System Monitor in HANA studio provides an overview of all your HANA system at a glance. From System Monitor, you can drill down into details of an individual system in Administration Editor. It tells about Data Disk, Log disk, Trace Disk, Alerts on resource usage with priority.

The following Information is available in System Monitor −

SAP HANA – Information Modeler

SAP HANA Information Modeler; also known as HANA Data Modeler is heart of HANA System. It enables to create modeling views at the top of database tables and implement business logic to create a meaningful report for analysis.

Features of Information Modeler

Provides multiple views of transactional data stored in physical tables of HANA database for analysis and business logic purpose.
Informational modeler only works for column based storage tables.
Information Modeling Views are consumed by Java or HTML based applications or SAP tools like SAP Lumira or Analysis Office for reporting purpose.
Also possible to use third party tools like MS Excel to connect to HANA and create reports.
SAP HANA Modeling Views exploit real power of SAP HANA.

There are three types of Information Views, defined as −

Attribute View
Analytic View
Calculation View

Row vs Column Store

SAP HANA Modeler Views can only be created on the top of Column based tables. Storing data in Column tables is not a new thing. Earlier it was assumed that storing data in Columnar based structure takes more memory size and not performance Optimized.

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With evolution of SAP HANA, HANA used column based data storage in Information views and presented the real benefits of columnar tables over Row based tables.

Column Store

In a Column store table, Data is stored vertically. So, similar data types come together as shown in the example above. It provides faster memory read and write operations with help of In-Memory Computing Engine.

In a conventional database, data is stored in Row based structure i.e. horizontally. SAP HANA stores data in both row and Column based structure. This provides Performance optimization, flexibility and data compression in HANA database.

Storing Data in Columnar based table has following benefits −

Data Compression
Faster read and write access to tables as compared to conventional Row based storage
Flexibility & parallel processing
Perform Aggregations and Calculations at higher speed

There are various methods and algorithms how data can be stored in Column based structure- Dictionary Compressed, Run Length Compressed and many more.

In Dictionary Compressed, cells are stored in form of numbers in tables and numeral cells are always performance optimized as compared to characters.

In Run length compressed, it saves the multiplier with cell value in numerical format and multiplier shows repetitive value in table.

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Functional Difference – Row vs Column Store

It is always advisable to use Column based storage, if SQL statement has to perform aggregate functions and calculations. Column based tables always perform better when running aggregate functions like Sum, Count, Max, Min.

Row based storage is preferred when output has to return complete row. The example given below makes it easy to understand.

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In the above example, while running an Aggregate function (Sum) in sales column with Where clause, it will only use Date and Sales column while running SQL query so if it is column based storage table then it will be performance optimized, faster as data is required only from two columns.

While running a simple Select query, full row has to be printed in output so it is advisable to store table as Row based in this scenario.

Information Modeling Views

Attribute View

Attributes are non-measurable elements in a database table. They represent master data and similar to characteristics of BW. Attribute Views are dimensions in a database or are used to join dimensions or other attribute views in modeling.

Important features are −

Attribute views are used in Analytic and Calculation views.
Attribute view represent master data.
Used to filter size of dimension tables in Analytic and Calculation View.

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Analytic View

Analytic Views use power of SAP HANA to perform calculations and aggregation functions on the tables in database. It has at least one fact table that has measures and primary keys of dimension tables and surrounded by dimension tables contain master data.

Important features are −

Analytic views are designed to perform Star schema queries.
Analytic views contain at least one fact table and multiple dimension tables with master data and perform calculations and aggregations
They are similar to Info Cubes and Info objects in SAP BW.
Analytic views can be created on top of Attribute views and Fact tables and performs calculations like number of units sold, total price, etc.

Calculation Views

Calculation Views are used on top of Analytic and Attribute views to perform complex calculations, which are not possible with Analytic Views. Calculation view is a combination of base column tables, Attribute views and Analytic views to provide business logic.

Important features are −

Calculation Views are defined either graphical using HANA Modeling feature or scripted in the SQL.
It is created to perform complex calculations, which are not possible with other views- Attribute and Analytic views of SAP HANA modeler.
One or more Attribute views and Analytic views are consumed with help of inbuilt functions like Projects, Union, Join, Rank in a Calculation View.

