SAP Hana Modeling

Sap Hana Modeling

SAP HANA Modeling is an activity by which we create information view. Information View is similar to dimension, cube or information provider of BW. This information view is used for creating the multi-dimensional data model.

SAP HANA Modeling Overview

Modelling is an activity in which user refine or slice data in the database table by creating information view based on the business scenario. This information views can be used for reporting and decision-making purpose.Information view is made from various combinations of content data to create a model for a business scenario.

Modeling SAP HANA Information Views are important for successfully exploiting the power of SAP HANA. These views are classified as

•       Attribute Views
•       Analytic Views
•       Calculation Views

Attribute View:

•     Attribute views are dimensions, BW characteristics or master data.
•     Attribute views are used to join to a dimension or attribute view.
•     In most cases used to model master data like entities (like Product, Employee, Business Partner)
•     Highly re-used and shared in Analytic- and Calculation Views

Analytic View:

• Analytic views are star schemas or fact tables surrounded by dimensions, calculations or restricted measures.
• In the language on SAP BW analytical views can be roughly compared with Info Cubes or Info Sets.
• Analytic views are typically defined on at least one fact table that contains transactional data along with number of tables or attribute views.
• Analytic views leverage the computing power of SAP HANA to calculate aggregate data, e. g., the number of bikes sold per country, or the maximum power consumed per month.
• It is specifically designed to execute star schema queries

Calculation View:

• Calculation views are composite views used on top of analytical and attribute views.
• It can perform complex calculations not possible with other views.
• It can be defined as either graphical views or scripted views depending on how they are created. Graphical views can be modeled using the graphical modeling features of the SAP HANA Modeler. Scripted views are created as sequences of SQL statements.
• Calculation views can be referred as combination of tables, attributes views and analytical views to deliver a complex business requirement. They offer to combine different analytical views into one source of data for reporting.

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SAP HANA Architecture

Welcome to this foundation tutorial explaining the SAP HANA Architecture in detail. Here, we will understand the different components that make up the SAP HANA appliance.

SAP HANA Architecture in blocks

SAP HANA is not just a database – it’s an appliance which consists of different servers. Index server is the primary component but it consists of other different servers as well. Let’s understand what each of these servers are responsible for.

Index Server 

It is the prime server of SAP HANA that contains actual data and processing engines. This server processes the SQL and MDX statements when authentication and transactions are required.

Persistence Layer 

 This layer maintains atomicity and durability of transactions. It is accountable to make sure that the database is able to be restored to the recent state and transactions are properly executed or not left in the middle.

Preprocessor Server 

This server analyzes text data and extracts information with the help of Preprocessors.

Name Server 

This server maintains the detailed information about the system topology. It keeps the updates about all the components and their location.

Statistic Server 

This server maintains log of other servers and their details such as status, performance, allocation/consumption of resources, etc. This data is used to keep track of the clients and alert monitors.

Session and Transaction Manager 

This server monitors the database transactions and their execution. When a transaction is committed or rolled back, Transaction manager informs the storage engines to take necessary measures.

XS Engine 

This server facilitates communication between external applications and SAP HANA system via HTTP in a web browser.
For SAP ERP Training or SAP  HANA Architecture Module Training please visit the links.

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Sap Hana Course Outline

Sap Hana Course Outline

Introduction

SAP HANA [High-Performance Analytic Appliance] is an in-memory data platform that is deployable as an on-premise appliance, or in the cloud.  It is a revolutionary platform that’s the best suited for performing a real-time analytics, developing and deploying real-time applications. At the core of this real-time data platform is the SAPHANA database which is fundamentally different than any other database engine in the market today (figure) SAP HANA Training

Whenever companies have to go deep within their data sets to ask interactive questions, and have to go broad (which means working with big data sets that are of different types and from different sources) at the same time, SAP HANA is well-suited. Increasingly there is a need for this data to be recent and preferably in real-time. Add to that the need for high speed (very fast response time and true interactivity) and the need to do all this without any pre-fabrication (no data preparation, no pre-aggregates, no-tuning) and you have a unique combination of requirements that only SAP HANA can address effectively. So we can say SAP HANA is thePlatform for Next-Generation Applications and Analytics.

