The document discusses monitoring tools available in the Computing Center Management System (CCMS). CCMS provides various monitors for monitoring SAP environments and components, which are useful for understanding system performance and diagnosing issues. Key monitoring tools in CCMS include the DBA Planning Calendar, Archive and Backup Monitor, Database Monitor, Alert Monitor, and Operating System Monitor. CCMS enables centralized monitoring of a system landscape from one system and helps ensure SAP installations are running efficiently.
This document provides an introduction to using R Studio for statistical analysis. It discusses how to install both R and R Studio on Windows and Mac systems. It then covers creating scripts and files in R Studio, basic R syntax including assigning values to variables, vectors, and strings. The document also demonstrates how to install and load packages to access additional functions, and how to access built-in datasets to practice working with data in R.
Column, line, pie, bar, area, and surface charts can all be created in Excel using data arranged in columns and rows on a worksheet. Column charts show comparisons over time, line charts show trends at intervals, pie charts show parts of a whole, bar charts compare individual items, area charts emphasize magnitude of change over time, and surface charts find optimum combinations between two data sets.
Data processing & Analysis: SPSS an overviewATHUL RAVI
This document provides an overview of SPSS (Statistical Package for Social Sciences), a software package used for statistical analysis. It discusses data processing and analysis, the basic steps in using SPSS which include getting data into SPSS, selecting an analysis procedure, running the procedure, and interpreting results. The SPSS interface is explained, showing how to enter variables and cases, import data from Excel, and conduct basic statistical analyses like frequency distributions and histograms.
The goal of this workshop is to introduce fundamental capabilities of R as a tool for performing data analysis. Here, we learn about the most comprehensive statistical analysis language R, to get a basic idea how to analyze real-word data, extract patterns from data and find causality.
This document provides instructions for using R software for agricultural data analysis. It discusses downloading and installing R, loading and exploring data, performing common analyses like ANOVA and correlations, and using specialized packages for tasks like AMMI analysis. The document recommends exploring R's capabilities and using reliable packages suited for agricultural research.
This document provides an overview and introduction to using the statistical software R. It outlines R's interface, workspace, help system, packages, input/output functions, and how to reuse results. It also discusses downloading and installing R, basic functions and syntax, data manipulation techniques like sorting and merging, creating graphs, and performing statistical analyses such as t-tests, regression, ANOVA, and multiple comparisons. The document recommends several tutorials that provide more in-depth information on using R for statistical modeling, data analysis, and graphics.
SPSS is a statistical software package used for data management and analysis. It can import data from various file formats, perform complex statistical analyses and generate reports, tables, and graphs. Some key features include an easy to use interface, robust statistical procedures, and the ability to work with different operating systems. While powerful and popular, SPSS is also expensive and less flexible than open-source alternatives like R for advanced or custom analyses.
The document discusses monitoring tools available in the Computing Center Management System (CCMS). CCMS provides various monitors for monitoring SAP environments and components, which are useful for understanding system performance and diagnosing issues. Key monitoring tools in CCMS include the DBA Planning Calendar, Archive and Backup Monitor, Database Monitor, Alert Monitor, and Operating System Monitor. CCMS enables centralized monitoring of a system landscape from one system and helps ensure SAP installations are running efficiently.
This document provides an introduction to using R Studio for statistical analysis. It discusses how to install both R and R Studio on Windows and Mac systems. It then covers creating scripts and files in R Studio, basic R syntax including assigning values to variables, vectors, and strings. The document also demonstrates how to install and load packages to access additional functions, and how to access built-in datasets to practice working with data in R.
Column, line, pie, bar, area, and surface charts can all be created in Excel using data arranged in columns and rows on a worksheet. Column charts show comparisons over time, line charts show trends at intervals, pie charts show parts of a whole, bar charts compare individual items, area charts emphasize magnitude of change over time, and surface charts find optimum combinations between two data sets.
Data processing & Analysis: SPSS an overviewATHUL RAVI
This document provides an overview of SPSS (Statistical Package for Social Sciences), a software package used for statistical analysis. It discusses data processing and analysis, the basic steps in using SPSS which include getting data into SPSS, selecting an analysis procedure, running the procedure, and interpreting results. The SPSS interface is explained, showing how to enter variables and cases, import data from Excel, and conduct basic statistical analyses like frequency distributions and histograms.
The goal of this workshop is to introduce fundamental capabilities of R as a tool for performing data analysis. Here, we learn about the most comprehensive statistical analysis language R, to get a basic idea how to analyze real-word data, extract patterns from data and find causality.
