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• Big Data – Is Big Data Relevant to me? – Big Data Questionnaires – Guest Post by Vinod Kumar

  - by Pinal Dave

  This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions of SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. I think the series from Pinal is a good one for anyone planning to start on Big Data journey from the basics. In my daily customer interactions this buzz of “Big Data” always comes up, I react generally saying – “Sir, do you really have a ‘Big Data’ problem or do you have a big Data problem?” Generally, there is a silence in the air when I ask this question. Data is everywhere in organizations – be it big data, small data, all data and for few it is bad data which is same as no data :). Wow, don’t discount me as someone who opposes “Big Data”, I am a big supporter as much as I am a critic of the abuse of this term by the people. In this post, I wanted to let my mind flow so that you can also think in the direction I want you to see these concepts. In any case, this is not an exhaustive dump of what is in my mind – but you will surely get the drift how I am going to question Big Data terms from customers!!! Is Big Data Relevant to me? Many of my customers talk to me like blank whiteboard with no idea – “why Big Data”. They want to jump into the bandwagon of technology and they want to decipher insights from their unexplored data a.k.a. unstructured data with structured data. So what are these industry scenario’s that come to mind? Here are some of them: Financials Fraud detection: Banks and Credit cards are monitoring your spending habits on real-time basis. Customer Segmentation: applies in every industry from Banking to Retail to Aviation to Utility and others where they deal with end customer who consume their products and services. Customer Sentiment Analysis: Responding to negative brand perception on social or amplify the positive perception. Sales and Marketing Campaign: Understand the impact and get closer to customer delight. Call Center Analysis: attempt to take unstructured voice recordings and analyze them for content and sentiment. Medical Reduce Re-admissions: How to build a proactive follow-up engagements with patients. Patient Monitoring: How to track Inpatient, Out-Patient, Emergency Visits, Intensive Care Units etc. Preventive Care: Disease identification and Risk stratification is a very crucial business function for medical. Claims fraud detection: There is no precise dollars that one can put here, but this is a big thing for the medical field. Retail Customer Sentiment Analysis, Customer Care Centers, Campaign Management. Supply Chain Analysis: Every sensors and RFID data can be tracked for warehouse space optimization. Location based marketing: Based on where a check-in happens retail stores can be optimize their marketing. Telecom Price optimization and Plans, Finding Customer churn, Customer loyalty programs Call Detail Record (CDR) Analysis, Network optimizations, User Location analysis Customer Behavior Analysis Insurance Fraud Detection & Analysis, Pricing based on customer Sentiment Analysis, Loyalty Management Agents Analysis, Customer Value Management This list can go on to other areas like Utility, Manufacturing, Travel, ITES etc. So as you can see, there are obviously interesting use cases for each of these industry verticals. These are just representative list. Where to start? A lot of times I try to quiz customers on a number of dimensions before starting a Big Data conversation. Are you getting the data you need the way you want it and in a timely manner? Can you get in and analyze the data you need? How quickly is IT to respond to your BI Requests? How easily can you get at the data that you need to run your business/department/project? How are you currently measuring your business? Can you get the data you need to react WITHIN THE QUARTER to impact behaviors to meet your numbers or is it always “rear-view mirror?” How are you measuring: The Brand Customer Sentiment Your Competition Your Pricing Your performance Supply Chain Efficiencies Predictive product / service positioning What are your key challenges of driving collaboration across your global business?  What the challenges in innovation? What challenges are you facing in getting more information out of your data? Note: Garbage-in is Garbage-out. Hold good for all reporting / analytics requirements Big Data POCs? A number of customers get into the realm of setting a small team to work on Big Data – well it is a great start from an understanding point of view, but I tend to ask a number of other questions to such customers. Some of these common questions are: To what degree is your advanced analytics (natural language processing, sentiment analysis, predictive analytics and classification) paired with your Big Data’s efforts? Do you have dedicated resources exploring the possibilities of advanced analytics in Big Data for your business line? Do you plan to employ machine learning technology while doing Advanced Analytics? How is Social Media being monitored in your organization? What is your ability to scale in terms of storage and processing power? Do you have a system in place to sort incoming data in near real time by potential value, data quality, and use frequency? Do you use event-driven architecture to manage incoming data? Do you have specialized data services that can accommodate different formats, security, and the management requirements of multiple data sources? Is your organization currently using or considering in-memory analytics? To what degree are you able to correlate data from your Big Data infrastructure with that from your enterprise data warehouse? Have you extended the role of Data Stewards to include ownership of big data components? Do you prioritize data quality based on the source system (that is Facebook/Twitter data has lower quality thresholds than radio frequency identification (RFID) for a tracking system)? Do your retention policies consider the different legal responsibilities for storing Big Data for a specific amount of time? Do Data Scientists work in close collaboration with Data Stewards to ensure data quality? How is access to attributes of Big Data being given out in the organization? Are roles related to Big Data (Advanced Analyst, Data Scientist) clearly defined? How involved is risk management in the Big Data governance process? Is there a set of documented policies regarding Big Data governance? Is there an enforcement mechanism or approach to ensure that policies are followed? Who is the key sponsor for your Big Data governance program? (The CIO is best) Do you have defined policies surrounding the use of social media data for potential employees and customers, as well as the use of customer Geo-location data? How accessible are complex analytic routines to your user base? What is the level of involvement with outside vendors and third parties in regard to the planning and execution of Big Data projects? What programming technologies are utilized by your data warehouse/BI staff when working with Big Data? These are some of the important questions I ask each customer who is actively evaluating Big Data trends for their organizations. These questions give you a sense of direction where to start, what to use, how to secure, how to analyze and more. Sign off Any Big data is analysis is incomplete without a compelling story. The best way to understand this is to watch Hans Rosling – Gapminder (2:17 to 6:06) videos about the third world myths. Don’t get overwhelmed with the Big Data buzz word, the destination to what your data speaks is important. In this blog post, we did not particularly look at any Big Data technologies. This is a set of questionnaire one needs to keep in mind as they embark their journey of Big Data. I did write some of the basics in my blog: Big Data – Big Hype yet Big Opportunity. Do let me know if these questions make sense?  Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Big Data – Basics of Big Data Architecture – Day 4 of 21

