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HANA Overview:

HANA is SAP’s in-memory appliance and is designed to process high volumes of transactional data without affecting the performance of operational systems. Organizations can synchronize key transactional tables into memory in near real-time, making these tables easily accessible for analysis and lookup. Once data is available in memory, departments can instantly look up individual line items from massive lists like booking documents, sales leads, or service records. SAP HANA provides a streamlined workflow from ideas to analysis. The workflow covers the entire process, starting from the identification of relevant operational data, turning raw data into relevant information, generation of semantically grouped information in models, and finally the publishing of the completed models.

HANA Key Differentiators
The key differentiators that sets SAP HANA apart from traditional analytic models is the absence of any materialization. All models are purely virtual and results are calculated based on the underlying detailed operational data. The absence of materialization makes model changes very easy.

Standard Interfaces
SAP HANA provides standard interfaces to existing applications, operational systems, or other business applications. This means that SAP HANA will not disrupt existing landscapes by connecting to existing data sources and easily leverage investment in existing BI clients.

Real-Time Transactional Data
SAP HANA can connect to real-time transactional data coming directly from an organization’s SAP Business Suite or data can be batch loaded from sources such as the SAP NetWeaver BW and / or non-SAP operational data can be loaded using the SAP Business Objects Data Services component.

Real-Time Replication
SAP HANA offers real-time replication services to replicate data from SAP and non-SAP systems into HANA, as well as data integration tools to allow batch replication of data from any SAP or non-SAP source.

Data Modelling
SAP HANA includes tools for data modeling, data and lifecycle management, and security. The SAP HANA modeling studio enables businesses to organize and manage data, leveraging compression and column-store techniques to allow analysis of tens of terabits of data in main memory. Data can even be partitioned to allow processing and calculation on-the-fly using multi-core processors.

SAP Business Objects BI Tools
With SAP HANA, you can establish connections with SAP Business Objects BI tools and directly leverage SAP HANA’s in-memory data, giving business users a complete range of insight and analysis capabilities for all high-performance applications. However, if users prefer to employ Excel or other tools and applications for insight and analysis, they can connect to SAP HANA through standard interfaces such as MDX or SQL.

What is big data?

Big data related to size of data at large, compute and process the data in real time fashion. Contains data sets(information from various tables) to manage, process the data.

 

What is OLTP and OLAP?

  1. OLTP (On-line Transaction Processing)– data modeling technique to handle daily business. Relatively its very fast way to process data.

Example:- grocery shopping at Walmart.

  1. OLAP (On-line Analytical Processing)-  is the process of analyzing the data. Used for management information system and decision support system. It helps the business to compute, process, and take a effective decision.

Example:- Clearance sales comparison (month to month, year to year).

 

What is Parallel processing?

Dividing the program among multiple processors. Usually to save execution time.

 

What is data compression?

The process of reducing the size of a data.

 

What is In Memory computing and what other Data bases are in the industry?

Process of performing query operation on data in memory is called in-memory computing and faster than traditional systems. Follow is the list of DB support in-memory operations.

  1. Aerospike
  2. Apache Geode
  3. dashDB
  4. DB2 BLU
  5. EXASolution
  6. FuelDB

 

Write about HANA Architecture?

The SAP HANA database is developed in C++ and runs on SUSE Linux Server. SAP HANA database consists of multiple servers and the most important component is the Index Server and consists of the following.
Index Server:

Main component of DB and contains data stores, and engine for processing the data. Process the queries in authenticated session and transactions.

Persistence Layer:
Responsible for durability and atomicity of transactions. Make sure that data is committed and can be restore in case of disasters (example system failure).
Preprocessor Server:
The index server uses the preprocessor server for analyzing text data and extracting the information on which the text search capabilities are based.
Name Server:
The name server owns the information about system. In a distributed system, the name server knows location of components running and data located on which server.
Statistic Server:
The statistics server collects information about status, performance and resource consumption from the other servers in the system. Also maintains the history for statistics data.

Session and Transaction Manager:
Transaction manager keeps track of running and closed transactions. When a transaction is committed or rolled back, it’s the responsibility of transaction manager to inform the other processes about current event.

XS Engine:

Uses HTTP module (engine) to connect to HANA database.

 

What is Row Store and Column Store in HANA?

Row Storage – It stores table records in a sequence of rows. Oracle, SQL server, Teradata store data in row storage.

Column Storage – It stores table records in a sequence of columns i.e. the entries of a column is stored in contiguous memory locations.

What is Calculation View, analytical View and Attribute View?
Attribute View:

Attribute view(s) are dimensions or master data and can be joined with dimension table or another attribute view.

Example : Flight display board at Airport.

Analytic View:

Consists of fact table (master table) with various dimension tables. Fact table contains the transactional information. Easy to summarize (aggregate) the data from dimensions table.

Example:- think of a Grocery section at supermarket. We can say that ‘section’ is the fact table and veggies are the dimensions.

 

Calculation View:

Calculation views are composite views and can perform complex calculation on data. It can combine information(such as facts) from various table, attribute and analytical views into one large chunk.

 

What is XS Engine?

Uses HTTP module (engine) to connect to HANA database.

 

What is MDX query?

Multidimensional Expressions (MDX) is a query language for OLAP databases.

 

What is ETL and data transformation and what tools are available in the industry?

ETL stands for Extract, Tranform and Load. It’s a process in data warehousing responsible for pulling data from various source systems and placing it into centralized data warehouse.

Data transformation, processing the raw data from different sources and converting it into readable form store it in centralized place such as data warehouse. Follow are the commonly used tools.

  1. Oracle Warehouse Builder (OWB)
  2. SAP Data Services
  3. Informatica
  4. SSIS
  5. Cognos

 

What types are SQL joins are available?

Inner join

Left Outer join

Right outer join

Cartesian join

 

What is HANA studio?

Tool used to develop artifacts about data. It enables users to manage the create and manage user authorizations, to create new or modify existing models of data etc.

 

What is Predictive analytics?

Predictive analytics process of extracting information from existing data sets in order to determine future outcomes.

Example: comparing sales data basis on past year

 

What is Session management in HANA?

Once the users are authenticated and creates an active session with in the system. Session management responsible for current state of transaction and involves in committing data. We can say that session management make sure that current statement executes during its allotted time.

Example: – Once the user logon to Facebook, it creates an active session during the stay of user. Whatever user post during this session will be committed.

 

What is Persistence management in HANA?

Responsible for durability and atomicity of transactions. Make sure that data is committed and can be restore in case of disasters (example system failure).
How many Engines are available in HANA DB?

  1. Join Engine:- Used when querying an Attribute View
  2. OLAP Engine:- Analytic Views (without derived columns) use the OLAP Engine
  3. Calculation Engine:- Calculation Views or Analytic Views with derived columns use this engine

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