This document provides instructions for using R software for agricultural data analysis. It discusses downloading and installing R, loading and exploring data, performing common analyses like ANOVA and correlations, and using specialized packages for tasks like AMMI analysis. The document recommends exploring R's capabilities and using reliable packages suited for agricultural research.
This document provides an overview and introduction to using the statistical software R. It outlines R's interface, workspace, help system, packages, input/output functions, and how to reuse results. It also discusses downloading and installing R, basic functions and syntax, data manipulation techniques like sorting and merging, creating graphs, and performing statistical analyses such as t-tests, regression, ANOVA, and multiple comparisons. The document recommends several tutorials that provide more in-depth information on using R for statistical modeling, data analysis, and graphics.
SPSS is a statistical software package used for data management and analysis. It can import data from various file formats, perform complex statistical analyses and generate reports, tables, and graphs. Some key features include an easy to use interface, robust statistical procedures, and the ability to work with different operating systems. While powerful and popular, SPSS is also expensive and less flexible than open-source alternatives like R for advanced or custom analyses.
Uses & applications of microsoft excel in vph researchDr Alok Bharti
Microsoft Excel is a spreadsheet application that allows users to enter and organize data into columns and rows, perform calculations with formulas, and visualize data through graphs and charts. It consists of worksheets where data is entered into cells that are organized by columns and rows. Common functions include formatting cells, filtering and sorting data, and using formulas to analyze data through calculations and pivot tables to examine relationships between variables.
The document discusses charts and graphs used in business, including their components and purposes. It explains that charts visually represent spreadsheet data in a way that highlights trends and relationships. Charts contain elements like data series, titles, axes, labels, legends and more. Examples of using charts include representing sales trends, expenses, and stock prices. The document identifies key chart components and their functions.
The document discusses importing and exporting data in R. It describes how to import data from CSV, TXT, and Excel files using functions like read.table(), read.csv(), and read_excel(). It also describes how to export data to CSV, TXT, and Excel file formats using write functions. The document also demonstrates how to check the structure and dimensions of data, modify variable names, derive new variables, and recode categorical variables in R.
This document provides an overview of relational algebra operations. There are five basic relational algebra operators: select, project, union, intersection, and cartesian product. The select and project operators are unary operators that operate on a single relation. Select filters rows based on a predicate, while project extracts specified column values. Union and intersection are binary operators that combine two relations, union returning all rows and intersection returning matching rows. Cartesian product returns all possible combinations of rows from two relations. Relational algebra provides a way to formulate queries using these relational operators.
Software packages for statistical analysis - SPSSANAND BALAJI
This document provides an overview of the Statistical Package for Social Sciences (SPSS). It discusses what SPSS is, how to define and enter variables, and the four main windows in SPSS including the data editor, output viewer, syntax editor, and script window. Basic functions like frequencies analysis, descriptives, and linear regression are also introduced.
The R language is a project designed to create a free, open source language which can be used as a replacement for the S-PLUS language, originally developed as the S language at AT&T Bell Labs, and currently marketed by Insightful Corporation of Seattle, Washington. R is an open source implementation of S, and differs from S-plus largely in its command-line only format.
Topics Covered:
1.Introduction to R
2.Installing R
3.Why Learn R
4.The R Console
5.Basic Arithmetic and Objects
6.Program Example
7.Programming with Big Data in R
8.Big Data Strategies in R
9.Applications of R Programming
10.Companies Using R
11.What R is not so good at
12.Conclusion
This document discusses data provisioning in SAP HANA. It defines data provisioning as the process of creating, preparing, and enabling data to be provided to users. This includes extract, transform, and load (ETL) processes to move data from source systems into SAP HANA. It describes the built-in and external tools that can be used for data provisioning in SAP HANA, including SAP Landscape Transformation, SAP Business Objects Data Services, and SAP Direct Extractor Connection. Specific ETL tools like SAP Landscape Transformation and SAP Data Services are discussed in more detail regarding their features and how they can be used to replicate and transform source data for loading into SAP HANA
The document discusses how to size hardware configurations for SAP HANA landscapes using SAP's Quick Sizer tool. It describes the SAP HANA version of Quick Sizer, which was created specifically for sizing SAP HANA deployments. The tool calculates hardware sizing requirements based on key performance indicators and user-provided data on usage details. It then provides an example of using Quick Sizer to size an on-premise SAP S/4HANA deployment, including sizing the front-end and back-end servers.
