ILog Jrules Online Training

Introduction to ILOG JRULES

IBM ILOG is a collection of tools and services designed to help customers more effectively and efficiently analyze, plan and improve business processes. ILOG incorporated into IBM operational decision manager enterprise software products for Business Rule Management Systems has visualization, optimization and supply chain solutions. WebSphere Operational Decision Management improves the quality of transaction and process related decisions to determine the appropriate course of action for each customer and internal interaction. Business rule is written in natural language and understood easily by business users.

ILog Jrules is a BRMS Software package which is now acquired by IBM. It is a widely used tool in BRM Space and has many attractive features which are suitable to the need of enterprise applications. The latest version of ILOG JRules is 7.0. ILOG JRules has following components:

1).Rule Studio

2).Rule Team Server

3).Rule Execution Server

4).Rule Scenario Manager

Above are the major components or products which comes with the ILOG JRules product. JRules is basically a Java based system. ILOG Also has a version for .net which also supports the same features like ILOG JRules support.As companies rely more and more on information technology (IT) to manage their business, IT departments need to develop more complex applications and simultaneously accommodate an increasing rate of change in the applications they support.

Often, the implementation of the company's business policy within these applications becomes too complex, voluminous, and fast changing for a traditional software architecture. When this happens, an enterprise Business Rule Management System (BRMS) provides solutions to make this management more efficient, both for developers and for the business users of the applications.

With a BRMS, developers and architects can extract the business logic from the traditional code of an application. When business policies are hard-coded into an enterprise application, the process of updating the system requires specialist programming staff, puts the stability of the system at risk, and can take a long time. By externalizing the business logic from a business application with business rules, IT users can develop and run the business logic independently of the application.

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Informatica MDM Online Training

Introduction to MDM

Informatica achieved major goal in its roadmap for powering universal master data management (MDM). Informatica announced the product at Informatica’s annual user conference – Informatica World 2013.

There are four major pillars on which Universal MDM depends; they are universal services, universal domains, universal governance and universal solutions. With Infa MDM 9.6, Informatica delivers on all four capabilities with a truly flexible master data management technology that enables companies to start small by solving their most immediate business problem and scaling to others across the enterprise.

Informatica MDM 9.6 brings this universal MDM strategy, delivering such key benefits as:

• Dynamic data masking for improved security and compliance

• Simplified administration and rapid MDM deployment through single stage data Onboarding.

• Database independence and operational scalability for Increased end user productivity

• Empowered business users through new Informatica MDM data governance user interface.

• Accelerated time-to-value through new MDM solutions.

1.    Universal Services: They are common platform services such as data integration, data quality, metadata and MDM services such as matching, survivorship, and security that form the foundation of MDM architecture. Informatica MDM 9.6 enhances the Universal Services capability with:

Supports Dynamic Data Masking: Real-time Protection against Unauthorized Users

For Dynamic data masking Infa MDM 9.6 uses real-time data protection rules to prevent unauthorized users from accessing sensitive information that is not required for them to perform their activities.

Single Stage Data Onboarding: Faster Deployment, Easier Administration

Informatica MDM customers can rapidly onboard master data from source systems directly into the target data model using Informatica Data Integration Hub services. While preserving the data validation checks and data quality tasks, this process simplifies the administration using familiar Informatica Data Integration tools and reduces the number of onboarding steps by half. This new single stage onboarding capability is delivered through Informatica MDM’s integration with Informatica Vibe, the world’s first and only embeddable virtual data machine.

2.    Universal Domains: Universal Domains are multiple data domains such as customer, product, location, employee, and beyond, as well as the relationships across the domains. Informatica MDM 9.6 expands the Universal Domains capability with:

Database Independence: Taking the Lid off Scalability and Big Data Processing

Informatica MDM 9.6 frees MDM from the restraints of traditional database processing by abstracting the data access layer for data matching, consolidation and outbound integration. Thus freed, MDM processes and deployments scale more efficiently and without limitation to handle increased data volumes, tasks and users.

3.    Universal Governance: Universal Governance empowers business users to perform data governance and stewardship activities through a common user interface accessible via InformaticaMDM Data Director, business applications, or MDM iOS app. Informatica MDM 9.6 powers Universal Governance capability with:

Enhanced Data Governance User Interface: Empowers business users

Informatica MDM 9.6 enhances data steward productivity and experience with improved reporting in the Informatica MDM Data Director dashboard, revised Data View with logical grouping and displaying match-based relationship disposition and embedded match scores.