  - by Pinal Dave

  In yesterday’s blog post we understood how Big Data evolution happened. Today we will understand basics of the Big Data Architecture. Big Data Cycle Just like every other database related applications, bit data project have its development cycle. Though three Vs (link) for sure plays an important role in deciding the architecture of the Big Data projects. Just like every other project Big Data project also goes to similar phases of the data capturing, transforming, integrating, analyzing and building actionable reporting on the top of  the data. While the process looks almost same but due to the nature of the data the architecture is often totally different. Here are few of the question which everyone should ask before going ahead with Big Data architecture. Questions to Ask How big is your total database? What is your requirement of the reporting in terms of time – real time, semi real time or at frequent interval? How important is the data availability and what is the plan for disaster recovery? What are the plans for network and physical security of the data? What platform will be the driving force behind data and what are different service level agreements for the infrastructure? This are just basic questions but based on your application and business need you should come up with the custom list of the question to ask. As I mentioned earlier this question may look quite simple but the answer will not be simple. When we are talking about Big Data implementation there are many other important aspects which we have to consider when we decide to go for the architecture. Building Blocks of Big Data Architecture It is absolutely impossible to discuss and nail down the most optimal architecture for any Big Data Solution in a single blog post, however, we can discuss the basic building blocks of big data architecture. Here is the image which I have built to explain how the building blocks of the Big Data architecture works. Above image gives good overview of how in Big Data Architecture various components are associated with each other. In Big Data various different data sources are part of the architecture hence extract, transform and integration are one of the most essential layers of the architecture. Most of the data is stored in relational as well as non relational data marts and data warehousing solutions. As per the business need various data are processed as well converted to proper reports and visualizations for end users. Just like software the hardware is almost the most important part of the Big Data Architecture. In the big data architecture hardware infrastructure is extremely important and failure over instances as well as redundant physical infrastructure is usually implemented. NoSQL in Data Management NoSQL is a very famous buzz word and it really means Not Relational SQL or Not Only SQL. This is because in Big Data Architecture the data is in any format. It can be unstructured, relational or in any other format or from any other data source. To bring all the data together relational technology is not enough, hence new tools, architecture and other algorithms are invented which takes care of all the kind of data. This is collectively called NoSQL. Tomorrow Next four days we will answer the Buzz Words – Hadoop. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• How-to configure Spring Social via XML

  - by Matthias Steiner

  I spend a few hours trying to get Twitter integration to work with Spring Social using the XML configuration approach. All the examples I could find on the web (and on stackoverflow) always use the @Config approach as shown in the samples For whatever reason the bean definition to get an instance to the twitter API throws an AOP exception: Caused by: java.lang.IllegalStateException: Cannot create scoped proxy for bean 'scopedTarget.twitter': Target type could not be determined at the time of proxy creation. Here's the complete config file I have: <?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:jaxrs="http://cxf.apache.org/jaxrs" xmlns:context="http://www.springframework.org/schema/context" xmlns:util="http://www.springframework.org/schema/util" xmlns:cxf="http://cxf.apache.org/core" xmlns:aop="http://www.springframework.org/schema/aop" xmlns:jee="http://www.springframework.org/schema/jee" xmlns:mvc="http://www.springframework.org/schema/mvc" xmlns:jdbc="http://www.springframework.org/schema/jdbc" xsi:schemaLocation=" http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.1.xsd http://cxf.apache.org/jaxrs http://cxf.apache.org/schemas/jaxrs.xsd http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context.xsd http://www.springframework.org/schema/util http://www.springframework.org/schema/util/spring-util-3.1.xsd http://cxf.apache.org/core http://cxf.apache.org/schemas/core.xsd http://www.springframework.org/schema/aop http://www.springframework.org/schema/aop/spring-aop-3.1.xsd http://www.springframework.org/schema/jee http://www.springframework.org/schema/jee/spring-jee-3.1.xsd http://www.springframework.org/schema/mvc http://www.springframework.org/schema/mvc/spring-mvc-3.1.xsd http://www.springframework.org/schema/jdbc http://www.springframework.org/schema/jdbc/spring-jdbc-3.1.xsd"> <import resource="classpath:META-INF/cxf/cxf.xml" /> <import resource="classpath:META-INF/cxf/cxf-servlet.xml" /> <jee:jndi-lookup id="dataSource" jndi-name="java:comp/env/jdbc/DefaultDB" /> <!-- initialize DB required to store user auth tokens --> <jdbc:initialize-database data-source="dataSource" ignore-failures="ALL"> <jdbc:script location="classpath:/org/springframework/social/connect/jdbc/JdbcUsersConnectionRepository.sql"/> </jdbc:initialize-database> <bean id="connectionFactoryLocator" class="org.springframework.social.connect.support.ConnectionFactoryRegistry"> <property name="connectionFactories"> <list> <ref bean="twitterConnectFactory" /> </list> </property> </bean> <bean id="twitterConnectFactory" class="org.springframework.social.twitter.connect.TwitterConnectionFactory"> <constructor-arg value="xyz" /> <constructor-arg value="xzy" /> </bean> <bean id="usersConnectionRepository" class="org.springframework.social.connect.jdbc.JdbcUsersConnectionRepository"> <constructor-arg ref="dataSource" /> <constructor-arg ref="connectionFactoryLocator" /> <constructor-arg ref="textEncryptor" /> </bean> <bean id="connectionRepository" factory-method="createConnectionRepository" factory-bean="usersConnectionRepository" scope="request"> <constructor-arg value="#{request.userPrincipal.name}" /> <aop:scoped-proxy proxy-target-class="false" /> </bean> <bean id="twitter" factory-method="?ndPrimaryConnection" factory-bean="connectionRepository" scope="request" depends-on="connectionRepository"> <constructor-arg value="org.springframework.social.twitter.api.Twitter" /> <aop:scoped-proxy proxy-target-class="false" /> </bean> <bean id="textEncryptor" class="org.springframework.security.crypto.encrypt.Encryptors" factory-method="noOpText" /> <bean id="connectController" class="org.springframework.social.connect.web.ConnectController"> <constructor-arg ref="connectionFactoryLocator"/> <constructor-arg ref="connectionRepository"/> <property name="applicationUrl" value="https://socialscn.int.netweaver.ondemand.com/socialspringdemo" /> </bean> <bean id="signInAdapter" class="com.sap.netweaver.cloud.demo.social.SimpleSignInAdapter" /> </beans> What puzzles me is that the connectionRepositoryinstantiation works perfectly fine (I commented-out the twitter bean and tested the code!) ?!? It uses the same features: request scope and interface AOP proxy and works, but the twitter bean instantiation fails ?!? The spring social config code looks as follows (I can not see any differences, can you?): @Configuration public class SocialConfig { @Inject private Environment environment; @Inject private DataSource dataSource; @Bean @Scope(value="singleton", proxyMode=ScopedProxyMode.INTERFACES) public ConnectionFactoryLocator connectionFactoryLocator() { ConnectionFactoryRegistry registry = new ConnectionFactoryRegistry(); registry.addConnectionFactory(new TwitterConnectionFactory(environment.getProperty("twitter.consumerKey"), environment.getProperty("twitter.consumerSecret"))); return registry; } @Bean @Scope(value="singleton", proxyMode=ScopedProxyMode.INTERFACES) public UsersConnectionRepository usersConnectionRepository() { return new JdbcUsersConnectionRepository(dataSource, connectionFactoryLocator(), Encryptors.noOpText()); } @Bean @Scope(value="request", proxyMode=ScopedProxyMode.INTERFACES) public ConnectionRepository connectionRepository() { Authentication authentication = SecurityContextHolder.getContext().getAuthentication(); if (authentication == null) { throw new IllegalStateException("Unable to get a ConnectionRepository: no user signed in"); } return usersConnectionRepository().createConnectionRepository(authentication.getName()); } @Bean @Scope(value="request", proxyMode=ScopedProxyMode.INTERFACES) public Twitter twitter() { Connection<Twitter> twitter = connectionRepository().findPrimaryConnection(Twitter.class); return twitter != null ? twitter.getApi() : new TwitterTemplate(); } @Bean public ConnectController connectController() { ConnectController connectController = new ConnectController(connectionFactoryLocator(), connectionRepository()); connectController.addInterceptor(new PostToWallAfterConnectInterceptor()); connectController.addInterceptor(new TweetAfterConnectInterceptor()); return connectController; } @Bean public ProviderSignInController providerSignInController(RequestCache requestCache) { return new ProviderSignInController(connectionFactoryLocator(), usersConnectionRepository(), new SimpleSignInAdapter(requestCache)); } } Any help/pointers would be appreciated!!! Cheers, Matthias

