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SAP Analytics Cloud

SAP Analytics Cloud Training in Hyderabad

An example of a type of agile and robust analytic platform can be referred to as SAP Analytics Cloud. Multiple functions can be done using this SAP Analytics platform such as those connecting different databases present and the different sources of information that are present, integration of the different business applications that are present, etc. Different advantages can be experienced by organizations when SAP Analytics Cloud is being implemented. The first one is that it helps to facilitate collaborative planning and to make the decision-making process faster and more efficient information insights are being collected. Not only this, the communication process that is present is also being enhanced when SAP Analytics Cloud training is being implemented.

  • Faculty
    In any business making effective predictions is very important, and this can be done using this platform. Therefore in this course, guidance will be provided by the institute. The faculty that will be responsible for teaching this course is Murali. The job role of Murali is Sr. BI Solution Architect. The fields of specialization of Murali are Business Intelligence, Reporting, Data Visualization, and ETL. His previous job was in the organization, Accenture as the Tech lead for the post of H TO H Capability. He has also achieved multiple recognitions for the excellence and dedication with which he performs his job role.
    He has various technical skills present. The first technical skill present is Ms-Excel. In Ms-Excel he has knowledge about the V-lookup, regression, how to perform the F-test and the T-test, and also about ANOVA. Apart from this he also knows the various platforms and tools such as SAP BW, and programming languages such as Python, etc. He also has technical skills present in the field of reporting and analysis. He has knowledge about design studios, how to work with a dashboard, and the SAC. Besides this, he has numerous certifications present related to these technical skills. They are certified in SAP Analytics Cloud in Ameerpet, Google Analytics, and Google Ads. He has technical skills present in various competencies such as Data Visualization, time management, etc.
  • Applications PF SAP Analytics Cloud
    In this application of Best SAP Analytics Cloud in Hyderabad, the course syllabus needs to be understood first. Ten units are present in this course. The first unit is about overview and positioning. In this unit, the overview of the SAP Analytics Cloud architecture can be well understood. Not only that there will be a comparison present between SAC and other kinds of Business Intelligence tools that are present. Another comparison that will be taught in this unit is between clouds vs. on-premise vs. hybrid.
    The advantages that SAC offers are also taught in this unit. In the next unit, the different kinds of connections are being taught. In this unit, it is also being taught how flat file data, cloud applications, and cloud databases can be connected and accessed. In the third unit, modeling is being taught. In this unit, a description of the model, its elements, and how operations are carried out with variables, transformations, and geo-dimension is being carried out all are taught in this modeling unit. The fourth unit is about Business Intelligence, fifth is about augmented analytics in which smart search, smart discovery, and smart insights are being taught.
    The rest of the units include Analytics designing, predictive scenario, administration, roadmap, certification for SAC, and lastly SAC planning. Different questions are frequently being asked such as who is eligible for learning the Best SAP Analytics Cloud course in Hyderabad, the different SAP Consultants present, the prerequisites for learning this course, etc. In the sixth unit which is about the analytics designer, an overview of the analytics designer will be taught. Not only that a comparison will be taught between what is the design mode, what is the run mode, and what is the view mode.
    One of the major things that will be taught in this unit is how a basic analytic application will be designed will be taught in this unit. In unit 7, the different predictive models present and their implementations are discussed. Apart from that how datasets and variables are used for working are also being discussed in this unit. Also, questions are often being asked about the latest certification code that is being used in SAC.
  • Course Syllabus

      UNIT-1: Overview & Positioning

      • SAP Analytics Cloud Architecture Overview
      • SAC vs other BI tools
      • Benefits & core functionalities of SAC
      • Cloud vs On-Premise vs Hybrid
      • SAP Analytic Cloud Client tools and Importance

      UNIT-2: Connections

      • Overview of Connections
      • Live Connections
      • Import Connections
      • Connecting and accessing Flat file data
      • Connecting and accessing Cloud applications
      • Connecting and accessing Cloud databases
      • Connecting and accessing SAP-HANA
      • Connecting and accessing Odata services

      UNIT-3: Modelling

      • What is MODEL
      • Components of MODEL
      • Working with Dimension and Classification
      • Configuring Geo-Dimension
      • Working with Measures
      • Working with Transformations
      • Working with Variables
      • Data Blending

      UNIT-4: Business Intelligence

      • Desinging SAC Stories
      • Working with Custom Templates
      • Working with Standard Templates
      • Working with Canvas-Responsive & Grid modes
      • Working with Designer(Builder panel , Styling Panel)
      • Filters in SAC
      • Query level filters
      • Story level filters
      • Page level filters
      • Widget level filters
      • Advanced Filters
      • Linked Analysis
      • Hyperlinking
      • Conditional Formatting
      • Customizing Measures
      • Customizing Dimensions
      • Data blending
      • Working with Chart widget
      • Working with Table widget
      • Working with Geo Map widget
      • R language basics
      • Generating R based Stories

      UNIT-5: Augmented Analytics

      • What is Augmented Analytics
      • Smart Search
      • Smart Discovery
      • Smart Insights

      UNIT-6: Analytics Designer

      • What is SAP Analytics Designer
      • Difference between SAC Stories vs SAP Analytics Designer
      • Analytics Designer overview and walkthrough
      • Outline,Designer,Error & reference panels
      • Design mode vs Run mode vs View mode
      • Desingning basic Analytic application
      • working with Container widgets
      • Implementing filters
      • working with Drop-down,Radibutton,Checkbox componets
      • working with script variables
      • working with script objects
      • Configuring and implementing Dynamic Visibility
      • Working with Loop functions and Conditional Statements
      • Implementing Hyperlinking and Explorer option

      UNIT-7: Predictive Scenario

      • Predictive scenario overview
      • SAC Stories vs SAC Applications vs SAC Predictive
      • Working with Datasets,Variables
      • Implementing Classification Precitive Model
      • Implementing Regression Predictive Model
      • Implementing Timeseries Predictive Model
      • Generating predictive stories

      UNIT-8: Administration

      • SAC Architecture Overview
      • Working with Roles(Standard vs Custom)
      • Defining Team(s)
      • Defining User(s)
      • Working with dataloading and scheduling
      • SAP Cloud connector
      • SAP Analyics Cloud Agent
      • SAC Lifecycle management/Transports

      UNIT-9: SAC Roadmap & Certification

      • SAC Roadmaps(Current vs Future)
      • SAC Project Implementation landscapes
      • SAC Certification Overview
      • ECC/BW/BO/S4-HANA/HANA-> SAC Migration Strategy

      UNIT-10: SAC Planning

      • SAC Planning Overview
      • Building a Planning model
      • Currency Table Configuration
      • Working with Value Driver Tree
      • Working with Data actions
      • Working with Data actions
      • Configuring allocations
      • Working with Distributions
      • Predictive forecasting implementation
      • Generating Stories using planning models
      • Generating analytic applications using planning models
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