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Making Techo ERP (Enterprise Resource Planning)
Intelligent
Introduction
In the present days, many of the corporations have opted to replace their disparate Information Systems
with a single integrated system. Rather than one IS or several ISs, in each Business function, All Business
function are served by one system that supports different activities for different department. Such systems
are often termed as Enterprise Resource Planning (ERP) Systems. (Murthy, 2008)
R is an open source programming language and software environment for statistical computing and
graphics. The R language has become very popular among statisticians and data miners for developing
statistical software and is widely used for advanced data analysis.
The goal of the integration of the Techo ERP database with R is to enable the embedding of R code in the
ERP database context. That is, the ERP database allows R code to be processed in-line as part of the
overall query execution plan. This scenario is suitable when an ERP based modeling and consumption
application wants to use the R environment for specific statistical functions.
An efficient data exchange mechanism supports the transfer of intermediate database tables directly into
the vector-oriented data structures of R. This offers a performance advantage compared to standard SQL
interfaces, which are tuple based and, therefore, require an additional data copy on the R side.
Related Work in Data Mining Research
In the last decade, major research progress has been made towards reform data mining algorithms. There
has been an explosion of work in scaling many major data mining techniques to work with large data sets,
i.e., ensuring that the algorithms are “disk-aware” and more generally, conscious of memory hierarchy,
instead of making the assumption that all data must reside in memory. Another direction of work that has
been pursued is to consider if data mining algorithms may be implemented as traditional database
applications. Such implementations ensure that the data mining implementations are not only disk-aware
but also “SQLaware”, i.e., the implementations take advantage of the functionality provided through the
SQL Engine and the API. Efforts to implement mining algorithms on top of database systems have also
led to primitives such as sampling to ease the task of data mining on relational systems, e.g., see the
proposal in. Experiments on Integrating unstructured and Structure data that our proposed set of
techniques lead to significant improvement in accuracy on real-life datasets.
PROBLEM DEFINITION:
Manufacturers and distributors in all industries and regions of the world are reevaluating how their
businesses impact the environment in which they operate, including their partners, customers and
communities. With this Techo ERP software, companies can manage their environmental programs
efficiently and achieve the targets that many companies are now obliged to attain.
This Business ERP software promises to be an important tool for companies to better manage
sustainability programs across their supply chain. By using this business software, companies can easily
manage the sustainability programs across their entire organization in one place, gain greater visibility
into their existing sustainability programs, and produce better results as well as for reporting purpose.
By implementing e-resource ERP system, organizations could also enjoy the benefits of Greater visibility
and control; improvement in lead time; improvement in work in process; improvement in inventory;
improvement in product quality ; improvement in defects; improvement in cycle time; improvement in
traceability and Reduced paper work, data entry, manpower.
If you think you need enterprise wide business intelligence that includes that data, you need to factor in
getting a data feed back into that organization and into your systems, you then need somewhere to store
and analyze it. You also need to consider what kind of business intelligence those solutions provide to see
how you're going to progress with your business intelligence solutions if you are going to use your
software as a service.
For many years business intelligence vendors were fighting with the Office products like Excel, but now
they're recognized as being just as integral to business intelligence as any other piece of software or
solution. Everybody uses it all the time, the finance and other department loves it and as the technology
and the visualization capability within this program and improving it will probably be used even more.
➢ Objective:
An Techo ERP manufacturing company wants to provide insights to its customers. Techo ERP
systems collect lot of data related to processes and customers. The ERP systems are installed in various
industries such asmanufacturing, retail and chemical processing industries.
The objective of this study are developing a interface where the ERP data can be imported to the R
system and data can be analyzed in the R system and the results can be reported back in the ERP
environment.
This project is to reflect the importance of supplier evaluation process, analyzing criteria that can be used
to determinate the best supplier and developing different methods that help to make this decision.
An analysis on the provided data was conducted to assist in report making for the Supplier Rating. The
analysis revealed a transparent view of the Supplier for a particular Item & the score was generated on the
basis of days delayed in the delivery of the particular item.
The market is changing and supplier selection approach has evolved from multiple suppliers to single
supplier approach. In the past, the traditional approach used to consider multiple suppliers and one main
criterion, the price. However, the market has moved towards contracting a single supplier selected by
means of a multiple criteria.
