🎓 Enroll Today & Start Learning from Industry Experts
4.9 Rating
SAP Analytics Cloud (SAC) Course
Learn SAP Analytics Cloud with hands-on training in dashboards, reporting, planning, and data visualization. Gain practical skills and real-world experience to become job-ready in business analytics and data-driven decision-making
Hands-on AI projects with industry-oriented training
Career-focused guidance with certification and placement support
Live Training
Instructor-led Online Training
Interactive live classes with expert trainers, practical learning,
LMS access, and cloud labs.
Live mentor sessions
Dedicated lab access
Weekend batches
Most popular
Self Paced
Recorded Video Training
Learn anytime with premium recorded sessions, downloadable study materials, and flexible access.
Unlimited recordings
LMS access included
Flexible learning
Flexible Access
Enterprise
Corporate Training
Team-oriented learning solutions with LMS integration, reporting, and enterprise support.
Team learning
Progress tracking
Dedicated support
Business Ready
KASHA TRAINING
About The Course
SAP Analytics Cloud (SAC) is SAP’s cloud-based analytic product that brings together business intelligence (BI), planning, and predictive analytics into a single application. It is a Software-as-a-Service (SaaS) product and the center of gravity in SAP’s cloud stack, making it easy for users to analyze data, plan, and predict — all in one interface.
SAC brings together the analysis, planning, forecasting, and visualization of data in one tool. It combines a world-class BI system with business planning, including the use of artificial intelligence and machine-learning technologies. A brief history: SAP began its journey toward integrated analytics in 2015 when it released SAP Cloud for Planning. It quickly evolved to include data visualization functionality and was renamed SAP BusinessObjects Cloud. By 2017, SAP had combined Planning, BI, and Predictive Analytics into one unified platform — SAP Analytics Cloud. Since then, SAC has continued to grow with advanced AI and Machine Learning capabilities.
Watch Preview
Benefits of Attending SAP Analytics Cloud (SAC) Training
- Enhanced Career Opportunities in BI & Analytics — Passing the SAC certification exam successfully helps professionals enhance their career opportunities in the field of Business Intelligence and Data Analysis, and ensures they have the necessary knowledge and skills to use SAP Analytics Cloud effectively in the workplace.
- High & Growing Demand in India & Globally — As more organizations transition from legacy SAP BI tools to the cloud, the demand for certified SAC Consultants, Business Analysts, and Data Scientists with proven SAC skills is consistently high in tech hubs like Bangalore, Pune, and Hyderabad, offering a significant competitive advantage in the job market.
- Master All 4 Pillars of SAC — Training covers all four pillars of SAC — BI Stories, Planning, Predictive Analytics, and Analytic Designer — along with integration with live data systems and databases, user and authorization management, and all three types of predictive models: Regression, Classification, and Time Series.
- No-Code Analytics Skills for Business Users — For basic usage, SAC is largely code-free and relies on intuitive interfaces, making it accessible to finance teams for budgeting and forecasting, as well as marketing and sales teams for understanding customer behavior and improving strategies.
- Future-Proof, AI-Ready Analytical Expertise — From modeling and planning to predictive analytics and collaboration, each SAC feature unlocks new possibilities, and for those ready to invest in their growth, the rewards are substantial — better roles, higher impact, and a future-proof career in the data-driven world.
- Cross-Functional Industry Applicability — SAC is accessible and valuable for C-suite executives looking for real-time performance dashboards, financial analysts working on forecasts and budgets, and operations and sales teams tracking KPIs and productivity — making trained professionals useful across all business functions.
- Strategic Planning & Forecasting Proficiency — Training provides a comprehensive understanding of SAC’s powerful planning and budgeting capabilities, including how to create strategic plans, utilize predictive forecasting, and leverage real-time data modeling for smarter decision-making and better business performance.
- Hands-On, Real-Time Practical Experience — SAC Planning training offers hands-on experience in financial planning, data integration, and collaborative planning, and is ideal for finance professionals, data analysts, business planners, and anyone looking to improve their planning and budgeting capabilities within the SAP environment.