4.    Universal Solutions: Universal Solutions accelerate Time-to-Value with predefined data models, prewired business rules and logic, and preconfigured user interface. Informatica MDM 9.6 expands its portfolio of industry solutions, already available for banking and pharmaceuticals, with:

New MDM Solutions: Acceleration of time-to-value

Continuing the innovation in MDM industry solutions, Informatica MDM 9.6 now includes solutions for the healthcare and insurance industries. These solutions improve business user productivity in common business processes in these industries.

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IBM WMB Online Training

WebSphere Message Broker introduction

You can use IBM® WebSphere® Message Broker to connect applications together, regardless of the message formats or protocols that they support.

This connectivity means that your diverse applications can interact and exchange data with other applications in a flexible, dynamic, and extensible infrastructure. WebSphere Message Broker routes, transforms, and enriches messages from one location to any other location:

§  The product supports a wide range of protocols: WebSphere MQ, JMS 1.1, HTTP and HTTPS, Web Services (SOAP and REST), File, Enterprise Information Systems (including SAP and Siebel), and TCP/IP.

§  It supports a broad range of data formats: binary formats (C and COBOL), XML, and industry standards (including SWIFT, EDI, and HIPAA). You can also define your own data formats.

§  It supports many operations, including routing, transforming, filtering, enriching, monitoring, distribution, collection, correlation, and detection.

Your interactions with WebSphere Message Broker can be considered in two broad categories:

§  Application development, test, and deployment. You can use one or more of the supplied options to program your applications:

§  Patterns provide reusable solutions that encapsulates a tested approach to solving a common architecture, design, or deployment task in a particular context. You can use them unchanged or modify them to suit your own requirements.

§  Message flows describe your application connectivity logic, which defines the exact path that your data takes in the broker, and therefore the processing that is applied to it by the message nodes in that flow.

§  Message nodes encapsulate required integration logic, which operates on your data when it is processed through your broker.

§  Message trees describe data in an efficient, format independent way. You can examine and modify the contents of message trees in many of the nodes that are provided, and you can supply additional nodes to your own design.

§  You can implement transformations by using graphical mapping, Java™, PHP, ESQL, and XSL, and can make your choice based on the skills of your workforce without having to provide retraining.

§  Operational management and performance. WebSphere Message Broker includes the following features and functionality, which support the operation and performance of your deployment:

§  An extensive range of administration and systems management options for developed solutions.

§  Support for a wide range of operating system and hardware platforms.

§  A scalable, highly performing architecture, based on requirements from traditional transaction processing environments.

§  Tight integration with software products, from IBM and other vendors, that provide related management and connectivity services.

WebSphere Message Broker is available in several modes, so that you can purchase a solution that meets your requirements. For more information, see Operation modes.

Application development

Your message processing applications, which you can run on more than 30 industry platforms, can connect to the broker by using one of the supported protocols already listed. Platforms from IBM, Microsoft, Oracle, and others are supported.

Diverse applications can exchange information in widely differing formats, with brokers handling the processing required for the information to arrive in the right place in the correct format, according to the rules that you have defined. The applications need only to understand their own formats and protocols, and not standards used by the applications to which they are connected.

Applications also have much greater flexibility in selecting which messages they want to receive, because you can apply filters to control the messages that are made available to them.

WebSphere Message Broker provides a framework that contains a wide variety of supplied, basic, functions along with user-defined enhancements, to enable rapid construction and modification of message processing rules.

Your applications can be integrated by providing message and data transformations in a single place, the broker. This integration helps to reduce the cost of application upgrades and modifications. You can extend your systems to reach your suppliers and customers, by meeting their interface requirements within your brokers. This ability can help you to improve the quality of your interactions, and allow you to respond more quickly to changing or additional requirements.

Messages are manipulated according to the rules that you define by using the WebSphere Message Broker Toolkit.