Content

HANA 100 & HANA 300 Course Content:

SAP HANA 100 Certification Syllabus

Introduction

• Introduction to SAP HANA
• SAP HANA In-Memory Strategy
• HANA Compared to BWA

Look and feel

• In memory Computing Studio
• Administration views
• Navigator View
• System View
• Information Modeler
• -Architecture
• Architecture Overview
• IMCE and surroundings
• Row Store
• Column Store
• Loading data into HANA
• Data Modelling
• Reporting
• Persistent Layer
• Back & Recovery

Data Provisioning

• Replication Server
• Replication process
• Replication Architecture
• Data services
• SAP BODS and HANA.
• Basic Data service connection types
• New to Data Services 4.0
• Full Extractor through ODP.
• Configure Import server
• Create and execute a Data service job to populate HANA.

Modelling

• Purpose of information Modeler.
• Levels of modelling in SAP HANA.
• Attribute Views
• Calculation Views
• Export & Import

Reporting

• HANA Reporting Layer.
• Connectivity options.
• Business Objects BI 4.0
• Business Objects BI 4.0 Explorer
• Business Objects BI 4.0 Enterprise
• Crystal reports via ODBC/JDBC Connections
• Others & MS Excel

User Management

• Creation of Users
• Creation of Roles
• Creation of Role Hierarchy
• Assignment of users to roles
• Authentications
• IMCE Authorizations

SAP HANA 300 Certification Syllabus

DATA PROVISIONING USING SLT

• Positioning and key concepts
• Overview on configuration Aspects
• Data Replication at a glance.
• SLT based transformation concepts.
• Selective Data Replication.
• Transformation of Data.
• Extension of (target) table structure.
• Specific Considerations.

Approaching SAP HANA Modeling

• Persistency Considerations
• SAP HANA Engine Overview
• Choosing views for the information Model.

Connecting Tables

• How to connect tables Using:
• Inner Join
• Left Outer Join
• Right Outer Join
• Full Outer Join
• Text Outer Join
• Referential Join
• Union

Advanced Modelling

• Creating Attribute Views.
• Using Hierarchies.
• Creating Restricted & calculated Measures.
• Using Filter Operations
• Using Variables
• SAP HANA SQL – Introduction.
• SQL Script and Procedures
• Using Currency Conversion.

Processing Information Models

• Validating Models
• Comparing Versions of Information Objects
• Checking Model References
• Generating: Auto Documentation.

Managing Modelling Concepts

• Schemas
• Import & Export
• Copying Objects

Security and Authorizations

• User Management & Security
• Types of Privileges
• Template Roles
• Administrative

For SAP ERP Training or SAP  HANA Module Training please visit the links.

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SAP HANA

SAP HANA                                     

Sap Hana is a modern, in memory database and platform that is deployable on premise or in the cloud.

The sap Hana platformis a flexible data source agnostic in memory data platform that allows customers to analyse large volumes of data in real time.it is also a development platform, providing an infrastructure and tools for building high performance application based on sap Hana extended application services (SAP HANA XS). It is the foundation of various SAP HANA editions, like the SAP HANA platform edition, providing core database technology. And the sap Hana enterprise edition, bundling additional components for data provisioning. Thesap Hana platform edition integrates a number of sap components including sap Hana database, SAP Hana studio and SAP Hana clients.

Overview

SAP HANA is acombination of HANA Database, Data Modelling, HANA Administration and Data Provisioning in one single suite. In SAP HANA, HANA stands for High-Performance Analytic Appliance. According to former SAP executive, Dr. Vishal Sikka, HANA stands for Hasso’s New Architecture. HANA developed interest by mid-2011 and various fortune 500 companies started considering it as an option to maintain Business Warehouse needs after that.