➢ Methodology
To process R code in the context of the ERP database, the R code is embedded in ERP SQL code in the
form of a RLANG procedure. The ERP database uses the external R environment to execute this R code,
similarly to native database operations like joins or aggregations. This allows the application developer to
elegantly embed R function definitions and calls within SQLScript and submit the entire code as part of a
query to the database.
To achieve this, the calculation engine of the ERP database was extended. The calculation engine
supports data flow graphs (calculation models) describing logical database execution plans. A node in this
data flow graph can be any native database operation, but also a custom operation. One of those custom
operations is the R operator.
SQL has limited numerical and statistical features. Not only are basic statistical functions missing from
SQL, but in many cases the numerical algorithms used in the basic aggregate functions are not
implemented to safeguard numerical accuracy. Also, the wide range of data types may have drawbacks
when it comes to performing arithmetic calculations across a row, as some of the conversions from one
numeric type to another may produce unexpected truncation and rounding. For these reasons, it may be
desirable or even necessary to perform a statistical analysis in a statistical package rather than in the
database.
One way to do this is to extract data from the database and import it into statistical software. The
statistical software may either reside on the server-side, i.e. on the machine which hosts the database, or it
may reside on the client-side, i.e. the user’s machine. The DBI package in R provides a uniform,
clientside interface to different database management systems, such as MySQL, PostgreSQL, and Oracle.
The DBI package provides a general interface to a database management system. Additional packages
that handle the specifics for particular database management systems are required.
R procedures can contain code that can harm security on the server where the Rserve is running, such as
the following:
• Access file system (read/write).
• Install new add-on/R packages that can contain binary code (for example, written in C).
• Execute operating system commands.
• Open network connections and download files or open connections to other servers.
One thing that is very clear though about R is that it’s a “data source agnostic” environment, but many of
the examples that use data either deal with flat files or connect to open source databases like SQL or
Postgres. This of course doesn’t mean you can’t use R with SQL Server, it just means you have to dig a
little deeper and understand how to connect the R environment to your SQL Server database.
CONCLUSION
In today’s technologies the customer has a lot of difficulties to access the organization’s facilities. The
customer have problem in contacting the organization. The model presented in this paper will solve these
problems all the customers complaints will be recording in the central database and will be process
according to the customer need. The customer can easily contact the organization and can purchase the
organization products very easily. The CRM (outer view) will collect the information about the products
and the queries will be forwarded to the inner view (ERP) to act upon these queries. The knowledge
discovery view generates new rules and patterns for the betterment of an organization for future
correspondence to improve the growth of the customers for an organization.
As we have seen, suppliers rating is used in a variety of ways and are critical to a company’s
success, but there is no one way to create a dashboard. So what would be the best way to go about
creating a dashboard, or improving your current process? Based on literature and the document analysis,
quality, delivery time, cost and service are the core criteria that should be evaluated in the supplier
dashboard. Service is also starting to differentiate suppliers, and the literature shows that in the future,
service is becoming a more critical aspect to be evaluated. Supplier rating should rate the performance of
all suppliers equally; therefore, it is important the criteria be measured as objectively as possible.
The final area we looked at was ease of use and effectiveness. The goal is to make the evaluation
Dashboard as easy as possible without forgoing the effectiveness of the evaluation. The way of assisting
with the creation of the instruction process is to give it to a third party to review. This will help with the
issue of the instructions making sense to those who are not familiar with the evaluation Dashboard
process, especially a new buyer or internal customers who may be reviewing this information.
We are developing a interface where the ERP data can be imported to the R system and data can be
analyzed in the R system and the results can be reported back in the ERP environment.
FUTURE WORK
The model will be enhancing with more information and more data mining technique will be applying and
new rules will be generated in future for the enhancement of an organization. Techo ERP tools will be
used to modify the existing work and make ease for the customers to access the organization’s
facilitieswithout any hesitation.
Details of Techo_ERP
Bio---TechoERP is a leading solution providing, powerful, intuitive, and easy-to-use Cloud-based software.
About---TechoERP is a fully automated, scalable cloud-based ERP which includes Employee Management
System, CRM, Buying, Selling, AI-based workflow, and Project & Multiple features for Business
Management.