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• Big Data – Evolution of Big Data – Day 3 of 21

  - by Pinal Dave

  In yesterday’s blog post we answered what is the Big Data. Today we will understand why and how the evolution of Big Data has happened. Though the answer is very simple, I would like to tell it in the form of a history lesson. Data in Flat File In earlier days data was stored in the flat file and there was no structure in the flat file.  If any data has to be retrieved from the flat file it was a project by itself. There was no possibility of retrieving the data efficiently and data integrity has been just a term discussed without any modeling or structure around. Database residing in the flat file had more issues than we would like to discuss in today’s world. It was more like a nightmare when there was any data processing involved in the application. Though, applications developed at that time were also not that advanced the need of the data was always there and there was always need of proper data management. Edgar F Codd and 12 Rules Edgar Frank Codd was a British computer scientist who, while working for IBM, invented the relational model for database management, the theoretical basis for relational databases. He presented 12 rules for the Relational Database and suddenly the chaotic world of the database seems to see discipline in the rules. Relational Database was a promising land for all the unstructured database users. Relational Database brought into the relationship between data as well improved the performance of the data retrieval. Database world had immediately seen a major transformation and every single vendors and database users suddenly started to adopt the relational database models. Relational Database Management Systems Since Edgar F Codd proposed 12 rules for the RBDMS there were many different vendors who started them to build applications and tools to support the relationship between database. This was indeed a learning curve for many of the developer who had never worked before with the modeling of the database. However, as time passed by pretty much everybody accepted the relationship of the database and started to evolve product which performs its best with the boundaries of the RDBMS concepts. This was the best era for the databases and it gave the world extreme experts as well as some of the best products. The Entity Relationship model was also evolved at the same time. In software engineering, an Entity–relationship model (ER model) is a data model for describing a database in an abstract way. Enormous Data Growth Well, everything was going fine with the RDBMS in the database world. As there were no major challenges the adoption of the RDBMS applications and tools was pretty much universal. There was a race at times to make the developer’s life much easier with the RDBMS management tools. Due to the extreme popularity and easy to use system pretty much every data was stored in the RDBMS system. New age applications were built and social media took the world by the storm. Every organizations was feeling pressure to provide the best experience for their users based the data they had with them. While this was all going on at the same time data was growing pretty much every organization and application. Data Warehousing The enormous data growth now presented a big challenge for the organizations who wanted to build intelligent systems based on the data and provide near real time superior user experience to their customers. Various organizations immediately start building data warehousing solutions where the data was stored and processed. The trend of the business intelligence becomes the need of everyday. Data was received from the transaction system and overnight was processed to build intelligent reports from it. Though this is a great solution it has its own set of challenges. The relational database model and data warehousing concepts are all built with keeping traditional relational database modeling in the mind and it still has many challenges when unstructured data was present. Interesting Challenge Every organization had expertise to manage structured data but the world had already changed to unstructured data. There was intelligence in the videos, photos, SMS, text, social media messages and various other data sources. All of these needed to now bring to a single platform and build a uniform system which does what businesses need. The way we do business has also been changed. There was a time when user only got the features what technology supported, however, now users ask for the feature and technology is built to support the same. The need of the real time intelligence from the fast paced data flow is now becoming a necessity. Large amount (Volume) of difference (Variety) of high speed data (Velocity) is the properties of the data. The traditional database system has limits to resolve the challenges this new kind of the data presents. Hence the need of the Big Data Science. We need innovation in how we handle and manage data. We need creative ways to capture data and present to users. Big Data is Reality! Tomorrow In tomorrow’s blog post we will try to answer discuss Basics of Big Data Architecture. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Working with Temporal Data in SQL Server

  - by Dejan Sarka

  My third Pluralsight course, Working with Temporal Data in SQL Server, is published. I am really proud on the second part of the course, where I discuss optimization of temporal queries. This was a nearly impossible task for decades. First solutions appeared only lately. I present all together six solutions (and one more that is not a solution), and I invented four of them. http://pluralsight.com/training/Courses/TableOfContents/working-with-temporal-data-sql-server

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• blurry lines between web application context layer, service layer and data access layer in spring

  - by thenaglecode

  I Originally asked this question in SO but on advice I have moved the question here... I'll admit I'm a spring newbie, but you can correct me if I'm wrong, this one liner looks kinda fishy in a best practices sort of way: @RepositoryRestResource(collectionResourceRel="people"...) public interface PersonRepository extends PagingAndSortingRepository<Person, Long> For those who are unaware, the following does many things: It is an interface definition that can be registered in an application context as a jpa repository, automagically hooking up all the default CRUD operations within a persistence context (that is externally configured). and also configures default controller/request-mapping/handler functionality at the namespace "/people" relative to your configured dispatcher servlet-mapping. Here's my point. I just crossed 3 conceptual layers with one line of code! this feels against my seperation-of-concern instincts but i wanted to hear your opinion. And for the sake of being on a question and answer site, I would like to know whether there is a better way of seperating these different layers - Service, Data, Controllers - whilst maintaining as minimal configuration as possible

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• Spring security request matcher is not working with regex

