Training for the Future

SAP Analytics Cloud for Business Intelligence

Course Code: SACBI

Dates: 22 Apr - 26 Apr | 8 Jul - 12 Jul | 2 Sep - 6 Sep | 25 Nov - 29 Nov

Price: £2950 Plus VAT

Duration: 1 Week /s

Course Objectives
SAP Analytics Cloud for Business Intelligence tool is a streamlined end-to-end Analytics An integrated SAP solution A single solution for business intelligence and organizational planning, enhanced with the power of predictive analytics and machine learning technology. Automatically discover the main business drivers behind your core KPIs. Reveal hidden insights and develop a clear understanding of your business data. Enhance your data quickly with intuitive suggestions during data preparation and automation of repetitive workflows.

Who Should Attend
For business analysts, Business Managers, and IT Staff.
Pre-Requisites: Before attending this course, delegates must have:
  • Some basic knowledge of data warehouse schema topology (including star and snowflake schemas). Some exposure to basic programming constructs (such as looping and branching)

  • Familiarity with Microsoft Office applications particularly Excel/Sheets

  • Course Overview
  • Overview of SAP Analytics Cloud for Business Intelligence and business performance

  • Solution overview; Architecture; Position in SAP portfolio
  • Story definitions and possibilities; charts, KPIs. Data Access control. Geospatial analysis

  • Overview of data acquisition, data modelling, and security
    Integration options in Business Content for Oil & GAS

  • General assessment of financial performance based on P&L, investments, and account positions

  • Benchmark direct production costs per cost category per barrel of crude for all districts, fields, or wells. Simulate changes of the direct production costs per barrel to meet demanding efficiency targets.

  • Assessment of the product portfolio performance of downstream and chemical business units with respect to contribution margin by markets, regions, and customer segments

  • Comparison of the refineries economics based on the difference of the cost of the raw materials and value of the petroleum products produced to improve e.g. decisions on matching supply/demand or investments

  • Improve decisions on the current portfolio of capital and STO (Shutdowns, Turnarounds, and Outages) projects based on budgets, costs, commercial value, risks and ROI including analysis of budget deviations

  • Monitor how well e.g. the oil platforms, fields, terminals and refineries reach the companies greenhouse gas emission reduction target

  • Report on status on incidents, near misses and safety observations including root causes

  • Overview of the Microsoft R ecosystem. Functional programming for data manipulation. Data visualization and exploratory data analysis. Installing R studio and setting up R in SAP Analytics. Understanding main data structures in R such as Data frame, Vector and List.
    Exploring and Understanding Data in R (summary, str, head, tail, so forth).

  • Smart Discovery & Simulation. Time-series forecasting. R visualisations & algorithm

  • Course Materials
    Notes and Handouts

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