Infosys’ blog on industry solutions, trends, business process transformation and global implementation in Oracle.

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November 15, 2017

Oracle Data Visualization Cloud Service

 

Oracle Data Visualization Cloud Service

 

Overview

Visual Analysis and Self Service discovery cloud service from Oracle. It has the following main features

  • Easy Upload

Upload data from a variety of sources (for example, spreadsheets, CSV files, Fusion Applications, and many databases) to your system and model it in a few easy steps

  • Simple Mash up

            Data from different sources is automatically connected

  • Easy Exploration

Create visualizations and projects that reveal trends in your company's data by creating insights and stories

  • Visual Experience

Auto visualization, Brushing and Intuitive, Filtering, Auto coloring, Built in Maps

 

Data Sources

DVCS can use data from the following sources for creating stunning visualization projects

  • Spreadsheet /CSV (<= 50 MB in size)

  • Data from Oracle Applications data sources

  • Oracle Transactional Business Intelligence Oracle BI EE analysis and subject areas

  • Data from a database as a service or on premise database using Remote Data Connector

  • Data from various on premise data sources such as (CSV, relational Databases, SQL query) can be uploaded and used in DVCS using Oracle Data Sync

  • Oracle Data Visualization Cloud Service REST API can also be used to programmatically load on-premises data to a data set that you can explore

 

Sample Hybrid Cloud Architecture with OBIA, OTBI and DVCS

OOB + Custom OBIEE Business Logic and reports

 

Or RDP

 

  • DVCS can be used to create visualization stories and projects directly using data from Oracle Applications data sources with Oracle Transactional Business Intelligence using Oracle BI EE analysis and subject area

  • Data extracted from the cloud ERP into an on premise data warehouse can then be used to create data visualization analysis and projects

 

DVCS Security Features

  • Identity domain

    • Identity Domain is a construct for managing certain features of Oracle Cloud including DVCS

    • The identity domain controls the authentication and authorization of users who sign in to Oracle Cloud services including DVCS

    • Several predefined roles and user accounts are available when DVCS is provisioned in an identity domain

    • If one has EBS on the cloud and uses DVCS to connect directly to OTBI subject areas. The 2 cloud services can share the same identity domain or it can be separate. The specifications of choosing the identity domain should be in the contract, but in theory both cases are possible

    • The roles in Identity domain are recognized in Web Logic

  • SSO

    • SSO is a token service for authentication while an identity domain allows you to manage users and roles.

    • One can integrate existing Oracle SSO with the identity domain of DVCS

  •  Application Roles

    • Comprises a set of privileges that determine what users can see and do after signing in to Oracle Data Visualization Cloud Service

    • There are two types of application role          

      • Predefined

      • User Defined

  • Data Level Security

One cannot control data visibility within DVCS but only control object visibility based on Application Roles/Users => meaning you can control which report a user can see but you cannot control what data the user can see in the report.  This is because you don't do any modeling within DVCS, so no data filters can be applied.   The data visibility is driven by the username used to connect to OTBI - whatever data this user sees will be visible within DVCS

 

Conclusion

DVCS is a powerful addition to the Oracle BI tools. It provides self-data discovery features with rich UI and visualization capabilities. It's a step in the right direction towards incorporation of the modern BI and Analytics features. It supports cloud and hybrid deployments supported. DVCS be used for root cause analysis data visualization project. Supported by Oracle's strong infrastructure, it provides an attractive option for Oracle's install base. It is not typically used for creating reports with large volumes or large number of columns. Using BICS, OBIEE, OAC one can develop tabular report with 500+ or 1000+ columns. In its current release, it is not possible to print or share (create for example a pdf and then send it via email) analysis created from the catalog those buttons are disabled.

 

 

References

https://docs.oracle.com/en/cloud/paas/data-visualization-cloud/bidvc/getting-started-data-visualization.html

 

November 9, 2017

Transaction matching of around two million records in under 5 minutes in ARCS

Oracle Account Reconciliation Cloud Service (ARCS) with Transaction Matching is a cloud based reconciliation platform with pre-built configurations and adherence to industry best practices; a recommended solution to cater to your reconciliation and matching needs.

Transaction Matching is a module within ARCS which inherits the features that facilitate preparation and review of reconciliations.

  • Additionally, Transaction matching adds efficient automation of the detailed comparison of transactions in two or more data sources
  • The calculation engine allows for intuitive "netting" of transactions within each data source to provide output which is easy to work with
  •  Flexibility in the setup and timing of the process allows to minimize the effort during "crunch time" and reduce risk

 

Transaction Matching Use Cases

Typical Transaction Matching Use Cases are shown below.

 

Use Cases.jpg

Often clients need to match more than million records between two source systems with complex match set rules. We have seen clients spending hours to try to manually match them in excel or use some solutions like Access database, Oracle tables etc. which can be very time consuming and have data quality issues. We will share our experience and some insights on how we successfully loaded and matched two source files with around 2 million records in less than 5 minutes using Transaction matching feature of ARCS for one of our e-commerce client.