Operational management

WebSphere Message Broker supports a choice of interfaces for operation and administration of your brokers:

§  The WebSphere Message Broker Toolkit

§  The WebSphere Message Broker Explorer is a graphical user interface, based on the WebSphere MQ Explorer, for administering your brokers

§  Applications that use the Message Broker API (also known as the CMP API)

§  A comprehensive set of commands, that you can run interactively or by using scripts

§  The Representational State Transfer API (REST) allows development of administrative applications without the need to install client software and web browsers can administer brokers through a user interface.

WebSphere Message Broker builds on the WebSphere MQ product, which provides assured, once-only delivery of messages between the applications. WebSphere MQ is included when you purchase WebSphere Message Broker.

WebSphere Message Broker is complemented by a wide variety of other IBM products such as Tivoli® Composite Application Manager for SOA, WebSphere Service Registry and Repository (WSRR), WebSphere Process Server, and WebSphere Transformation Extender (WTX).

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IBM Netezza Online Training

Introduction to Netezza

IBM Netezza is a powerful and highly parallelized Data Warehousing system that is simple to administer and to maintain. This system is an appliance that is purpose-built for data warehousing. The system is commonly referred to as data warehouse appliance that is designed specifically for running complex data warehousing workloads. The concept of an appliance is realized by integrating the database, server and the storage into an easy to deploy and manage system.

In any database system the main bottle neck is IO. IBM Netezza reduces this bottleneck by using a commodity FPGA (Field-Programmable Gate Array) by pushing the SQL closer to silicon to help improve IO performance. This core component of the appliance is referred to as the Database Accelerator.

The Database Accelerator along with the other components of the IBM Netezza appliance was discussed during a short high-level overview of the architecture. This overview was presented at the beginning of the workshop during a brief presentation. The presentation also included the basic usage on how to administer and maintain a Netezza database. The concepts covered in the presentation were reinforced by getting hands on experience using a Netezza appliance. Instead of using an actual IBM Netezza appliance a virtualized environment was provided with a lab manual outlining the steps and commands to run. The lab manual also included explanations for each of the step-by-step instructions used in the exercises.

The agenda for the topics covered in the Hands-on-Lab exercises was:

1.    Create Netezza Database Users and Groups (and set privileges)

2.    Create the Workshop database

3.    Create tables in the Workshop database

4.    Load data into the Netezza Appliance with the nzload utility using the External Table framework

The workshop showed how simple it was to setup a IBM Netezza appliance after it has been delivered and configured. A factory-configured and installed IBM Netezza appliance includes some of the following components:

§  An IBM Netezza data warehouse appliance with pre-installed IBM Netezza software

§  A preconfigured Linux operating system (with Netezza modifications)

§  Several preconfigured Linux users and groups:

§  An IBM Netezza database user named ADMIN. The ADMIN user is the database super-user, and has full access to all system functions and objects

The IBM Netezza appliance also includes a SQL dialect called Netezza Structured Query Language (NZSQL). You can use SQL commands to create and manage your Netezza databases, user access, and permissions for the databases, as well as to query and modify the contents of the databases.

On a new IBM Netezza appliance, there is one main database, SYSTEM, and a database template, MASTER_DB. IBM Netezza uses the MASTER_DB as a template for all other user databases that are created on the system.

Before creating the databases and tables, a brief explanation was provided about the virtualized environment used in the workshop. This also included how to connect to the Netezza appliance, which is completed through the Netezza SMP Host. Once connected to the Netezza appliance a set of new users were created, which were used for the remainder of the workshop. The concept of users and privileges were explored later when the database and tables were created. This would involve setting up a basic Security Access Model, which restricted or permitted certain actions to objects within the Netezza Appliance.

After the Netezza Database Users were created the database and the tables for the workshop were created. Once the database and the tables are created, the next step as with any data warehouse environment is to load data into the tables in the database. This was easy by using the Netezza utility nzload which uses the External Table framework to efficiently load data in to a Netezza database. This framework contains more than one component, some of these components are:

§  External Tables -- These are tables stored as flat files on the host or client systems and registered like tables in the Netezza catalog. They can be used to load data into the Netezza appliance or unload data to the file system.

§  nzload -- This is a wrapper command line tool around external tables that provides an easy method loading data into the Netezza appliance.

§  Format Options -- These are options for formatting the data load to and from external tables.