This Tecklearn ‘Information Modeler and System Monitor in SAP Hana’ blog helps you with commonly asked questions if you are looking out for a job in SAP Hana and SAP Domain. If you wish to learn SAP Hana and build a career in SAP domain, then check out our interactive, SAP HANA Training, that comes with 24*7 support to guide you throughout your learning period. Please find the link for course details:

https://www.tecklearn.com/course/sap-hana-training-certification/

SAP HANA Training

About the Course

SAP HANA is an in-memory computing application that is designed and developed to boost the business processes, deliver smart solutions, and simplify both hardware and software environments. Our Sap Hana Training course will help you understand and learn the fundamentals and will also felicitate on training hands-on for the better grasp on the course. Further, we have the highly qualified professionals who will train you about Sap Hana Studio, Modelling, Security features and its various other aspects. You will understand why SAP HANA is a fundamentally different database engine upon the completion of this SAP HANA course.

Why Should you take SAP HANA Training?

The average Sap Hana Consultant salary $165,750 per year or $85 per hour. (neuvoo.com).
SAP HANA is the highest growing technology; hence, there is no surprise in plenty of career opportunities in this field. Since it is one among the fastest-growing products in the history of SAP, it is considered by the industries as a ground-breaking key for in-memory databases.
SAP HANA currently has more than 6,500 customers globally.

What you will Learn in this Course?

Introduction to SAP HANA

Fundamentals of SAP HANA
Capabilities of SAP HANA
Limitations of SAP HANA

Key Features of SAP HANA

Key Features: High Performance functionalities In-Memory computing, Columnar store database, Data Compression and Massive Parallel Processing
Using SAP HANA for Non-SAP Applications

Architecture of SAP HANA

Detailed Architecture of SAP HANA Database
Concept of SAP HANA Landscapes and Scenarios

Overview of HANA Studio

SAP HANA System – Perspectives, Administration, Modelling, Development Plan
HANA Database SQL Basics and Database SQL Script
Types of statements and data types
Operators, expressions and basic query execution
Sub-queries, Types of Joins, Expressions and Loops
Catalog – Schema, Table, Views, Functions, Stored Procedures, Index, Synonyms, Sequences, Triggers

Data Provisioning

Data Provisioning with Flat File upload
Provisioning – SDA (Smart Data Access)
Joins Types in HANA

SAP HANA Modelling

Types of Models
Attribute Views, Joins and Using Filter Operations
Creating Restricted and Calculated Columns
Using Hierarchies
Analytic Views – Star Schema design and Multi-Dimensional Modelling
Variables and Input parameters

Calculation Views

Dimension Calculation View
Information View
SAP HANA Variables
Introduction to Input Parameters

SAP Project

Using HANA analytical view building of COPA (Controlling and Profitability Analysis) model
SAP HANA COPA for evaluation of market segments and classification of markets according to the products, customers or any combination of it

Dimension Calculation View

Dimension Calculation View – Star Join Calculation view
Using Projection, Join, Aggregation, Union and Rank

In-depth Modelling

Refactoring information models
Schema Mapping
Propagate to schematics and Show Lineage
Schema Mapping
Generating Time Data
Union Pruning
Using Time Travel
Migrating deprecated Information models
Using Currency Conversion
Web based Modelling Work bench

Analytic Privileges and Decision Tables

Classical Analytic Privileges
SQL Analytic Privileges
Dynamic analytic Privileges.
Turning Business Rules into Decision tables
Table Functions

SAP HANA Table Function

Query Optimizing Technique related to SAP HANA Tables
Web Based Modelling work bench

SAP HANA on Cloud

SAP Analytics with SAP Reporting environment SAP BOBJ – tools, WEBI, LUMIRA, DASHBOARD (integration between sap Hana and bob)

Advanced Topics Overview

SAP HANA Dynamic tiering
Delta Merge
SDI (Smart Data Integration)
SDA (Smart Data Access)

DATA Provisioning

SLT – SAP Landscape Transformation
BODS – Business Objects Data Services

Analytical Privileges

Classical XML Based Analytical Privileges
SQL Analytical Privileges

HANA Administration and Security

Hana Administration
Security in SAP HANA – User Management

Got a question for us? Please mention it in the comments section and we will get back to you.

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