- Joule AI Assistant & Smart Feature Mastery — Professionals who complete SAC training are expected to leverage Smart Assist features including Smart Discovery, Smart Predict, Smart Insights, and Search to Insight — skills that are critical as SAC evolves into a fully AI-powered analytics platform
SAP Analytics Cloud (SAC) Key Features
- Unified BI, Planning & Predictive Platform — One of the biggest advantages of SAP Analytics Cloud is its unified architecture — it combines multiple analytical disciplines including BI, planning, predictive analytics, and augmented analytics into a single cloud environment, eliminating data silos, reducing IT overhead, and streamlining workflows across departments.
- Interactive Stories & Data Visualization — SAC includes self-service reporting tools that allow users to build rich, interactive data stories with charts, tables, maps, and dashboards, providing a comprehensive and intuitive platform for business intelligence reporting and data-driven decision-making.
- Integrated Planning & Budgeting — SAC provides an all-in-one ecosystem for financial and operational planning capabilities — companies can conduct what-if simulations, create versions of a budget, and perform rolling forecasts that connect strategy and execution in a single unified environment.
- Augmented Analytics (AI & Machine Learning) — Augmented Analytics in SAP Analytics Cloud enhances decision-making by embedding AI and machine learning directly into the analytics experience, automating complex data preparation, insight discovery, and predictive modeling, making advanced analytics accessible to all business users — not just data scientists.
- Smart Discovery — Smart Discovery uncovers hidden insights quickly by analyzing data and highlighting key patterns, automatically generating an overview report that identifies key influencers and outliers in a dataset, simplifying the data exploration process and saving time for business users.
- Smart Predict — Smart Predict builds and applies predictive models — including Classification, Regression, and Time Series — to forecast outcomes and identify key influencers, allowing business users to create predictive models without extensive data science expertise.
- Search to Insight (Natural Language Query) — Data questions can be asked in natural language, and SAC provides instant visual answers. Using Natural Language Processing (NLP), Search to Insight converts user queries into charts or tables automatically, making analytics accessible to every level of the organization.
- Collaborative Planning & Workflow — SAC includes collaborative features and process automation capabilities that enable multiple users to participate in planning, budgeting, and forecasting workflows simultaneously, ensuring alignment across teams and departments.
- Real-Time Data Connectivity — SAC offers real-time access to business data, aiding organizations in making decisions based on current information, and can be integrated with SAP S/4HANA or third-party systems for live data connections.
- SAP Joule AI Assistant Integration — SAP Joule serves as a personal AI assistant throughout the analytics journey — instead of manually navigating through various tools like Smart Discovery, Predictive Planning, or Search to Insight, Joule selects the most suitable AI feature based on the questions users ask, further simplifying the analytics experience.
- Multi-Source Data Integration — SAC synchronizes data from across an entire infrastructure using a single cloud platform built on top of the SAP HANA in-memory database, enabling organizations to budget, plan, forecast, and run consolidations with predictive analytics across SAP and non-SAP data sources.
- Analytic Designer (Custom Applications) — The Analytic Designer in SAC allows developers and power users to build customized analytic applications with advanced interactivity, scripting, and tailored user experiences beyond standard story-based reporting, catering to complex enterprise reporting needs.
Our Programs
Course Curriculum
1. Introduction to SAP Analytics cloud(SAC)
Get started with Java architecture. Understand the fundamental differences between JDK, JRE, and JVM, set up your development environment with IntelliJ IDEA, and write your first compilation-ready Java application.
Java History, Features, and WORA Concept
Video · 0:00 - 25:00
Understanding JVM, JRE, and JDK Internals
Video · Starts at 1:40
Guide: Environment Setup & IntelliJ Configurations
Reading 15 min
Lab: Writing and Compiling Your First "Hello World"
Lab 45 min
Module 01 Assessment — Java Architecture
Quiz 15 min
2. SAC Data Connectivity and integration
Master Java data types, operators, and memory implications. Learn the critical rules of implicit/explicit type casting and how variables interact within memory blocks.
Primitive vs Non-Primitive Data Types
Video · 5 min
Java Operators: Arithmetic, Relational, Logical & Bitwise
Video · 5 min
Widening and Narrowing Type Casting
Video · 5 min
Lab: Building a Precision Currency Converter Layout
Lab 60 min
3. Data Modeling in SAC
Implement conditional execution and looping constructs. Understand structural loops, switch expressions, jump rules (break/continue), and scanner inputs.