The document provides information about SAP HANA, including what it is, its architecture, and development scenarios. SAP HANA is an in-memory database that can be deployed on-premise or in the cloud. It allows for real-time analysis of large data volumes. The architecture includes components like the index server, XS runtime, and name server. Development in SAP HANA involves using calculation views to define slices of data and Studio as an development environment. Time dimensions and graphical views can also be generated.
This document provides guidance on sizing an SAP LT Replication Server for SAP HANA landscape. It discusses factors that influence performance such as software versions, configuration, network factors, and data reading type. The document then presents assumptions, a template-based sizing approach, and sizing guidelines to estimate hardware requirements for the replication server. It also includes a section on comments and feedback.
1310 success stories_and_lessons_learned_implementing_sap_hana_solutionsBobby Shah
The document summarizes a session on implementing SAP HANA solutions. It provides an overview of SAP HANA, currently available solutions based on SAP HANA including SAP HANA standalone and SAP NetWeaver BW powered by SAP HANA. It also discusses tips and tricks for implementing SAP HANA standalone solutions, including data modeling vs analytic modeling and using SAP HANA analytic modeling and Data Services data modeling. Observations on implementing BW powered by SAP HANA are also presented along with examples of performance improvements customers have seen.
SAP HANA is an in-memory database platform that stores transactional data in memory for real-time analytics by eliminating disk input/output lag; it uses columnar storage with efficient compression and built-in indexing for each column to enable fast queries and joins; SAP HANA features include predictive analytics, multitenant containers, high availability, and tools for data modeling, administration, and development.
Whether MVC for user interfaces, or Spine and Leaf for data centers, new
architecture patterns in our industry act as sort of historical markers of the
effectiveness and acceptance of new technologies. Practical techniques push the
bounds resulting in a shift. Application of distributed storage and streaming
capabilities such as Kafka and of course Hadoop are shifting Big Data architectures
from a layer cake concept, or North/South oriented approach to one which can be
thought of as an East/West architectural concept. Recently popular is Lambda
Architecture, this article presents an SAP HANA based rendering of the Lambda
Architecture.
What is Sap HANA Convista Consulting Asia.pdfankeetkumar4
SAP HANA is the most recent, in-memory information base, and stage which can be sent on-premises or cloud. SAP HANA is a blend of equipment and programming, which coordinates various parts like SAP HANA Database, SAP SLT (System Landscape Transformation) Replication server, SAP HANA Direct Extractor association, and Sybase replication.
HANA has remarkable reception by the SAP clients. SAP HANA is equipped for handling a lot of constant information in a brief time frame period
SAP HANA Integrated Online Course Training in Hyderabad | Imagine LifeImagine life
Imaginelife Provides SAP HANA Integrated Online Classroom Training and E Learning Courses Providing Institution Specialized for IT Courses Learning Beginners, Learn SAP Cloud Integration and Business Processes Certification Programming, Training provided by Online Real Time Experts.
Projected cost analysis of the Sap Hana Platform Cost Savings Enabled By Tr...Abdulrahman Abdulrahim
The document summarizes a study conducted by Forrester Consulting on the projected cost savings from transitioning to SAP's HANA in-memory platform. It finds that a composite organization could save 37% in total costs of ownership over 3 years by moving its SAP BW, ERP, and a custom application to HANA. Key cost savings come from reduced hardware, software, and labor needs due to HANA's simplified data management and faster development times. Customers interviewed achieved significant data compression and increased efficiency in administration and development.
This document provides an overview and analysis of cost savings projected for a composite organization transitioning various applications, including SAP BW, SAP ERP, and a custom application, to the SAP HANA platform over three years. Interviews with existing SAP HANA customers informed the analysis. The analysis projects that the composite organization could save 37% of total costs over three years by reducing hardware, software, and labor costs through the simplified and automated environment of the SAP HANA platform. Key projected savings include 70% reduction in software costs, 15% reduction in hardware costs, and 20% reduction in administration and development labor costs.
This document provides an overview of SAP HANA, including its architecture and various use cases. It describes SAP HANA as an in-memory database that can be used as primary persistence for SAP NetWeaver applications, as a data mart for real-time analytics and reporting, and as a platform for building applications. It also discusses SAP HANA's technical deployment options, software components, and implementation considerations.
SAP HANA is an in-memory database platform that can be deployed on-premise or in the cloud. When deployed on-premise, SAP HANA combines software and hardware components optimized by SAP and its partners. In the cloud, SAP HANA is offered through managed services on infrastructure like SAP HANA One. To take advantage of SAP HANA's high-speed processing, developers can use Open SQL, core data services, and ABAP managed database procedures.
