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Janaswamy Services is a website created to serve the people through computer internetwork. We are providing various services through this site. You may use these services which is of so much use which can solve one's own issues. For example, Astrology services, Self prepared Medicines or Household medicines, Works related to Books and Publications, Training materials in Spoken English, Computer Science through our website. Especially the main intention to create our website is to make them learn and know what is what. We provide true facts about astrology and other learning materials. Knowledge is immeasurable. There may be differences in representation. The truths should be considered. So we request our viewers who view our website to go through the true facts which we keep in our Astrology Catalogue, Learning Catalogue and Devotionals Catalogue.


Latest Technologies

Cloud Computing

A cloud-based test and development environment enables developers to deliver their applications faster, more cost-effectively, and with fewer errors than traditional data center environments.

Cloud computing, also on-demand computing, is a kind of Internet-based computing that provides shared processing resources and data to computers and other devices on demand. It is a model for enabling ubiquitous, on-demand access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications and services), which can be rapidly provisioned and released with minimal management effort. Cloud computing and storage solutions provide users and enterprises with various capabilities to store and process their data in third-party data centers. It relies on sharing of resources to achieve coherence and economy of scale, similar to a utility (like the electricity grid) over a network.

Cloud computing has become a highly demanded service or utility due to the advantages of high computing power, cheap cost of services, high performance, scalability, accessibility as well as availability. Some cloud vendors are experiencing growth rates of 50% per year,but being still in a stage of infancy, it has pitfalls that need to be addressed to make cloud computing services more reliable and user friendly.

Data Warehouse/Business Intelligence

In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data and are used for creating analytical reports for knowledge workers throughout the enterprise. Examples of reports could range from annual and quarterly comparisons and trends to detailed daily sales analysis.

The data stored in the warehouse is uploaded from the operational systems (such as marketing, sales, etc., shown in the figure to the right). The data may pass through an operational data store for additional operations before it is used in the DW for reporting.

List of DW Tools used in Data Warehousing Technology:

DW - BI Softwares
SQL Server
Oracle 11g
Data Stage
Netweaver BI
Business Warehouse
Ab Initio
Ab Initio


SAP SE (/ɛseɪˈpi/) (Systemanalyse und Programmentwicklung; Systems, Applications & Products in Data Processing) is a Germanmultinational software corporation that makes enterprise software to manage business operations and customer relations.

SAP competitors are primarily in the enterprise resource planning software industry. In this field, Oracle Corporation is SAP's major competitor. SAP also competes in the customer relationship management, marketing & sales software, manufacturing, warehousing & industrial software, and supply chain management & logistics software sectors.

In 2015, the company launched SAP S/4HANA, the newest generation of the SAP Business Suite. It was written natively for the SAP HANA platform. It offers cloud, on-premises and hybrid deployment options to customers, with its benefits including a smaller data footprint, higher throughput, faster analytics and faster access to data. It also allows existing SAP Business Suite customers to upgrade to this product from SAP Business Suite.


  • SAP Advanced Planner and Optimizer (APO)
  • SAP Analytics
  • SAP Advanced Business Application Programming (ABAP)
  • SAP Apparel and Footwear Solution (AFS)
  • SAP Business Information Warehouse (BW)
  • SAP Business Intelligence (BI)
  • SAP Catalog Content Management (CCM)
  • SAP Convergent Charging (CC)
  • SAP PRD2(P2)
  • SAP Enterprise Buyer Professional (EBP)
  • SAP Enterprise Learning
  • SAP Portal (EP)
  • SAP Exchange Infrastructure (XI)
    (From release 7.0 onwards, SAP XI
    has been renamed as SAP Process Integration (SAP PI))
  • SAP Extended Warehouse Management (EWM)
  • SAP GRC (Governance, Risk and Compliance)
  • SAP EHSM (Environment Health Safety Management)
  • Enteprise Central Component (ECC)
  • SAP HANA (formerly known as High-performance Analytics Appliance)
  • SAP Human Resource Management Systems (HRMS)
  • SAP SuccessFactors
  • SAP Internet Transaction Server (ITS)
  • SAP Incentive and Commission Management (ICM)
  • SAP Knowledge Warehouse (KW)
  • SAP Manufacturing
  • SAP Master Data Management (MDM)
  • SAP Rapid Deployment Solutions (RDS)
  • SAP Service and Asset Management
  • SAP Solutions for mobile business
  • SAP Solution Composer
  • SAP Strategic Enterprise Management (SEM)
  • SAP Test Data Migration Server (TDMS)
  • SAP Training and Event Management (TEM)
  • SAP NetWeaver Application Server (Web AS)
  • SAP xApps
  • SAP Supply Chain Performance Management (SCPM)
  • SAP Supply Chain Management (SCM)
  • SAP Sustainability Performance Management (SUPM)

SAP Industry Solutions

  • SAP for Retail
  • SAP for Utilities (ISU)
  • SAP for Public Sector (IS PSCD)
  • SAP for Oil & Gas (IS Oil & Gas)
  • SAP for Telecommunications (IST)
  • SAP for Healthcare (ISH)
  • SAP for Banking (SAP for banking)
  • SAP for Insurance (SAP for Insurance)
  • SAP Financial Services Network (FSN)
  • SAP Shipping Services Network (SSN)
  • Engineering Construction & Operations (EC&O)
  • SAP IS Airlines & Defense

SAP Partial List of Products

  • Customer Relationship Management (CRM)
  • Enterprise Resource Planning (ERP)
  • Product Lifecycle Management (PLM)
  • Supply Chain Management (SCM)
  • Supplier Relationship Management (SRM)

Big Data

Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences.

Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying and information privacy. The term often refers simply to the use of predictive analytics or certain other advanced methods to extract value from data, and seldom to a particular size of data set. Accuracy in big data may lead to more confident decision making, and better decisions can result in greater operational efficiency, cost reduction and reduced risk.

Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.

Data Science

Data science is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, data mining, and predictive analytics, similar to Knowledge Discovery in Databases (KDD).

Data science employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science, including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition and learning, visualization, predictive analytics, uncertainty modeling, data warehousing, data compression, computer programming, artificial intelligence, and high performance computing. Methods that scale to big data are of particular interest in data science, although the discipline is not generally considered to be restricted to such big data, and big data solutions are often focused on organizing and preprocessing the data instead of analysis. The development of machine learning has enhanced the growth and importance of data science.

Data scientists use their data and analytical ability to find and interpret rich data sources; manage large amounts of data despite hardware, software, and bandwidth constraints; merge data sources; ensure consistency of datasets; create visualizations to aid in understanding data; build mathematical models using the data; and present and communicate the data insights/findings. They are often expected to produce answers in days rather than months, work by exploratory analysis and rapid iteration, and to produce and present results with dashboards (displays of current values) rather than papers/reports, as statisticians normally do.


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