Need for SAP HANA

Today, most successful companies respond quickly to market changes and new

Opportunities. A key to this is the effective and efficient use of data and information by

Analyst and managers.

·         HANA overcomes the limitations mentioned below:

·     Due to increase in “Data Volume”, it is a challenge for the companies to provide access to real time     data for analysis and business use.

·        It involves high maintenance cost for IT companies to store and maintain large data volumes.

·            Due to unavailability of real time data, analysis and processing results are delayed.

Features of In-Memory Database

The main features of SAP HANA in-memory database are:

SAP HANA is Hybrid In-memory database.

· It combines row based, column based and Object Oriented base technology.

· It uses parallel processing with multicore CPU Architecture.

· Conventional Database reads memory data in 5 milliseconds. SAP HANA In-Memory database reads data in 5 nanoseconds.

Advantages of In-Memory Database

· HANA database takes advantage of in-memory processing to deliver the fastest data retrieval speeds, which is enticing to companies struggling with high-scale online transactions or timely forecasting and planning.

· Disk-based storage is still the enterprise standard and price of RAM has been declining steadily, so memory-intensive architectures will eventually replace slow, mechanical spinning disks and will lower the cost of data storage.

· In-Memory Column-based storage provides data compression up to 11 times, thus, reducing the storage space of huge data.

· This speed advantages offered by RAM storage system are further enhanced by the use of multi-core CPUs, multiple CPUs per node and multiple nodes per server in a distributed environment.

Access the data you need in real time – with SAP HANA in-memory database services

At the core, SAP HANA is a relational database management system (RDBMS). It combines OLAP and OLTP processing into a single in-memory database – eliminating disk bottlenecks and offering ground-breaking performance. This ACID-compliant, in-memory columnar database stores compressed data, offers parallel processing across multiprocessor cores, and supports single instruction multiple data (SIMD) commands.

SAP HANA Vendors

The few vendor includes

· IBM

· Dell

· HP

· Cisco

· Fujitsu

· Lenovo (China)

· NEC
· Huawei

SAP HANA Modelling

SAP HANA Modeller option is used to create Information views on the top of schemas-> tables in HANA database. These views are consumed by JAVA/HTML based applications or SAP Applications like SAP Lumia, Office Analysis or third party software like MS Excel for reporting purpose to meet business logic and to perform analysis and extract information.

HANA Modelling is done on the top of tables available in Catalog tab under Schema in HANA studio and all views are saved under Content table under Package. You can create new Package under Content tab in HANA studio using right click on Content and New. All Modelling Views created inside one package comes under the same package in HANA studio and categorized according to View Type. Each View has different structure for Dimension and Fact tables. Dim tables are defined with master data and Fact table has Primary Key for dimension tables and measures like Number of Unit sold, Average delay time, Total Price, etc.

SCHEMA IN DATA WAREHOUSE

Schemas are logical description of tables in Data Warehouse. Schemas are created by joining multiple fact and Dimension tables to meet some business logic. Database uses relational model to store data. However, Data Warehouse use Schemas that join dimensions and fact tables to meet business logic. There are three types of Schemas used in a Data Warehouse:

· Star Schema

· Snowflakes Schema

· Galaxy Schema

Star Schema

In Star Schema, Each Dimension is joined to one single Fact table. Each Dimension is represented by only one dimension and is not further normalized. Dimension Table contains set of attribute that are used to analyse the data.

EXAMPLE.

Snowflakes Schema

In Snowflakes schema, some of Dimension tables are further, normalized and Dim tables are connected to single Fact Table. Normalization is used to organize attributes and tables of database to minimize the data redundancy. Normalization involves breaking a table into less redundant smaller tables without losing any information and smaller tables are joined to Dimension table.

Galaxy Schema

In Galaxy Schema, there are multiple Fact tables and Dimension tables. Each Fact table stores primary keys of few Dimension tables and measures/facts to do analysis.

For more details about sap erp training and sap HANA training please visit : www.asipt.net/sap-erp-training

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