Please visit - www.mansur-pune.blogspot.com for SAP Training materials download .
https://drive.google.com/folderview?id=0B5mQZCJnlt6NSkFUTHhldm5wSVk&usp=sharing
Technical Overview of CDS View – SAP HANA Part IAshish Saxena
SAP HANA has introduced new paradigms to SAP ABAP application programming. Before SAP HANA, development paradigm in SAP was based on DATA-to-Code where intensive calculation was done at the application layer and database utilization was minimized. New programming paradigm in SAP HANA is Code-to-Data, where the intensive calculation is done at the database layer and less programming at application layer.
Uses & applications of microsoft excel in vph researchDr Alok Bharti
Microsoft Excel is a spreadsheet application that allows users to enter and organize data into columns and rows, perform calculations with formulas, and visualize data through graphs and charts. It consists of worksheets where data is entered into cells that are organized by columns and rows. Common functions include formatting cells, filtering and sorting data, and using formulas to analyze data through calculations and pivot tables to examine relationships between variables.
The document discusses charts and graphs used in business, including their components and purposes. It explains that charts visually represent spreadsheet data in a way that highlights trends and relationships. Charts contain elements like data series, titles, axes, labels, legends and more. Examples of using charts include representing sales trends, expenses, and stock prices. The document identifies key chart components and their functions.
The document discusses importing and exporting data in R. It describes how to import data from CSV, TXT, and Excel files using functions like read.table(), read.csv(), and read_excel(). It also describes how to export data to CSV, TXT, and Excel file formats using write functions. The document also demonstrates how to check the structure and dimensions of data, modify variable names, derive new variables, and recode categorical variables in R.
This document provides an overview of relational algebra operations. There are five basic relational algebra operators: select, project, union, intersection, and cartesian product. The select and project operators are unary operators that operate on a single relation. Select filters rows based on a predicate, while project extracts specified column values. Union and intersection are binary operators that combine two relations, union returning all rows and intersection returning matching rows. Cartesian product returns all possible combinations of rows from two relations. Relational algebra provides a way to formulate queries using these relational operators.
Software packages for statistical analysis - SPSSANAND BALAJI
This document provides an overview of the Statistical Package for Social Sciences (SPSS). It discusses what SPSS is, how to define and enter variables, and the four main windows in SPSS including the data editor, output viewer, syntax editor, and script window. Basic functions like frequencies analysis, descriptives, and linear regression are also introduced.
The R language is a project designed to create a free, open source language which can be used as a replacement for the S-PLUS language, originally developed as the S language at AT&T Bell Labs, and currently marketed by Insightful Corporation of Seattle, Washington. R is an open source implementation of S, and differs from S-plus largely in its command-line only format.
Topics Covered:
1.Introduction to R
2.Installing R
3.Why Learn R
4.The R Console
5.Basic Arithmetic and Objects
6.Program Example
7.Programming with Big Data in R
8.Big Data Strategies in R
9.Applications of R Programming
10.Companies Using R
11.What R is not so good at
12.Conclusion
This document discusses data provisioning in SAP HANA. It defines data provisioning as the process of creating, preparing, and enabling data to be provided to users. This includes extract, transform, and load (ETL) processes to move data from source systems into SAP HANA. It describes the built-in and external tools that can be used for data provisioning in SAP HANA, including SAP Landscape Transformation, SAP Business Objects Data Services, and SAP Direct Extractor Connection. Specific ETL tools like SAP Landscape Transformation and SAP Data Services are discussed in more detail regarding their features and how they can be used to replicate and transform source data for loading into SAP HANA
The document discusses how to size hardware configurations for SAP HANA landscapes using SAP's Quick Sizer tool. It describes the SAP HANA version of Quick Sizer, which was created specifically for sizing SAP HANA deployments. The tool calculates hardware sizing requirements based on key performance indicators and user-provided data on usage details. It then provides an example of using Quick Sizer to size an on-premise SAP S/4HANA deployment, including sizing the front-end and back-end servers.
The document provides information about SAP HANA, including what it is, its architecture, and development scenarios. SAP HANA is an in-memory database that can be deployed on-premise or in the cloud. It allows for real-time analysis of large data volumes. The architecture includes components like the index server, XS runtime, and name server. Development in SAP HANA involves using calculation views to define slices of data and Studio as an development environment. Time dimensions and graphical views can also be generated.
This document provides guidance on sizing an SAP LT Replication Server for SAP HANA landscape. It discusses factors that influence performance such as software versions, configuration, network factors, and data reading type. The document then presents assumptions, a template-based sizing approach, and sizing guidelines to estimate hardware requirements for the replication server. It also includes a section on comments and feedback.