With a good understanding on how to create and populate tables in a Netezza database discussion followed on the importance of Data Distribution. Since IBM Netezza is built on a massively parallel architecture that distributes data and workloads over a large number of processing and data nodes, the single most important tuning factor is choosing the right distribution key. The distribution key governs which data rows of a table are distributed to a data slice and it is very important to choose an optimal distribution key to avoid data skew, processing skew and to make joins co-located whenever possible. This concept was so important that a separate section was devoted to this topic. The exercises examined how to pick the best Hash Key for distribution for each of the tables created in this workshop. During these set of exercises CTAS tables were utilized that showed how easy it is to change the Hash Key for a table without having to manually recreate and reload the data in the table.

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Apache Mahout Online Training

Introduction to Apache Mahout:

Once the exclusive domain of academics and corporations with large research budgets, intelligent applications that learn from data and user input are becoming more common. The need for machine-learning techniques like clustering, collaborative filtering, and categorization has never been greater, be it for finding commonalities among large groups of people or automatically tagging large volumes of Web content. The Apache Mahout project aims to make building intelligent applications easier and faster. Mahout co-founder Grant Ingersoll introduces the basic concepts of machine learning and then demonstrates how to use Mahout to cluster documents, make recommendations, and organize content.

Apache Mahout is an Apache TLP project to build powerful scalable machine learning tools for use on analyzing big-data on distributed manner. Machine learning is the discipline of artificial intelligence that enables to learn on data, spam filtering and natural language processing. Apache mahout enable clustering, dimensionality reduction and miscellaneous.

Machine learning is a subfield of artificial intelligence concerned with techniques that allow computers to improve their outputs based on previous experiences. The field is closely related to data mining and often uses techniques from statistics, probability theory, pattern recognition, and a host of other areas. Although machine learning is not a new field, it is definitely growing. Many large companies, including IBM®, Google, Amazon, Yahoo!, and Facebook, have implemented machine-learning algorithms in their applications. Many, many more companies would benefit from leveraging machine learning in their applications to learn from users and past situations.
Machine learning uses run the gamut from game playing to fraud detection to stock-market analysis. It's used to build systems like those at Netflix and Amazon that recommend products to users based on past purchases, or systems that find all of the similar news articles on a given day. It can also be used to categorize Web pages automatically according to genre (sports, economy, war, and so on) or to mark e-mail messages as spam.

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MongoDB Online Training

Introduction to MongoDB

MongoDB is the open source NoSQL database product and has enabled developers to build new types of applications for cloud and social technologies. In this level of consistency can be chosen depending on the value of the data and allow faster access to data by utilizing internal memory for storing working set. Dynamic schema provides rich data model allowing maps to navigate programming language types.

Overview

MongoDB is a document database that provides high performance, high availability, and easy scalability.

§  Document Database

§  Documents (objects) map nicely to programming language data types.

§  Embedded documents and arrays reduce need for joins.

§  Dynamic schema makes polymorphism easier.

§  High Performance

§  Embedding makes reads and writes fast.

§  Indexes can include keys from embedded documents and arrays.

§  Optional streaming writes (no acknowledgments).

§  High Availability

§  Replicated servers with automatic master failover.

§  Easy Scalability

§  Automatic sharding distributes collection data across machines.

§  Eventually-consistent reads can be distributed over replicated servers.

§  Advanced Operations

§  With MongoDB Management Service (MMS) MongoDB supports a complete backup solution and full deployment monitoring.

MongoDB Data Model

A MongoDB deployment hosts a number of databases. A manual:database holds a set of collections. Amanual:collection holds a set of documents. A manual:document is a set of key-value pairs. Documents have dynamic schema. Dynamic schema means that documents in the same collection do not need to have the same set of fields or structure, and common fields in a collection’s documents may hold different types of data.

See Document Structure and Data Modeling for more information.

Deployment Architectures

Although MongoDB supports a “standalone” or single-instance operation, production MongoDB deployments are distributed by default. Replica sets provide high performance replication with automated failover, while sharded clusters make it possible to partition large data sets over many machines transparently to the users. MongoDB users combine replica sets and sharded clusters to provide high levels redundancy for large data sets transparently for applications.

MongoDB Queries

Queries in MongoDB provides a set of operators to define how the find()method selects documents from a collection based on a query specification document that uses a combination of exact equality matches and conditionals using a query operator.