Decision Making: If-Else Clusters & Nested Conditions
Video · 5 min
Enhanced Switch Statements (Java 14+ Features)
Video · 5 min
Loops: While, Do-While, and For loops compared
Video · 5 min
Lab: Multi-Tier Tax Computation Utility
Video · 5 min
4. Data Management and preparation
Implement conditional execution and looping constructs. Understand structural loops, switch expressions, jump rules (break/continue), and scanner inputs.
1D and 2D Arrays: Declaration, Memory allocation & Iteration
Video · 5 min
The String Class: Immutability & Heap Allocation Mechanics
Video · 5 min
StringBuilder vs StringBuffer for Dynamic Sequences
Video · 5 min
Lab: Implementing Substring Searching & Pattern Matchers
Lab 75 min
5. Story Design and Visualization
Transition from procedural programming to structured Classes and Objects. Write scalable architectures using encapsulation patterns, access modifiers, constructors, and parameter overloads.
Classes, Objects, and the Identity Paradigm
Video · 5 min
Constructor Chaining & the 'this' Keyword Contexts
Video · 5 min
Encapsulation: Access Modifiers & Data Hiding Structures
Video · 5 min
Project: Inventory Management System Core Console
Project 120 min
7.Advanced Reporting and Dashboards
Build robust runtime environments. Intercept processing disruptions via try-catch blocks, handle checked/unchecked branches safely, and deploy custom nested application exceptions.
The Throwable Hierarchy: Errors vs Exceptions
Video · 5 min
Handling Flows via try, catch, finally, and multi-catch
Video · 5 min
Throwing Exceptions: throws declarations vs throw states
Video · 5 min
Lab: Writing Try-With-Resources and Custom Exceptions
Project 120 min
8. Business intelligence and Analytics
Manipulate group entities cleanly using dynamic data configurations. Understand performance tradeoffs between List variants, Set operations, Map pairings, and sorting systems via Comparators.
Framework Anatomy: List Implementations (ArrayList vs LinkedList)
Video · 5 min
Set Implementations & Hashing Tables: HashSet vs TreeSet
Video · 5 min
Key-Value Structures: HashMap Buckets & LinkedHashMap Mechanics
Video · 5 min
Lab: Comparable vs Comparator Entity Custom Sorting
Project 120 min
9. Planning and Budgeting
Persist runtime variables straight to data streams. Manage Byte pipelines vs Character utilities, file adjustments via NIO, and object byte-stream flattenings via Serialization implementations.
Byte Streams (FileInputStream) vs Character Streams (FileReader)
Video · 5 min
Buffered Processing Operations for High Performance
Video · 5 min
Object Serialization Techniques and 'transient' Flags
Video · 5 min
Lab: Parsing Data Tables & Archiving Object Snapshots
Project 120 min
12
Modules
76
Lessons
42h
Total Duration
14
Coding Labs
4
Projects
Our Programs
Feedback from our Participants
I had a fantastic learning experience with this SAP Analytics Cloud course. The lessons were well-organized, and the instructor explained data modeling, storytelling, and planning features in a simple way. The practical assignments helped me apply what I learned immediately. I would definitely recommend this training to anyone interested in SAP analytics solutions.
Ankit Sharma
Our Programs
Frequently Asked Questions
Live Data Connections map queries directly to underlying systems (such as SAP S/4HANA or BW/4HANA) through a reverse proxy, rendering real-time business records without replicating data into the cloud. Import Data Connections physically replicate datasets into the SAC cloud tenant storage on a scheduled refresh configuration loop, unlocking access to advanced smart transformations.
Module 4 details robust dataset processing tools. You will implement Data Cleaning algorithms, cross-model Data Blending rules, custom calculated fields, and Smart Data Preparation to validate records and resolve quality conflicts before passing data blocks into dashboard layouts.
Yes, while we establish core foundational mechanics, we extensively cover modern additions like Java 8 Lambda Expressions, functional Stream APIs, Optional containers, and the enhanced switch statements introduced in newer releases (Java 14+).
Module 01 is entirely free for a preview configuration. For the full comprehensive enrollment structure, we provide a 7-day money-back guarantee if the learning framework does not fit your operational style.