Address--Plot no-161 / Sector-80 / Preet City
City---Mohali
State---Punjab
Zipcode------160055
Phone number------+91 62398 8508
Website: https://techoerp.in/
facebook link-------- https://www.facebook.com/TECHO-107729585206093
instagram link------- https://www.instagram.com/techoerp/
twitter link--------- https://twitter.com/OptimisticTecho

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TechoERP.pdf

  • 1. Making Techo ERP (Enterprise Resource Planning) Intelligent Introduction In the present days, many of the corporations have opted to replace their disparate Information Systems with a single integrated system. Rather than one IS or several ISs, in each Business function, All Business function are served by one system that supports different activities for different department. Such systems are often termed as Enterprise Resource Planning (ERP) Systems. (Murthy, 2008) R is an open source programming language and software environment for statistical computing and graphics. The R language has become very popular among statisticians and data miners for developing statistical software and is widely used for advanced data analysis. The goal of the integration of the Techo ERP database with R is to enable the embedding of R code in the ERP database context. That is, the ERP database allows R code to be processed in-line as part of the overall query execution plan. This scenario is suitable when an ERP based modeling and consumption
  • 2. application wants to use the R environment for specific statistical functions. An efficient data exchange mechanism supports the transfer of intermediate database tables directly into the vector-oriented data structures of R. This offers a performance advantage compared to standard SQL interfaces, which are tuple based and, therefore, require an additional data copy on the R side. Related Work in Data Mining Research In the last decade, major research progress has been made towards reform data mining algorithms. There has been an explosion of work in scaling many major data mining techniques to work with large data sets, i.e., ensuring that the algorithms are “disk-aware” and more generally, conscious of memory hierarchy, instead of making the assumption that all data must reside in memory. Another direction of work that has been pursued is to consider if data mining algorithms may be implemented as traditional database applications. Such implementations ensure that the data mining implementations are not only disk-aware but also “SQLaware”, i.e., the implementations take advantage of the functionality provided through the SQL Engine and the API. Efforts to implement mining algorithms on top of database systems have also led to primitives such as sampling to ease the task of data mining on relational systems, e.g., see the proposal in. Experiments on Integrating unstructured and Structure data that our proposed set of techniques lead to significant improvement in accuracy on real-life datasets. PROBLEM DEFINITION: Manufacturers and distributors in all industries and regions of the world are reevaluating how their businesses impact the environment in which they operate, including their partners, customers and communities. With this Techo ERP software, companies can manage their environmental programs efficiently and achieve the targets that many companies are now obliged to attain. This Business ERP software promises to be an important tool for companies to better manage sustainability programs across their supply chain. By using this business software, companies can easily manage the sustainability programs across their entire organization in one place, gain greater visibility into their existing sustainability programs, and produce better results as well as for reporting purpose.
  • 3. By implementing e-resource ERP system, organizations could also enjoy the benefits of Greater visibility and control; improvement in lead time; improvement in work in process; improvement in inventory; improvement in product quality ; improvement in defects; improvement in cycle time; improvement in traceability and Reduced paper work, data entry, manpower. If you think you need enterprise wide business intelligence that includes that data, you need to factor in getting a data feed back into that organization and into your systems, you then need somewhere to store and analyze it. You also need to consider what kind of business intelligence those solutions provide to see how you're going to progress with your business intelligence solutions if you are going to use your software as a service. For many years business intelligence vendors were fighting with the Office products like Excel, but now they're recognized as being just as integral to business intelligence as any other piece of software or solution. Everybody uses it all the time, the finance and other department loves it and as the technology and the visualization capability within this program and improving it will probably be used even more. ➢ Objective:
  • 4. An Techo ERP manufacturing company wants to provide insights to its customers. Techo ERP systems collect lot of data related to processes and customers. The ERP systems are installed in various industries such asmanufacturing, retail and chemical processing industries. The objective of this study are developing a interface where the ERP data can be imported to the R system and data can be analyzed in the R system and the results can be reported back in the ERP environment. This project is to reflect the importance of supplier evaluation process, analyzing criteria that can be used to determinate the best supplier and developing different methods that help to make this decision. An analysis on the provided data was conducted to assist in report making for the Supplier Rating. The analysis revealed a transparent view of the Supplier for a particular Item & the score was generated on the basis of days delayed in the delivery of the particular item. The market is changing and supplier selection approach has evolved from multiple suppliers to single supplier approach. In the past, the traditional approach used to consider multiple