eurexchange.com/vstoxx/app2/
Views: 2229 PyData
Overview of Toad Data Point
 
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http://www.DellSoftware.com/Business-Intelligence-Suite Learn how to simplify data analysis with Toad Data Point, part of Dell Software's Toad Business Intelligence Suite.
Views: 758 Dell EMC Support
기존 데이터웨어하우스를 새로운 빅데이터 스트림으로 확장하는 베스트 프랙티스
 
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Session Ⅱ : 기존 데이터웨어하우스를 새로운 빅데이터 스트림으로 확장하는 베스트 프랙티스 과거 대부분 기업들은 통상적으로 트랜잭션데이터와 BI(비즈니스 인텔리전스)의 분석을 통해서만 비즈니스의 통찰을 얻을 수 있었습니다. 하지만 빅데이터 시대에 접어들면서, 기업들은 소셜, 모바일, 센서데이터와 같은 새로운 정보 스트림을 활용하게 되었으며 이를 통해 좀 더 완전한 비즈니스 통찰이 가능케 되었습니다. 빅데이터 시대에 우리는 어떠한 준비를 해야 할까요? 지금 오라클 웨비나 데이를 사전 등록하세요! 기존 데이터 웨어하우스를 빅데이터에 연결시켜주는 차세대 오라클 데이터통합 방법을 공유하려고 합니다. 간단한 사전등록으로 편안하게 시청하세요.
Views: 513 TalkIT
SECOND MAX SALARY SQL INTERVIEW QUESTION
 
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SECOND MAX SALARY SQL INTERVIEW QUESTION A Job Portal http://www.InterviewDot.com http://www.InterviewDot.com http://www.InterviewDot.com One Click Dream Job - http://www.interviewdot.com/upload-resume/uploadresume.htm Are you looking for a new Job ? InterviewDot.com - A Job Portal http://www.InterviewDot.com http://www.InterviewDot.com http://www.InterviewDot.com One Click Dream Job - http://www.interviewdot.com/upload-resume/uploadresume.htm JAVA/SPRING/SQL/JUNIT INTERVIEW QUESTION AND ANSWER SECOND MAX SALARY SQL INTERVIEW QUESTION
Views: 78 Interview DOT
P 8 STAGING TABLE
 
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CREDITS :PAWAN VISHWAKARMA building a staging area
Views: 31 Dheemant Palan