  - by Felipe Cardoso Martins

  Using Spring MVC + Security I have a business requirement that the users from SEC (Security team) has full access to the application and FRAUD (Anti-fraud team) has only access to the pages that URL not contains the words "block" or "update" with case insensitive. Bellow, all spring dependencies: $ mvn dependency:tree | grep spring [INFO] +- org.springframework:spring-webmvc:jar:3.1.2.RELEASE:compile [INFO] | +- org.springframework:spring-asm:jar:3.1.2.RELEASE:compile [INFO] | +- org.springframework:spring-beans:jar:3.1.2.RELEASE:compile [INFO] | +- org.springframework:spring-context:jar:3.1.2.RELEASE:compile [INFO] | +- org.springframework:spring-context-support:jar:3.1.2.RELEASE:compile [INFO] | \- org.springframework:spring-expression:jar:3.1.2.RELEASE:compile [INFO] +- org.springframework:spring-core:jar:3.1.2.RELEASE:compile [INFO] +- org.springframework:spring-web:jar:3.1.2.RELEASE:compile [INFO] +- org.springframework.security:spring-security-core:jar:3.1.2.RELEASE:compile [INFO] | \- org.springframework:spring-aop:jar:3.0.7.RELEASE:compile [INFO] +- org.springframework.security:spring-security-web:jar:3.1.2.RELEASE:compile [INFO] | +- org.springframework:spring-jdbc:jar:3.0.7.RELEASE:compile [INFO] | \- org.springframework:spring-tx:jar:3.0.7.RELEASE:compile [INFO] +- org.springframework.security:spring-security-config:jar:3.1.2.RELEASE:compile [INFO] +- org.springframework.security:spring-security-acl:jar:3.1.2.RELEASE:compile Bellow, some examples of mapped URL path from spring log: Mapped URL path [/index] onto handler 'homeController' Mapped URL path [/index.*] onto handler 'homeController' Mapped URL path [/index/] onto handler 'homeController' Mapped URL path [/cellphone/block] onto handler 'cellphoneController' Mapped URL path [/cellphone/block.*] onto handler 'cellphoneController' Mapped URL path [/cellphone/block/] onto handler 'cellphoneController' Mapped URL path [/cellphone/confirmBlock] onto handler 'cellphoneController' Mapped URL path [/cellphone/confirmBlock.*] onto handler 'cellphoneController' Mapped URL path [/cellphone/confirmBlock/] onto handler 'cellphoneController' Mapped URL path [/user/update] onto handler 'userController' Mapped URL path [/user/update.*] onto handler 'userController' Mapped URL path [/user/update/] onto handler 'userController' Mapped URL path [/user/index] onto handler 'userController' Mapped URL path [/user/index.*] onto handler 'userController' Mapped URL path [/user/index/] onto handler 'userController' Mapped URL path [/search] onto handler 'searchController' Mapped URL path [/search.*] onto handler 'searchController' Mapped URL path [/search/] onto handler 'searchController' Mapped URL path [/doSearch] onto handler 'searchController' Mapped URL path [/doSearch.*] onto handler 'searchController' Mapped URL path [/doSearch/] onto handler 'searchController' Bellow, a test of the regular expressions used in spring-security.xml (I'm not a regex speciality, improvements are welcome =]): import java.util.Arrays; import java.util.List; public class RegexTest { public static void main(String[] args) { List<String> pathSamples = Arrays.asList( "/index", "/index.*", "/index/", "/cellphone/block", "/cellphone/block.*", "/cellphone/block/", "/cellphone/confirmBlock", "/cellphone/confirmBlock.*", "/cellphone/confirmBlock/", "/user/update", "/user/update.*", "/user/update/", "/user/index", "/user/index.*", "/user/index/", "/search", "/search.*", "/search/", "/doSearch", "/doSearch.*", "/doSearch/"); for (String pathSample : pathSamples) { System.out.println("Path sample: " + pathSample + " - SEC: " + pathSample.matches("^.*$") + " | FRAUD: " + pathSample.matches("^(?!.*(?i)(block|update)).*$")); } } } Bellow, the console result of Java class above: Path sample: /index - SEC: true | FRAUD: true Path sample: /index.* - SEC: true | FRAUD: true Path sample: /index/ - SEC: true | FRAUD: true Path sample: /cellphone/block - SEC: true | FRAUD: false Path sample: /cellphone/block.* - SEC: true | FRAUD: false Path sample: /cellphone/block/ - SEC: true | FRAUD: false Path sample: /cellphone/confirmBlock - SEC: true | FRAUD: false Path sample: /cellphone/confirmBlock.* - SEC: true | FRAUD: false Path sample: /cellphone/confirmBlock/ - SEC: true | FRAUD: false Path sample: /user/update - SEC: true | FRAUD: false Path sample: /user/update.* - SEC: true | FRAUD: false Path sample: /user/update/ - SEC: true | FRAUD: false Path sample: /user/index - SEC: true | FRAUD: true Path sample: /user/index.* - SEC: true | FRAUD: true Path sample: /user/index/ - SEC: true | FRAUD: true Path sample: /search - SEC: true | FRAUD: true Path sample: /search.* - SEC: true | FRAUD: true Path sample: /search/ - SEC: true | FRAUD: true Path sample: /doSearch - SEC: true | FRAUD: true Path sample: /doSearch.* - SEC: true | FRAUD: true Path sample: /doSearch/ - SEC: true | FRAUD: true Tests Scenario 1 Bellow, the important part of spring-security.xml: <security:http entry-point-ref="entryPoint" request-matcher="regex"> <security:intercept-url pattern="^.*$" access="ROLE_SEC" /> <security:intercept-url pattern="^(?!.*(?i)(block|update)).*$" access="ROLE_FRAUD" /> <security:access-denied-handler error-page="/access-denied.html" /> <security:form-login always-use-default-target="false" login-processing-url="/doLogin.html" authentication-failure-handler-ref="authFailHandler" authentication-success-handler-ref="authSuccessHandler" /> <security:logout logout-url="/logout.html" success-handler-ref="logoutSuccessHandler" /> </security:http> Behaviour: FRAUD group **can't" access any page SEC group works fine Scenario 2 NOTE that I only changed the order of intercept-url in spring-security.xml bellow: <security:http entry-point-ref="entryPoint" request-matcher="regex"> <security:intercept-url pattern="^(?!.*(?i)(block|update)).*$" access="ROLE_FRAUD" /> <security:intercept-url pattern="^.*$" access="ROLE_SEC" /> <security:access-denied-handler error-page="/access-denied.html" /> <security:form-login always-use-default-target="false" login-processing-url="/doLogin.html" authentication-failure-handler-ref="authFailHandler" authentication-success-handler-ref="authSuccessHandler" /> <security:logout logout-url="/logout.html" success-handler-ref="logoutSuccessHandler" /> </security:http> Behaviour: SEC group **can't" access any page FRAUD group works fine Conclusion I did something wrong or spring-security have a bug. The problem already was solved in a very bad way, but I need to fix it quickly. Anyone knows some tricks to debug better it without open the frameworks code? Cheers, Felipe

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• Spring MVC annotation config problem

