SAP's Business Information Warehouse (BW) is a comprehensive business intelligence product centered around a data warehouse that is optimized for SAP's R/3 environment.
SAP BW is one of the important technical module of SAP and it stands for business information warehouse. The most important thing in the running of a business is data. Every business activity generates data. This data is used by a company is all areas of its business; it is used by the employees of the company in their work, to help them make a better decision.
SAP NetWeaver BW is a special software made by the maker of enterprise resource planning ERP ) software systems, SAP, which groups together and formats huge amounts of business data in the Enterprise Data Warehouse. It does so with the help of SAP BI tools, and is supported by a wide range of Enterprise Planning tools.
This allows the SAP BI software to analyze the data which is important for all decision making in the company. In this way, SAP BW optimizes business processes, helps a corporation to act faster and to be more flexible, as per the current requirements of a market.
SAP Fiori is a software that provides the porting of applications on mobile devices announced on 15 May 2013.
SAP Fiori is based on SAP's technology platform called NetWeaver. It enables applications to be used on desktop computers, tablets and smartphones. SAP Fiori supports HTML5.
SAP Fiori is a new user experience (UX) for SAP software and applications. It provides a set of applications that are used in regular business functions like work approvals, financial apps, calculation apps and various self-service apps.
SAP Fiori provides 300+ role-based applications like HR, Manufacturing, finance, etc. When you open the SAP Fiori home page application, you will see a picture of the flowers. It is because Fiori means ‘flowers’ in Italian.
SAP Fiori is a product line of SAP apps that have a device-agnostic user interface (UI).
At the 2013 SAP TechEd conference in Las Vegas, SAP announced that SAP Fiori would be the company's predominant user-interface model going forward for its enterprise resource planning (ERP), customer resource management (CRM), supply chain management (SCM), procurement, and talent management software, and that new Fiori applications would follow in those areas. As of this writing, there are currently 25 Fiori apps.
Video About SAP Fiori? https://www.youtube.com/watch?v=CX5X8ewlD0I
Confluence is a team collaboration software. Written in Java and mainly used in corporate environments, it is developed and marketed by Atlassian. Confluence is sold as either on-premises software or as software as a service.
Confluence is our collaboration wiki tool used to help teams to collaborate and share knowledge efficiently. With Confluence, your users can create pages and blogs which can be commented on and edited by all members of the team. For example, you will be able to create a roadmap easily, create notes containing checklist, create a knowledge base and centralize everything in one place. You can also attach files, like your excel planning and display it on a page for more convenience.
Confluence has also been designed to integrate with Jira and they have many integration points, giving Confluence users the ability to view, interact with, and reference Jira issues from a wiki page.
MLlib is Spark’s scalable machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as underlying optimization primitives, as outlined below:
Classification and regression
Feature extraction and transformation
Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface centered on the RDD abstraction This interface mirrors a functional/higher-order model of programming: a "driver" program invokes parallel operations such as map, filter or reduce on an RDD by passing a function to Spark, which then schedules the function's execution in parallel on the cluster.
These operations, and additional ones such as joins, take RDDs as input and produce new RDDs. RDDs are immutable and their operations are lazy; fault-tolerance is achieved by keeping track of the "lineage" of each RDD so that it can be reconstructed in the case of data loss. RDDs can contain any type of Python, Java, or Scala objects.
Light GBM is a fast, distributed, high-performance gradient boosting framework based on decision tree algorithm, used for ranking, classification and many other machine learning tasks.
Since it is based on decision tree algorithms, it splits the tree leaf wise with the best fit whereas other boosting algorithms split the tree depth wise or level wise rather than leaf-wise. So when growing on the same leaf in Light GBM, the leaf-wise algorithm can reduce more loss than the level-wise algorithm and hence results in much better accuracy which can rarely be achieved by any of the existing boosting algorithms. Also, it is surprisingly very fast, hence the word ‘Light’.
Watir (Web Application Testing in Ruby, pronounced water), is an open-source family of Ruby libraries for automating web browsers. It drives Internet Explorer, Firefox, Chrome, Opera and Safari, and is available as a RubyGems gem.
Watir-classic makes use of the fact that Ruby has built in Object Linking and Embedding (OLE) capabilities. As such it is possible to drive Internet Explorer programmatically. Watir-classic operates differently than HTTP based test tools, which operate by simulating a browser. Instead Watir-classic directly drives the browser through the OLE protocol, which is implemented over the Component Object Model (COM) architecture.
The COM permits interprocess communication (such as between Ruby and Internet Explorer) and dynamic object creation and manipulation (which is what the Ruby program does to the Internet Explorer). Microsoft calls this OLE automation, and calls the manipulating program an automation controller. Technically, the Internet Explorer process is the server and serves the automation objects, exposing their methods; while the Ruby program then becomes the client which manipulates the automation objects.
Watir-webdriver is a modern version of the Watir API based on Selenium. Selenium 2.0 (selenium-webdriver) aims to be the reference implementation of the WebDriver specification. In Ruby, Jari Bakken has implemented the Watir API as a wrapper around the Selenium 2.0 API. Not only is Watir-webdriver derived from Selenium 2.0, it is also built from the HTML specification, so Watir-webdriver should always be compatible with existing W3C specifications.
The Spring Web model-view-controller (MVC) framework is designed around a DispatcherServlet that dispatches requests to handlers, with configurable handler mappings, view resolution, locale and theme resolution as well as support for uploading files.
The default handler is based on the @Controller and @RequestMapping annotations, offering a wide range of flexible handling methods. With the introduction of Spring 3.0, the @Controller mechanism also allows you to create RESTful Web sites and applications, through the @PathVariable annotation and other features.
Spring Web MVC you can use any object as a command or form-backing object; you do not need to implement a framework-specific interface or base class. Spring's data binding is highly flexible: for example, it treats type mismatches as validation errors that can be evaluated by the application, not as system errors.
Thus you need not duplicate your business objects' properties as simple, untyped strings in your form objects simply to handle invalid submissions, or to convert the Strings properly. Instead, it is often preferable to bind directly to your business objects.
Spring's view resolution is extremely flexible. A Controller is typically responsible for preparing a model Map with data and selecting a view name but it can also write directly to the response stream and complete the request. View name resolution is highly configurable through file extension or Accept header content type negotiation, through bean names, a properties file, or even a custom ViewResolver implementation.
The model (the M in MVC) is a Map interface, which allows for the complete abstraction of the view technology. You can integrate directly with template based rendering technologies such as JSP, Velocity and Freemarker, or directly generate XML, JSON, Atom, and many other types of content. The model Map is simply transformed into an appropriate format, such as JSP request attributes, a Velocity template model.
Spring MVC, like many other web frameworks, is designed around the front controller pattern where a central Servlet, the DispatcherServlet, provides a shared algorithm for request processing while actual work is performed by configurable, delegate components. This model is flexible and supports diverse workflows.
The DispatcherServlet, as any Servlet, needs to be declared and mapped according to the Servlet specification using Java configuration or in web.xml. In turn the DispatcherServlet uses Spring configuration to discover the delegate components it needs for request mapping, view resolution, exception handling