1310 success stories_and_lessons_learned_implementing_sap_hana_solutionsBobby Shah
The document summarizes a session on implementing SAP HANA solutions. It provides an overview of SAP HANA, currently available solutions based on SAP HANA including SAP HANA standalone and SAP NetWeaver BW powered by SAP HANA. It also discusses tips and tricks for implementing SAP HANA standalone solutions, including data modeling vs analytic modeling and using SAP HANA analytic modeling and Data Services data modeling. Observations on implementing BW powered by SAP HANA are also presented along with examples of performance improvements customers have seen.
SAP HANA is an in-memory database platform that stores transactional data in memory for real-time analytics by eliminating disk input/output lag; it uses columnar storage with efficient compression and built-in indexing for each column to enable fast queries and joins; SAP HANA features include predictive analytics, multitenant containers, high availability, and tools for data modeling, administration, and development.
Whether MVC for user interfaces, or Spine and Leaf for data centers, new
architecture patterns in our industry act as sort of historical markers of the
effectiveness and acceptance of new technologies. Practical techniques push the
bounds resulting in a shift. Application of distributed storage and streaming
capabilities such as Kafka and of course Hadoop are shifting Big Data architectures
from a layer cake concept, or North/South oriented approach to one which can be
thought of as an East/West architectural concept. Recently popular is Lambda
Architecture, this article presents an SAP HANA based rendering of the Lambda
Architecture.
What is Sap HANA Convista Consulting Asia.pdfankeetkumar4
SAP HANA is the most recent, in-memory information base, and stage which can be sent on-premises or cloud. SAP HANA is a blend of equipment and programming, which coordinates various parts like SAP HANA Database, SAP SLT (System Landscape Transformation) Replication server, SAP HANA Direct Extractor association, and Sybase replication.
HANA has remarkable reception by the SAP clients. SAP HANA is equipped for handling a lot of constant information in a brief time frame period
SAP HANA Integrated Online Course Training in Hyderabad | Imagine LifeImagine life
Imaginelife Provides SAP HANA Integrated Online Classroom Training and E Learning Courses Providing Institution Specialized for IT Courses Learning Beginners, Learn SAP Cloud Integration and Business Processes Certification Programming, Training provided by Online Real Time Experts.
Projected cost analysis of the Sap Hana Platform Cost Savings Enabled By Tr...Abdulrahman Abdulrahim
The document summarizes a study conducted by Forrester Consulting on the projected cost savings from transitioning to SAP's HANA in-memory platform. It finds that a composite organization could save 37% in total costs of ownership over 3 years by moving its SAP BW, ERP, and a custom application to HANA. Key cost savings come from reduced hardware, software, and labor needs due to HANA's simplified data management and faster development times. Customers interviewed achieved significant data compression and increased efficiency in administration and development.
This document provides an overview and analysis of cost savings projected for a composite organization transitioning various applications, including SAP BW, SAP ERP, and a custom application, to the SAP HANA platform over three years. Interviews with existing SAP HANA customers informed the analysis. The analysis projects that the composite organization could save 37% of total costs over three years by reducing hardware, software, and labor costs through the simplified and automated environment of the SAP HANA platform. Key projected savings include 70% reduction in software costs, 15% reduction in hardware costs, and 20% reduction in administration and development labor costs.
This document provides an overview of SAP HANA, including its architecture and various use cases. It describes SAP HANA as an in-memory database that can be used as primary persistence for SAP NetWeaver applications, as a data mart for real-time analytics and reporting, and as a platform for building applications. It also discusses SAP HANA's technical deployment options, software components, and implementation considerations.
SAP HANA is an in-memory database platform that can be deployed on-premise or in the cloud. When deployed on-premise, SAP HANA combines software and hardware components optimized by SAP and its partners. In the cloud, SAP HANA is offered through managed services on infrastructure like SAP HANA One. To take advantage of SAP HANA's high-speed processing, developers can use Open SQL, core data services, and ABAP managed database procedures.
Please visit - www.mansur-pune.blogspot.com for SAP Training materials download .
https://drive.google.com/folderview?id=0B5mQZCJnlt6NSkFUTHhldm5wSVk&usp=sharing
Technical Overview of CDS View – SAP HANA Part IAshish Saxena
SAP HANA has introduced new paradigms to SAP ABAP application programming. Before SAP HANA, development paradigm in SAP was based on DATA-to-Code where intensive calculation was done at the application layer and database utilization was minimized. New programming paradigm in SAP HANA is Code-to-Data, where the intensive calculation is done at the database layer and less programming at application layer.