  - by Seth

  I'm trying to improve my spring mvc configuration so as to not require a new config file for every servlet I add, but I'm running into problems. I've tried using this tutorial as a starting point, but I'm running into an issue that I can't figure out. The problem is that when I do a GET to my servlet, I get back a 404 error. Here's my config and a representative java snippet from a Controller: web.xml: <?xml version="1.0" encoding="UTF-8"?> <web-app version="2.5" xmlns="http://java.sun.com/xml/ns/javaee" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://java.sun.com/xml/ns/javaee http://java.sun.com/xml/ns/javaee/web-app_2_5.xsd"> <display-name>SightLogix Coordination System</display-name> <description>SightLogix Coordination System</description> <servlet> <servlet-name>Spring MVC Dispatcher Servlet</servlet-name> <servlet-class>org.springframework.web.servlet.DispatcherServlet</servlet-class> <init-param> <param-name>contextConfigLocation</param-name> <param-value> /WEB-INF/application-context.xml /WEB-INF/application-security.xml </param-value> </init-param> <load-on-startup>1</load-on-startup> </servlet> <servlet-mapping> <servlet-name>Spring MVC Dispatcher Servlet</servlet-name> <url-pattern>/slcs/*</url-pattern> </servlet-mapping> <context-param> <param-name>contextConfigLocation</param-name> <param-value> /WEB-INF/application-context.xml /WEB-INF/application-security.xml </param-value> </context-param> <listener> <listener-class> org.springframework.web.context.ContextLoaderListener </listener-class> </listener> <filter> <filter-name>springSecurityFilterChain</filter-name> <filter-class>org.springframework.web.filter.DelegatingFilterProxy</filter-class> </filter> <filter-mapping> <filter-name>springSecurityFilterChain</filter-name> <url-pattern>/*</url-pattern> </filter-mapping> </web-app> application-context.xml: <?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:mvc="http://www.springframework.org/schema/mvc" xmlns:context="http://www.springframework.org/schema/context" xsi:schemaLocation=" http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.0.xsd http://www.springframework.org/schema/mvc http://www.springframework.org/schema/mvc/spring-mvc-3.0.xsd http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context-3.0.xsd" default-init-method="init" default-destroy-method="destroy"> <mvc:annotation-driven /> <context:component-scan base-package="top.level" /> </beans> application-security.xml: <beans:beans xmlns="http://www.springframework.org/schema/security" xmlns:beans="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.0.xsd http://www.springframework.org/schema/security http://www.springframework.org/schema/security/spring-security-3.0.xsd"> <http> <intercept-url pattern="/**" access="ROLE_MANAGER" requires-channel="https" /> <http-basic /> </http> <authentication-manager> <authentication-provider user-service-ref="myUserDetailsService"> <password-encoder hash="sha"/> </authentication-provider> </authentication-manager> <beans:bean id="myUserDetailsService" class="path.to.my.UserDetailsServiceImpl"> </beans:bean> </beans:beans> Snippet of a Controller class (one of many, but they all look essentially like this): @Controller @RequestMapping("/foo.xml") public class FooController { @RequestMapping(method=RequestMethod.GET) public void handleGET(HttpServletRequest request, HttpServletResponse response) throws IOException { ... Can anyone tell me what I'm doing incorrectly? Thanks!

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• How can I Convert XML to an Object using Spring 3.0 mvc while making RESTful request

  - by brock

  Hi, I'm using the Spring 3.0 RC1 framework and I'm currently testing out Spring mvc. I wanted to use Spring mvc to handle restful requests. I have set up my controller to handle the URI request. I am passing in xml with the request. So on the controller I have a method like follows: public void request(RequestObject request) { doSomething(); } I am having a hard time converting the xml to the RequestObject. I haven't seen much documentation on this and I was wondering if anyone could point me in the right direction. I'm guess that you would have to annotate the RequestObject using JAXB or something in order to tell Spring to convert the xml file to RequestObject but I'm not sure. Thanks for all of your help!!

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• New Communications Industry Data Model with "Factory Installed" Predictive Analytics using Oracle Da

  - by charlie.berger

  Oracle Introduces Oracle Communications Data Model to Provide Actionable Insight for Communications Service Providers   We've integrated pre-installed analytical methodologies with the new Oracle Communications Data Model to deliver automated, simple, yet powerful predictive analytics solutions for customers.  Churn, sentiment analysis, identifying customer segments - all things that can be anticipated and hence, preconcieved and implemented inside an applications.  Read on for more information! TM Forum Management World, Nice, France - 18 May 2010 News Facts To help communications service providers (CSPs) manage and analyze rapidly growing data volumes cost effectively, Oracle today introduced the Oracle Communications Data Model. With the Oracle Communications Data Model, CSPs can achieve rapid time to value by quickly implementing a standards-based enterprise data warehouse that features communications industry-specific reporting, analytics and data mining. The combination of the Oracle Communications Data Model, Oracle Exadata and the Oracle Business Intelligence (BI) Foundation represents the most comprehensive data warehouse and BI solution for the communications industry. Also announced today, Hong Kong Broadband Network enhanced their data warehouse system, going live on Oracle Communications Data Model in three months. The leading provider increased its subscriber base by 37 percent in six months and reduced customer churn to less than one percent. Product Details Oracle Communications Data Model provides industry-specific schema and embedded analytics that address key areas such as customer management, marketing segmentation, product development and network health. CSPs can efficiently capture and monitor critical data and transform it into actionable information to support development and delivery of next-generation services using: More than 1,300 industry-specific measurements and key performance indicators (KPIs) such as network reliability statistics, provisioning metrics and customer churn propensity. Embedded OLAP cubes for extremely fast dimensional analysis of business information. Embedded data mining models for sophisticated trending and predictive analysis. Support for multiple lines of business, such as cable, mobile, wireline and Internet, which can be easily extended to support future requirements. With Oracle Communications Data Model, CSPs can jump start the implementation of a communications data warehouse in line with communications-industry standards including the TM Forum Information Framework (SID), formerly known as the Shared Information Model. Oracle Communications Data Model is optimized for any Oracle Database 11g platform, including Oracle Exadata, which can improve call data record query performance by 10x or more. Supporting Quotes "Oracle Communications Data Model covers a wide range of business areas that are relevant to modern communications service providers and is a comprehensive solution - with its data model and pre-packaged templates including BI dashboards, KPIs, OLAP cubes and mining models. It helps us save a great deal of time in building and implementing a customized data warehouse and enables us to leverage the advanced analytics quickly and more effectively," said Yasuki Hayashi, executive manager, NTT Comware Corporation. "Data volumes will only continue to grow as communications service providers expand next-generation networks, deploy new services and adopt new business models. They will increasingly need efficient, reliable data warehouses to capture key insights on data such as customer value, network value and churn probability. With the Oracle Communications Data Model, Oracle has demonstrated its commitment to meeting these needs by delivering data warehouse tools designed to fill communications industry-specific needs," said Elisabeth Rainge, program director, Network Software, IDC. "The TM Forum Conformance Mark provides reassurance to customers seeking standards-based, and therefore, cost-effective and flexible solutions. TM Forum is extremely pleased to work with Oracle to certify its Oracle Communications Data Model solution. Upon successful completion, this certification will represent the broadest and most complete implementation of the TM Forum Information Framework to date, with more than 130 aggregate business entities," said Keith Willetts, chairman and chief executive officer, TM Forum. Supporting Resources Oracle Communications Oracle Communications Data Model Data Sheet Oracle Communications Data Model Podcast Oracle Data Warehousing Oracle Communications on YouTube Oracle Communications on Delicious Oracle Communications on Facebook Oracle Communications on Twitter Oracle Communications on LinkedIn Oracle Database on Twitter The Data Warehouse Insider Blog