suppliers and one main criterion, the price. However, the market has moved towards contracting a single supplier selected by means of a multiple criteria. ➢ Methodology To process R code in the context of the ERP database, the R code is embedded in ERP SQL code in the form of a RLANG procedure. The ERP database uses the external R environment to execute this R code, similarly to native database operations like joins or aggregations. This allows the application developer to elegantly embed R function definitions and calls within SQLScript and submit the entire code as part of a query to the database. To achieve this, the calculation engine of the ERP database was extended. The calculation engine supports data flow graphs (calculation models) describing logical database execution plans. A node in this data flow graph can be any native database operation, but also a custom operation. One of those custom operations is the R operator. SQL has limited numerical and statistical features. Not only are basic statistical functions missing from SQL, but in many cases the numerical algorithms used in the basic aggregate functions are not implemented to safeguard numerical accuracy. Also, the wide range of data types may have drawbacks when it comes to performing arithmetic calculations across a row, as some of the conversions from one numeric type to another may produce unexpected truncation and rounding. For these reasons, it may be
  • 5. desirable or even necessary to perform a statistical analysis in a statistical package rather than in the database. One way to do this is to extract data from the database and import it into statistical software. The statistical software may either reside on the server-side, i.e. on the machine which hosts the database, or it may reside on the client-side, i.e. the user’s machine. The DBI package in R provides a uniform, clientside interface to different database management systems, such as MySQL, PostgreSQL, and Oracle. The DBI package provides a general interface to a database management system. Additional packages that handle the specifics for particular database management systems are required. R procedures can contain code that can harm security on the server where the Rserve is running, such as the following: • Access file system (read/write). • Install new add-on/R packages that can contain binary code (for example, written in C). • Execute operating system commands. • Open network connections and download files or open connections to other servers. One thing that is very clear though about R is that it’s a “data source agnostic” environment, but many of the examples that use data either deal with flat files or connect to open source databases like SQL or Postgres. This of course doesn’t mean you can’t use R with SQL Server, it just means you have to dig a little deeper and understand how to connect the R environment to your SQL Server database. CONCLUSION In today’s technologies the customer has a lot of difficulties to access the organization’s facilities. The customer have problem in contacting the organization. The model presented in this paper will solve these problems all the customers complaints will be recording in the central database and will be process according to the customer need. The customer can easily contact the organization and can purchase the organization products very easily. The CRM (outer view) will collect the information about the products and the queries will be forwarded to the inner view (ERP) to act upon these queries. The knowledge discovery view generates new rules and patterns for the betterment of an organization for future correspondence to improve the growth of the customers for an organization.
  • 6. As we have seen, suppliers rating is used in a variety of ways and are critical to a company’s success, but there is no one way to create a dashboard. So what would be the best way to go about creating a dashboard, or improving your current process? Based on literature and the document analysis, quality, delivery time, cost and service are the core criteria that should be evaluated in the supplier dashboard. Service is also starting to differentiate suppliers, and the literature shows that in the future, service is becoming a more critical aspect to be evaluated. Supplier rating should rate the performance of all suppliers equally; therefore, it is important the criteria be measured as objectively as possible. The final area we looked at was ease of use and effectiveness. The goal is to make the evaluation Dashboard as easy as possible without forgoing the effectiveness of the evaluation. The way of assisting with the creation of the instruction process is to give it to a third party to review. This will help with the issue of the instructions making sense to those who are not familiar with the evaluation Dashboard process, especially a new buyer or internal customers who may be reviewing this information. We are developing a interface where the ERP data can be imported to the R system and data can be analyzed in the R system and the results can be reported back in the ERP environment. FUTURE WORK The model will be enhancing with more information and more data mining technique will be applying and new rules will be generated in future for the enhancement of an organization. Techo ERP tools will be used to modify the existing work and make ease for the customers to access the organization’s facilitieswithout any hesitation. Details of Techo_ERP Bio---TechoERP is a leading solution providing, powerful, intuitive, and easy-to-use Cloud-based software. About---TechoERP is a fully automated, scalable cloud-based ERP which includes Employee Management System, CRM, Buying, Selling, AI-based workflow, and Project & Multiple features for Business Management. Address--Plot no-161 / Sector-80 / Preet City City---Mohali State---Punjab Zipcode------160055 Phone number------+91 62398 8508
  • 7. Website: https://techoerp.in/ facebook link-------- https://www.facebook.com/TECHO-107729585206093 instagram link------- https://www.instagram.com/techoerp/ twitter link--------- https://twitter.com/OptimisticTecho