This document introduces the SAP HANA Cookbook for MySQL Developers. The cookbook provides real examples, code snippets, and tutorials to help MySQL developers leverage advanced analytics capabilities on SAP HANA such as predictive analytics, text mining, and geospatial processing. It covers how to load MySQL data into SAP HANA using open source ETL tools, perform ad-hoc analytics and build predictive applications using R algorithms on SAP HANA. The goal is to help MySQL developers maximize the value of their existing databases by pairing them with SAP HANA for advanced analytics.
SAP HANA direct extractor:Data acquisition Deepak Chaubey
The document provides an installation and configuration guide for the SAP HANA Direct Extractor Connection (DXC). It includes an overview of DXC, the setup steps in SAP HANA and the source SAP system, configuration for SAP Business Warehouse data transfer, and monitoring the data load process. The guide also includes an appendix on an alternative "sidecar" approach and references other relevant documentation.
SAP HANA is an in-memory database developed by SAP that allows for real-time analytics by storing data in RAM rather than on disk. It is made up of several technical components including the SAP In-Memory Database and runs on the SUSE Linux operating system. SAP HANA uses different styles of data replication to ingest data from various sources and make it available for real-time querying. It supports both analytic and transactional applications from SAP with more applications being developed to leverage its in-memory capabilities. While it can store tens of terabytes of data, it is not suited for petabyte-scale unstructured "big data" workloads.
SAP Crystal Reports & SAP HANA - Integration and RoadmapKenneth Li
This document provides an overview and instructions for integrating SAP Crystal Reports with SAP HANA. It discusses the key components - Crystal Reports for Enterprise for report design, a Crystal Reports Reporting Service for processing, and a Delivery Unit for browser viewing. It also covers deploying the components, configuring SAP HANA and the reporting service, authoring reports, promoting reports for consumption in Lumira, and migrating reports. Some known current limitations are also listed.
SAP HANA typical implementations today
Outlook for the next 12-18 months
Disaster Recovery capabilities of SAP HANA
Complete automation of Disaster Recovery for SAP HANA with SUSE Linux High Availability
Speakers: Dan Lahl (VP Database Product, SAP), Markus Guertler (Senior SAP Architect, SUSE)
Similar to Write back functionality from various dashboard tools to sap hana (20)
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SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
Write back functionality from various dashboard tools to sap hana
1. Page 1 Author– Ramkumar Rajendran
Write back functionality from various
dashboard tools to SAP HANA
2. Page 2 Author– Ramkumar Rajendran
Author Biography
Ramkumar Rajendran
.
Ramkumar Rajendran is a Consultant at a leading firm with an
experience of 4 years. He has specialized in various tools like SAP HANA,
SAP BI, SAP BO (Xcelsius, Webi and IDT), Tableau, Lumira and Hadoop-
Hive. He has worked upon the Sentiment Analysis of Twitter data. He
has involved in the integration of HANA and Hadoop. He has worked on
multiple implementation projects for various industry sectors.
3. Page 3 Author– Ramkumar Rajendran
Table of Contents
1 About this document ..................................................................4
2 Introduction ...............................................................................5
SAP HANA................................................................................................... 5
SAP HANA extended application services .............................................. 5
3 Design Plan ........................................Error! Bookmark not defined.
4 Case study update from Tableau, Qlikview and Xcelsius ................7
SAP HANA table......................................................................................... 7
Server Side Application built using JavaScript ....................................... 8
HANA Table view of the record to be changed ...................................10
Tableau Solution......................................................................................11
How the Tableau Solution works ..........................................................13
Qlikview Solution ....................................................................................14
Xcelsius Solution......................................................................................15
Other Reporting tools.............................................................................15
5 Summary..................................................................................16
6 Reference Material ...................................................................16
4. Page 4 Author– Ramkumar Rajendran
About this document
Updating database tables from the reporting tools like Tableau, Qlikview, Xcelsius, etc. was
considered to be a myth earlier and believed to be possible only specialized application like
Business planning and consolidation, Integrated planning etc. These reporting tools were
believed to be just used for visualizing the underlying data from the database through various
graphs and charts.
This paper describes the possibility of updating tables from various reporting tools with an
innovative solution.
As a pre-requisite to go through the document, it is expected that the user is aware of basic SAP
HANA functionalities, basic features of Tableau, Qlikview and Xcelsius and JavaScript concepts.