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• Big Data – How to become a Data Scientist and Learn Data Science? – Day 19 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned the importance of the analytics in Big Data Story. In this article we will understand how to become a Data Scientist for Big Data Story. Data Scientist is a new buzz word, everyone seems to be wanting to become Data Scientist. Let us go over a few key topics related to Data Scientist in this blog post. First of all we will understand what is a Data Scientist. In the new world of Big Data, I see pretty much everyone wants to become Data Scientist and there are lots of people I have already met who claims that they are Data Scientist. When I ask what is their role, I have got a wide variety of answers. What is Data Scientist? Data scientists are the experts who understand various aspects of the business and know how to strategies data to achieve the business goals. They should have a solid foundation of various data algorithms, modeling and statistics methodology. What do Data Scientists do? Data scientists understand the data very well. They just go beyond the regular data algorithms and builds interesting trends from available data. They innovate and resurrect the entire new meaning from the existing data. They are artists in disguise of computer analyst. They look at the data traditionally as well as explore various new ways to look at the data. Data Scientists do not wait to build their solutions from existing data. They think creatively, they think before the data has entered into the system. Data Scientists are visionary experts who understands the business needs and plan ahead of the time, this tremendously help to build solutions at rapid speed. Besides being data expert, the major quality of Data Scientists is “curiosity”. They always wonder about what more they can get from their existing data and how to get maximum out of future incoming data. Data Scientists do wonders with the data, which goes beyond the job descriptions of Data Analysist or Business Analysist. Skills Required for Data Scientists Here are few of the skills a Data Scientist must have. Expert level skills with statistical tools like SAS, Excel, R etc. Understanding Mathematical Models Hands-on with Visualization Tools like Tableau, PowerPivots, D3. j’s etc. Analytical skills to understand business needs Communication skills On the technology front any Data Scientists should know underlying technologies like (Hadoop, Cloudera) as well as their entire ecosystem (programming language, analysis and visualization tools etc.) . Remember that for becoming a successful Data Scientist one require have par excellent skills, just having a degree in a relevant education field will not suffice. Final Note Data Scientists is indeed very exciting job profile. As per research there are not enough Data Scientists in the world to handle the current data explosion. In near future Data is going to expand exponentially, and the need of the Data Scientists will increase along with it. It is indeed the job one should focus if you like data and science of statistics. Courtesy: emc Tomorrow In tomorrow’s blog post we will discuss about various Big Data Learning resources. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Unstructured Data - The future of Data Administration

  Some have claimed that there is a problem with the way data is currently managed using the relational paradigm do to the rise of unstructured data in modern business. PCMag.com defines unstructured data as data that does not reside in a fixed location. They further explain that unstructured data refers to data in a free text form that is not bound to any specific structure. With the rise of unstructured data in the form of emails, spread sheets, images and documents the critics have a right to argue that the relational paradigm is not as effective as the object oriented data paradigm in managing this type of data. The relational paradigm relies heavily on structure and relationships in and between items of data. This type of paradigm works best in a relation database management system like Microsoft SQL, MySQL, and Oracle because data is forced to conform to a structure in the form of tables and relations can be derived from the existence of one or more tables. These critics also claim that database administrators have not kept up with reality because their primary focus in regards to data administration deals with structured data and the relational paradigm. The relational paradigm was developed in the 1970’s as a way to improve data management when compared to standard flat files. Little has changed since then, and modern database administrators need to know more than just how to handle structured data. That is why critics claim that today’s data professionals do not have the proper skills in order to store and maintain data for modern systems when compared to the skills of system designers, programmers , software engineers, and data designers  due to the industry trend of object oriented design and development. I think that they are wrong. I do not disagree that the industry is moving toward an object oriented approach to development with the potential to use more of an object oriented approach to data.   However, I think that it is business itself that is limiting database administrators from changing how data is stored because of the potential costs, and impact that might occur by altering any part of stored data. Furthermore, database administrators like all technology workers constantly are trying to improve their technical skills in order to excel in their job, so I think that accusing data professional is not just when the root cause of the lack of innovation is controlled by business, and it is business that will suffer for their inability to keep up with technology. One way for database professionals to better prepare for the future of database management is start working with data in the form of objects and so that they can extract data from the objects so that the stored information within objects can be used in relation to the data stored in a using the relational paradigm. Furthermore, I think the use of pattern matching will increase with the increased use of unstructured data because object can be selected, filtered and altered based on the existence of a pattern found within an object.

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• Developing an analytics's system processing large amounts of data - where to start

  - by Ryan

  Imagine you're writing some sort of Web Analytics system - you're recording raw page hits along with some extra things like tagging cookies etc and then producing stats such as Which pages got most traffic over a time period Which referers sent most traffic Goals completed (goal being a view of a particular page) And more advanced things like which referers sent the most number of vistors who later hit a goal. The naieve way of approaching this would be to throw it in a relational database and run queries over it - but that won't scale. You could pre-calculate everything (have a queue of incoming 'hits' and use to update report tables) - but what if you later change a goal - how could you efficiently re-calculate just the data that would be effected. Obviously this has been done before ;) so any tips on where to start, methods & examples, architecture, technologies etc.

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• How to implement login page using Spring Security so that it works with Spring web flow?

  - by simon

  I have a web application using Spring 2.5.6 and Spring Security 2.0.4. I have implemented a working login page, which authenticates the user against a web service. The authentication is done by defining a custom authentincation manager, like this: <beans:bean id="customizedFormLoginFilter" class="org.springframework.security.ui.webapp.AuthenticationProcessingFilter"> <custom-filter position="AUTHENTICATION_PROCESSING_FILTER" /> <beans:property name="defaultTargetUrl" value="/index.do" /> <beans:property name="authenticationFailureUrl" value="/login.do?error=true" /> <beans:property name="authenticationManager" ref="customAuthenticationManager" /> <beans:property name="allowSessionCreation" value="true" /> </beans:bean> <beans:bean id="customAuthenticationManager" class="com.sevenp.mobile.samplemgmt.web.security.CustomAuthenticationManager"> <beans:property name="authenticateUrlWs" value="${WS_ENDPOINT_ADDRESS}" /> </beans:bean> The authentication manager class: public class CustomAuthenticationManager implements AuthenticationManager, ApplicationContextAware { @Transactional @Override public Authentication authenticate(Authentication authentication) throws AuthenticationException { //authentication logic return new UsernamePasswordAuthenticationToken(principal, authentication.getCredentials(), grantedAuthorityArray); } The essential part of the login jsp looks like this: <c:url value="/j_spring_security_check" var="formUrlSecurityCheck"/> <form method="post" action="${formUrlSecurityCheck}"> <div id="errorArea" class="errorBox"> <c:if test="${not empty param.error}"> ${sessionScope["SPRING_SECURITY_LAST_EXCEPTION"].message} </c:if> </div> <label for="loginName"> Username: <input style="width:125px;" tabindex="1" id="login" name="j_username" /> </label> <label for="password"> Password: <input style="width:125px;" tabindex="2" id="password" name="j_password" type="password" /> </label> <input type="submit" tabindex="3" name="login" class="formButton" value="Login" /> </form> Now the problem is that the application should use Spring Web Flow. After the application was configured to use Spring Web Flow, the login does not work anymore - the form action to "/j_spring_security_check" results in a blank page without error message. What is the best way to adapt the existing login process so that it works with Spring Web Flow?