MongoDB Design Philosophy

MongoDB wasn’t designed in a lab. We built MongoDB from our own experiences building large scale, high availability, robust systems. We didn’t start from scratch, we really tried to figure out what was broken, and tackle that. So the way I think about MongoDB is that if you take MySql, and change the data model from relational to document based, you get a lot of great features: embedded docs for speed, manageability, agile development with schema-less databases, easier horizontal scalability because joins aren’t as important. There are lots of things that work great in relational databases: indexes, dynamic queries and updates to name a few, and we haven’t changed much there. For example, the way you design your indexes in MongoDB should be exactly the way you do it in MySql or Oracle, you just have the option of indexing an embedded field.

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IBM BPM Online Training

Introduction to IBM BPM

Business Process Manager Express and Business Process Manager Standard run BPMN processes, providing the functionality of Lombardi Edition. Business Process Manager Advanced adds the ability to run BPEL processes, providing the functionality of both Lombardi Edition and Process Server. This article focuses on Business Process Manager Advanced.

A key concept from Lombardi Edition that is expanded on in Business Process Manager is that of a central repository for all process artifacts, called the Process Center. All of the items you build are stored and governed by the Process Center. The Process Center is a process repository, focusing on assets at the process level. It can work with WebSphere Service Registry and Repository, which provides governance at the service level.

The tool used by BPMN process designers who formerly used the Lombardi Authoring Environment is now called the IBM Process Designer (hereafter called Process Designer). The tool used by BPEL developers who previously used WebSphere Integration Developer is now called the IBM Integration Designer (hereafter called Integration Designer).

Business scenario

How you could create a human-centric process in Lombardi Edition, and invoke an integration-centric process in Process Server. In this article, you'll see how the same scenario can be performed using Business Process Manager V7.5, and how having the Process Center as a common repository makes the development and deployment effort easier. The first scenario will show a top-down design, where you start with a BPMN process in Process Designer and create a new service to be implemented in Integration Developer. The second scenario will show a bottoms-up design, where you create an asset in Integration Developer and make it available to Process Designer for use in a BPMN process.

Working with the BPEL process

For the purposes of this article, a pre-built process is provided. You'll begin by importing the process, exploring it, and exposing it as a Web service. A project interchange file is provided for you to download and unzip.

Import the process

The Process Center manages process applications. You can access the Process Center from Process Designer, Integration Designer, or from a web browser. Since you'll begin with a BPEL process, you'll use Integration Designer for this section. Process applications consist of artifacts created in Process Designer, Integration Designer, or both. This enables you to manage all relevant artifacts in a single container, the Process App

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SAP Hybris Online Training

Introduction to SAP Hybris

Hybris, the world’s fastest-growing commerce platform provider ranked “leader” by both principal analyst firms, today announced that the hybris Commerce Suite can now be fully integrated with SAP and is available on the hybris Extend marketplace The integration offers hybris customers and partners a way to facilitate fast and easy integration with SAP Enterprise Resource Planning (ERP). hybris will officially announce the integration at SAP’s Sapphire NOW event in Orlando (hybris booth number: 1633).

Based on hybris’ OmniCommerce strategy, this integration enables retailers and enterprises to provide a single, cohesive customer experience from any sales channel and touchpoint in the purchasing process through hybris’ open architecture. This avoids the "rip and replace" approaches used by many vendors. Instead, companies can leverage the potential of their total system landscape in new ways to provide an enhanced customer experience.

"One of the major challenges manufacturers and distributors face when executing an e-commerce strategy is how to easily and cost-effectively integrate their commerce system with their ERP system,” explained Patrick Finn, Vice President of Channels, Americas at hybris. “With more than 100 customers globally already incorporating hybris' state-of-the art commerce platform with SAP, there is a proven model for this integration. However, the new framework is a great asset to our customers and channel partners as the integration process will now be faster, easier and cheaper. In addition, organizations can avoid expensive consulting, process and systems integration management time, and experience a more streamlined and effective process.”

SAP Hybris an agile suite provides integration framework for e commerce solutions. It enables multi-channel commerce, master data management and order management. Hybris commerce accelerator is customizable with B2B functionality available in on premise perpetual license. Segmentation and personalization by inheriting customer experience intelligence functionality. Access to ERP and back-office tools for advanced customer experience. SAPHybris online training teach the complete knowledge on management console and cockpit framework to determine scope of customization.

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