5. Page 5 Author– Ramkumar Rajendran
Introduction
SAP HANA
SAP HANA is an innovative in-memory database and data management platform, specifically
developed to take full advantage of the capabilities provided by modern hardware to increase
application performance. By keeping all relevant data in main memory, data processing
operations are significantly accelerated.
Design for scalability is a core SAP HANA principle. SAP HANA can be distributed across many
multiple hosts to achieve scalability in terms of both data volume and user concurrency. Unlike
clusters, distributed HANA systems also distribute the data efficiently, achieving high scaling
without I/O locks.
The key performance indicators of SAP HANA appeal to many of our customers, and thousands
of deployments are in progress. SAP HANA has become the fastest growing product in SAP’s
40+ year history.
SAP HANA Extended ApplicationServices
SAP HANA Extended Application Services (SAP HANA XS) provide applications and application
developers with access to the SAP HANA database using a consumption model that is exposed
via HTTP.
In addition to providing application-specific consumption models, SAP HANA XS also host
system services that are part of the SAP HANA database. For example: search services and a
built-in Web server that provides access to the static content stored in the SAP HANA
repository.
The consumption model provided by SAP HANA XS focuses on server-side applications written
in JavaScript. Applications written in server-side JavaScript can make use of a powerful set of
specially developed API functions, for example, to enable access to the current request session
or the database.
6. Page 6 Author– Ramkumar Rajendran
Design Plan
The technique of updating the HANA tables from the reporting tools is heavily built around a
server side application developed with JavaScript code, which gets invoked from the report and
the relevant data is passed as parameter to this code in the HANA server. With the availability
of these parameters the server side application is executed resulting in update of the values in
the tables.
In order to update data into HANA table would require passing of 3 parameters to application
layer, namely -
1. Primary keys to distinguish a unique record.
2. Name of the column.
3. Value which needs to be updated in the table.
As depicted in the above figure the server side application is called which residing in the
Webserver of HANA database and the relevant parameters are passed from the reporting tools
to this application. This code further executes to update the HANA database tables, which is
thinly coupled with the Webserver resulting in immediate update of the table with the passed
parameter.
Reporting Tools
Webserver-HANA
Database-HANA
The server side application
in HANA Webserver is
invoked and parameters are
passed resulting in update
of HANA tables
7. Page 7 Author– Ramkumar Rajendran
Case Study – Update data from Tableau, Qlikviewand Xcelsius
SAP HANA Table
Let’s assume that we have a table in SAP HANA, named “BANK_INDICATORS” with the following
structure.
With regard to our earlier mention, the primary keys of the table have to be noted which is
“COUNTRY” and “DATE” in this case. The value of these key fields needs to be passed from the
reporting layer to identify a unique record in the table.
The initial set of data in the table would be looking like this.
8. Page 8 Author– Ramkumar Rajendran
Server Side Application built using JavaScript
SAP HANA Extended Application Services (SAP HANA XS) helps in hosting a server-side
application written in JavaScript. We would utilize the potential of this application in our case
study to update the HANA table with the parameters passed while invoking the application.
switch (field)
{
case'COUNTRY':
conn.prepareStatement("SET SCHEMA "HANA"").execute();
var st = conn.prepareStatement("UPDATE "HANA"."BANK_INDICATORS" SET "COUNTRY" = ?
WHERE "COUNTRY" = ?");
st.setString(1,data);
st.setString(2,cname);
break;
case'DATE':
conn.prepareStatement ("SET SCHEMA "HANA"").execute();
var st = conn.prepareStatement("UPDATE "HANA"."BANK_INDICATORS" SET "DATE" = ? WHERE
"COUNTRY" = ? AND "DATE" = ?");
st.setString(1,data);
st.setString(2,cname);
st.setString(3,date);
break;
case'INTERNET_USERS':
conn.prepareStatement("SET SCHEMA "HANA"").execute();
var st = conn.prepareStatement("UPDATE "HANA"."BANK_INDICATORS" SET "INTERNET_USERS"
= ? WHERE "COUNTRY" = ? AND "DATE" = ?");
st.setString(1,data);
st.setString(2,cname);
st.setString(3,date);
break;
9. Page 9 Author– Ramkumar Rajendran
case'MILITARY_EXPENDITURE':
conn.prepareStatement("SET SCHEMA "HANA"").execute();
var st = conn.prepareStatement("UPDATE "HANA"."BANK_INDICATORS" SET
"MILITARY_EXPENDITURE" = ? WHERE "COUNTRY" = ? AND "DATE" = ?");
st.setString(1,data);
st.setString(2,cname);
st.setString(3,date);
break;
case'GDP_PERCAPITA':
conn.prepareStatement("SET SCHEMA "HANA"").execute();
var st = conn.prepareStatement("UPDATE "HANA"."BANK_INDICATORS" SET"GDP_PERCAPITA" =
? WHERE "COUNTRY" = ? AND "DATE" = ?");
st.setString(1,data);
st.setString(2,cname);
st.setString(3,date);
break;
case'LIFE_EXPECTANCY':
conn.prepareStatement("SET SCHEMA "HANA"").execute();
var st = conn.prepareStatement("UPDATE "HANA"."BANK_INDICATORS" SET "LIFE_EXPECTANCY"
= ? WHERE "COUNTRY" = ? AND "DATE" = ?");
st.setString(1,data);
st.setString(2,cname);
st.setString(3,date);
break;
}
10. Page 10 Author– Ramkumar Rajendran
HANA Table view of the recordto be changed
Consider the below view of the table “BANK_INDICATORS”. Assume that we need to change the
“LIFE_EXPECTANCY” of the record which is highlighted in the below figure to ‘60’.