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• ACL architechture for a Software As a service in Spring 3.0

  - by geoaxis

  I am making a software as a service using Spring 3.0 (Spring MVC, Spring Security, Spring Roo, Hibernate) I have to come up with a flexible access control list mechanism.I have three different kinds of users System (who can do any thing to the system, includes admin and internal daemons) Operations (who can add and delete users, organizations, and do maintenance work on behalf of users and organizations) End Users (they belong to one or more organization, for each organization, the user can have one or more roles, like being organization admin, or organization read-only member) (role like orgadmin can also add users for that organization) Now my question is, how should i model the entity of User? If I just take the End User, it can belong to one or more organizations, so each user can contain a set of references to its organizations. But how do we model the users role for each organization, So for example User UX belongs to organizations og1, og2 and og3, and for og1 he is both orgadmin, and org-read-only-user, where as for og2 he is only orgadmin and for og3 he is only org-read-only-user I have the possibility of making each user belong to one organization alone, but that's making the system bounded and I don't like that idea (although i would still satisfy the requirement) If you have a better extensible ACL architecture, please suggest it. Since its a software as a service, one would expect that alot of different organizations would be part if the same system. I had one concern that it is not a good idea to keep og1 and og2 data on the same DB (if og1 decides to spawn a 100 reports on the system, og2 should not suffer) But that is some thing advanced for now and is not directly related to ACL but to the physical distribution of data and setup of services based on those ACLs This is a community Wiki question, please correct any thing which you wish to do so. Thanks

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• How to read spring-application-context.xml and AnnotationConfigWebApplicationContext both in spring mvc

  - by Suvasis

  In case I want to read bean definitions from spring-application-context.xml, I would do this in web.xml file. <context-param> <param-name>contextConfigLocation</param-name> <param-value> /WEB-INF/applicationContext.xml </param-value> </context-param> <listener> <listener-class>org.springframework.web.context.ContextLoaderListener</listener-class> </listener> In case I want to read bean definitions through Java Configuration Class (AnnotationConfigWebApplicationContext), I would do this in web.xml <servlet> <servlet-name>appServlet</servlet-name> <servlet-class>org.springframework.web.servlet.DispatcherServlet</servlet-class> <init-param> <param-name>contextClass</param-name> <param-value> org.springframework.web.context.support.AnnotationConfigWebApplicationContext </param-value> </init-param> <init-param> <param-name>contextConfigLocation</param-name> <param-value> org.package.MyConfigAnnotatedClass </param-value> </init-param> </servlet> How do I use both in my application. like reading beans from both configuration xml file and annotated class. Is there a way to load spring beans in xml file while we are using AppConfigAnnotatedClass to instantiate/use rest of the beans.

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• Big Data – Beginning Big Data – Day 1 of 21

  - by Pinal Dave

  What is Big Data? I want to learn Big Data. I have no clue where and how to start learning about it. Does Big Data really means data is big? What are the tools and software I need to know to learn Big Data? I often receive questions which I mentioned above. They are good questions and honestly when we search online, it is hard to find authoritative and authentic answers. I have been working with Big Data and NoSQL for a while and I have decided that I will attempt to discuss this subject over here in the blog. In the next 21 days we will understand what is so big about Big Data. Big Data – Big Thing! Big Data is becoming one of the most talked about technology trends nowadays. The real challenge with the big organization is to get maximum out of the data already available and predict what kind of data to collect in the future. How to take the existing data and make it meaningful that it provides us accurate insight in the past data is one of the key discussion points in many of the executive meetings in organizations. With the explosion of the data the challenge has gone to the next level and now a Big Data is becoming the reality in many organizations. Big Data – A Rubik’s Cube I like to compare big data with the Rubik’s cube. I believe they have many similarities. Just like a Rubik’s cube it has many different solutions. Let us visualize a Rubik’s cube solving challenge where there are many experts participating. If you take five Rubik’s cube and mix up the same way and give it to five different expert to solve it. It is quite possible that all the five people will solve the Rubik’s cube in fractions of the seconds but if you pay attention to the same closely, you will notice that even though the final outcome is the same, the route taken to solve the Rubik’s cube is not the same. Every expert will start at a different place and will try to resolve it with different methods. Some will solve one color first and others will solve another color first. Even though they follow the same kind of algorithm to solve the puzzle they will start and end at a different place and their moves will be different at many occasions. It is  nearly impossible to have a exact same route taken by two experts. Big Market and Multiple Solutions Big Data is exactly like a Rubik’s cube – even though the goal of every organization and expert is same to get maximum out of the data, the route and the starting point are different for each organization and expert. As organizations are evaluating and architecting big data solutions they are also learning the ways and opportunities which are related to Big Data. There is not a single solution to big data as well there is not a single vendor which can claim to know all about Big Data. Honestly, Big Data is too big a concept and there are many players – different architectures, different vendors and different technology. What is Next? In this 31 days series we will be exploring many essential topics related to big data. I do not claim that you will be master of the subject after 31 days but I claim that I will be covering following topics in easy to understand language. Architecture of Big Data Big Data a Management and Implementation Different Technologies – Hadoop, Mapreduce Real World Conversations Best Practices Tomorrow In tomorrow’s blog post we will try to answer one of the very essential questions – What is Big Data? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Reading data from an Entity Framework data model through a WCF Data Service

  - by nikolaosk

  This is going to be the fourth post of a series of posts regarding ASP.Net and the Entity Framework and how we can use Entity Framework to access our datastore. You can find the first one here , the second one here and the third one here . I have a post regarding ASP.Net and EntityDataSource. You can read it here .I have 3 more posts on Profiling Entity Framework applications. You can have a look at them here , here and here . Microsoft with .Net 3.0 Framework, introduced WCF. WCF is Microsoft's...(read more)

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• Big Data&rsquo;s Killer App&hellip;

  - by jean-pierre.dijcks

  Recently Keith spent  some time talking about the cloud on this blog and I will spare you my thoughts on the whole thing. What I do want to write down is something about the Big Data movement and what I think is the killer app for Big Data... Where is this coming from, ok, I confess... I spent 3 days in cloud land at the Cloud Connect conference in Santa Clara and it was quite a lot of fun. One of the nice things at Cloud Connect was that there was a track dedicated to Big Data, which prompted me to some extend to write this post. What is Big Data anyways? The most valuable point made in the Big Data track was that Big Data in itself is not very cool. Doing something with Big Data is what makes all of this cool and interesting to a business user! The other good insight I got was that a lot of people think Big Data means a single gigantic monolithic system holding gazillions of bytes or documents or log files. Well turns out that most people in the Big Data track are talking about a lot of collections of smaller data sets. So rather than thinking "big = monolithic" you should be thinking "big = many data sets". This is more than just theoretical, it is actually relevant when thinking about big data and how to process it. It is important because it means that the platform that stores data will most likely consist out of multiple solutions. You may be storing logs on something like HDFS, you may store your customer information in Oracle and you may store distilled clickstream information in some distilled form in MySQL. The big question you will need to solve is not what lives where, but how to get it all together and get some value out of all that data. NoSQL and MapReduce Nope, sorry, this is not the killer app... and no I'm not saying this because my business card says Oracle and I'm therefore biased. I think language is important, but as with storage I think pragmatic is better. In other words, some questions can be answered with SQL very efficiently, others can be answered with PERL or TCL others with MR. History should teach us that anyone trying to solve a problem will use any and all tools around. For example, most data warehouses (Big Data 1.0?) get a lot of data in flat files. Everyone then runs a bunch of shell scripts to massage or verify those files and then shoves those files into the database. We've even built shell script support into external tables to allow for this. I think the Big Data projects will do the same. Some people will use MapReduce, although I would argue that things like Cascading are more interesting, some people will use Java. Some data is stored on HDFS making Cascading the way to go, some data is stored in Oracle and SQL does do a good job there. As with storage and with history, be pragmatic and use what fits and neither NoSQL nor MR will be the one and only. Also, a language, while important, does in itself not deliver business value. So while cool it is not a killer app... Vertical Behavioral Analytics This is the killer app! And you are now thinking: "what does that mean?" Let's decompose that heading. First of all, analytics. I would think you had guessed by now that this is really what I'm after, and of course you are right. But not just analytics, which has a very large scope and means many things to many people. I'm not just after Business Intelligence (analytics 1.0?) or data mining (analytics 2.0?) but I'm after something more interesting that you can only do after collecting large volumes of specific data. That all important data is about behavior. What do my customers do? More importantly why do they behave like that? If you can figure that out, you can tailor web sites, stores, products etc. to that behavior and figure out how to be successful. Today's behavior that is somewhat easily tracked is web site clicks, search patterns and all of those things that a web site or web server tracks. that is where the Big Data lives and where these patters are now emerging. Other examples however are emerging, and one of the examples used at the conference was about prediction churn for a telco based on the social network its members are a part of. That social network is not about LinkedIn or Facebook, but about who calls whom. I call you a lot, you switch provider, and I might/will switch too. And that just naturally brings me to the next word, vertical. Vertical in this context means per industry, e.g. communications or retail or government or any other vertical. The reason for being more specific than just behavioral analytics is that each industry has its own data sources, has its own quirky logic and has its own demands and priorities. Of course, the methods and some of the software will be common and some will have both retail and service industry analytics in place (your corner coffee store for example). But the gist of it all is that analytics that can predict customer behavior for a specific focused group of people in a specific industry is what makes Big Data interesting. Building a Vertical Behavioral Analysis System Well, that is going to be interesting. I have not seen much going on in that space and if I had to have some criticism on the cloud connect conference it would be the lack of concrete user cases on big data. The telco example, while a step into the vertical behavioral part is not really on big data. It used a sample of data from the customers' data warehouse. One thing I do think, and this is where I think parts of the NoSQL stuff come from, is that we will be doing this analysis where the data is. Over the past 10 years we at Oracle have called this in-database analytics. I guess we were (too) early? Now the entire market is going there including companies like SAS. In-place btw does not mean "no data movement at all", what it means that you will do this on data's permanent home. For SAS that is kind of the current problem. Most of the inputs live in a data warehouse. So why move it into SAS and back? That all worked with 1 TB data warehouses, but when we are looking at 100TB to 500 TB of distilled data... Comments? As it is still early days with these systems, I'm very interested in seeing reactions and thoughts to some of these thoughts...

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• Accelerate your SOA with Data Integration - Live Webinar Tuesday!

  - by dain.hansen

  Need to put wind in your SOA sails? Organizations are turning more and more to Real-time data integration to complement their Service Oriented Architecture. The benefit? Lowering costs through consolidating legacy systems, reducing risk of bad data polluting their applications, and shortening the time to deliver new service offerings. Join us on Tuesday April 13th, 11AM PST for our live webinar on the value of combining SOA and Data Integration together. In this webcast you'll learn how to innovate across your applications swiftly and at a lower cost using Oracle Data Integration technologies: Oracle Data Integrator Enterprise Edition, Oracle GoldenGate, and Oracle Data Quality. You'll also hear: Best practices for building re-usable data services that are high performing and scalable across the enterprise How real-time data integration can maximize SOA returns while providing continuous availability for your mission critical applications Architectural approaches to speed service implementation and delivery times, with pre-integrations to CRM, ERP, BI, and other packaged applications Register now for this live webinar!

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• Prevent Cross-Site Request Forgery in a Spring WebFlow Application

  - by Eric J.

  I'm looking for a (hopefully straightforward) way to add CSRF protection to an application build on Spring WebFlow 2. An approach that migrates well to Spring WebFlow 3 (when released) is preferred.

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• Howcan I get started with Spring Batch?

  - by C. Ross

  I'm trying to learn Spring Batch, but the startup guide is very confusing. Comments like You can get a pretty good idea about how to set up a job by examining the unit tests in the org.springframework.batch.sample package (in src/main/java) and the configuration in src/main/resources/jobs. aren't exactly helpful. Also I find the Sample project very complicated (17 non-empty Namespaces with 109 classes)! Is there a simpler place to get started with Spring Batch?

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• Can i use Spring on GAE?

  - by n002213f

  Can i use Spring Webflow/MVC and Spring Security and Hibernate on Google App Engine? Is there a list/summary of java frameworks that can be used on the GAE?

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• What are annotations and how do they actually work for frameworks like Spring?

  - by Rachel

  I am new to Spring and now a days I hear a lot about Spring Framework. I have two sets of very specific questions: Set No. 1: What are annotations in general ? How does annotations works specifically with Spring framework ? Can annotations be used outside Spring Framework or are they Framework specific ? Set No. 2: What module of Spring Framework is widely used in Industry ? I think it is Spring MVC but why it is the most used module, if am correct or correct me on this ? I am newbie to Spring and so feel free to edit this questions to make more sense.

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• What is annotations and how do it actually works for frameworks like Spring ?

  - by Rachel

  I am new to Spring and now a days I hear a lot about Spring Framework. I have two sets of very specific questions: Set No. 1: What are annotations in general ? How does annotations works specifically with Spring framework ? Can annotations be used outside Spring Framework or are they Framework specific ? Set No. 2: What module of Spring Framework is widely used in Industry ? I think it is Spring MVC but why it is the most used module, if am correct or correct me on this ? I am newbie to Spring and so feel free to edit this questions to make more sense.

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