It should be noted that key fields include COUNTRY and DATE, which in this case are ‘Albania’
and ’01-Jul-2006’.
11. Page 11 Author– Ramkumar Rajendran
Tableau Solution
Create a Tableau dashboard with live connection to SAP HANA which would look like below.
Enter the new value for the field as 60 and choose the field which needs to be updated from
the drop down box.
Right click anywhere in the dashboard and select “Update new value for LIFE_EXPECTANCY”
12. Page 12 Author– Ramkumar Rajendran
Refresh the Tableau dashboard and we could see that the value for LIFE_EXPECTANCY is
updated as ‘60’ in the dashboard.
And the same value can be seen updated in the HANA table level.
13. Page 13 Author– Ramkumar Rajendran
Howthe Tableau Solutionworks?
A text input area for the new value and a drop down box for the field names is created as
shown in the below figure.
A URL action is created which is associated with the parameters “Enter updated data” and
“Select Field” and the dashboard.
This URL action as mentioned above dynamically collects the relevant parameters, viz. primary
keys of the HANA table (COUNTRY and DATE), the new value (60) and the field which needs to
be updated (LIFE_EXPECTANCY) and executes the server side application at the HANA
webserver level with these parameters which in turn would update HANA database table with
these parameters.
http://10.118.0.80:1080/HANA_PAPER/HANA_PAPER/bank.xsjs?field=<Parameters.Select
Field>&cname=<COUNTRY>&cdate=<DATE>&data=<Parameters.Data>
14. Page 14 Author– Ramkumar Rajendran
QlikviewSolution
On the same lines the dashboard in Qlikview will also help in updating HANA tables. The
dashboard will look as follows.
In this case we are required to explicitly ask the key field information apart from the new value
and field name information from the users since the same functionality can’t be performed
here
In addition to what have been done for Tableau, we are expected to manually fetch the data of
each relevant field through manual variables. Also a bit of macro coding is required to give a
better user experience.
15. Page 15 Author– Ramkumar Rajendran
Xcelsius Solution
The dashboard built with Xcelsius will look as follows.
In this case the new value will be updated on the basis of the correction done in the input text
area available once any of the record is chosen. The link for the server side application in HANA
webserver is embedded into one of the excel sheet present in the dashboard, which is called
while clicking on the Update button.
Other Reporting tools
As per our research the same technique can be applied across majority of the reporting tools,
except a few like Explorer and Lumira which doesn’t support URL actions.
16. Page 16 Author– Ramkumar Rajendran
Summary
The combinedpotential of SAPHANA ExtendedApplicationServicesandthe variousreportingtools
have beenutilizedtoaccomplishaveryenthrallingsolution.Thistechniquecanbe applicable in
scenarioswhere the usersare expectedtoupdate valuesona regularbasis.
It doesn’tserve asa complete replacementforSAPBPC,SAPIP,Hyperion,etc. Butthe mythof updating
data to database fromthe reportinglayerisbroken.
What we have illustratedoverhere isasimple mechanismtoachieve thistask.We canfurther
customize thistechnique toaccomplishmuchcomplex real timesolutions.
The same technique canbe furtherextendedtoothertoolslike MicroStrategy,Spotfire,etc.
References
http://help.sap.com/hana/SAP_HANA_Developer_Guide_en.pdf
http://scn.sap.com/community/developer-center/hana/blog/2012/12/21/hana-development-xs-odata-
services
http://www.tableausoftware.com/public/blog
http://community.qlik.com/welcome
http://everythingxcelsius.com/