Idea Inception

Client wanted to match up to 2 million records from their point of sale system (POS) and the details obtained from Merchant transaction system. They were using access data base for this activity which was giving them results in hours and they reached out to Infosys with this requirement to help them streamline this time-consuming and frustrating process.

 

Solution and Approach

Source Files.

1. Point of Sale transaction file.

    The POS file had 9 columns and the file provided was in txt format (a pdf report converted into a text file). Below is the snapshot of the same.

POS.jpg

2. Merchant system transaction file

           The Merchant system transaction file had 21 columns and the file was in csv format. Below is the snapshot of the file.

Merchant.jpg

Matching rules

Client wanted the matching rules to be based on the condition that the card number and the amount from POS transaction file matches against the cardholder number and amount from the Merchant transaction file with the stipulation of many to one transaction match where many transactions from Point of Sale system matches with single batch (grouped by amount) transaction from Merchant system file.

 

Initial Challenges

The initial challenges with this requirement are below

1. Size of File.

    The size of the files provided were huge as there were 9 and 21 columns respectively and both the files had around 2 million records resulting in file sizes of > 1 GB per file. This much large a file is difficult to read and edit by any text editor.

2. Formatting

    Another bigger challenge was formatting the given files as per ARCS transaction matching needs. The files provided were in text format and to read and format them given their file size was a tough nut to crack.

 

Infosys Solution

We took this challenge and delivered as promised. The biggest challenge was to import the file containing about 2 million transactions into the ARCS Transaction matching from both the system and match them automatically in quick time. Other tools and custom solutions were taking hours for this process. Importing 2 million records in a csv file is a huge input for any system to ingest. It would typically take anywhere between 15-30 minutes just to import one file into a system. We had another challenge in formatting the files because the file we received was a .pdf file converted into text format and we needed them to be converted into .csv to be accepted by ARCS Transaction Matching. We used Oracle ARCS TM, formatting tools, text editors and Oracle provided EPM Automate utility to format the files, automatically ingest and auto-match the files from two transactional systems.

 

The EPM Automate Utility enables Service Administrators to remotely perform tasks within Oracle Enterprise Performance Management Cloud instances and automate many repeatable tasks like import and export metadata, data, artifact and application snapshots, templates, and Data Management mappings.

 

Tips and Lessons Learnt

With the above requirement's implementation, we have learned a few lessons and below are some tips when implementing similar type of solution.

  • ARCS TM also accepts .zip format input files, hence compress the files into .zip format so that they are smaller in size plus quick and easy to upload on the ARCS cloud.
  • Powerful text editors like Notepad++ or Textpad when formatting the files, could be used.
  • Create custom attributes which can be used in matching rules for faster auto-matching of transactions.
  • If possible, try to get the export from the transactionsystems in .csv format to reduce conversion times.

Performance Metrics

Below are our performance metrics while implementing client's requirement of matching around 2 million records using Oracle ARCS Transaction Matching.

 

Import POS million records - 27 seconds

Import Merchant million records - 61 seconds

Run Auto Match - 53 seconds

 

Complete Process - 2 minutes 21 seconds (Less than half of 5 minutes)

 

Result?

 

Happy client and Happy us.

 

We deliver!!!! - Please visit our company website to know more about our Account Reconciliation and Transaction matching solutions.



November 8, 2017

Emerging Trend in SSHR- PART3

Key Players in the HRMS Self-Service


  1. Oracle Self-Service Human Resources (SSHR) - Oracle Self-Service HR is part of Oracle Human Resources Management family of applications, and integrates seamlessly with other Human Resources applications, including Human Resources(core),HR IntelligenceLearning ManagementPerformance Management and Compensation Workbench.
  2. Applaud Self Service HR - Applaud System is best system made by Oracle experts that enhances Oracle HR Self-Service with an intuitive interface & mobile experience for employees and managers. It is simplified system used by desktop & mobile users.

Enhancements needed in the Oracle Self Service future edition

 

Following best ERP practice, Oracle E-business Suite Self-service HRMS application is overall based on extensive customer feedback, analyst research, experts' challenges & Oracle's own commitment to drive leadership. As per our recent experience in HRMS implementation projects, listing some areas that attracts customer's requirement & need further enhancement in the tool . Some of them are discussed below:-

 

1.       Introducing Employee Probation as function in self-service

The function should be available with Managers /Administrators or HRMS professionals. In certain industries, it is observed that employees have to complete Probation period based on multiple round of evaluation done by managers during different phases. Managers & administrators should be given enough flexibility to set expectations for employee to provide feedback against those expectations.

 

2.       Configuring Reminders

Oracle SSHR should give the flexibility to send reminders where the number of reminders should be configurable. Once reminders are complete, application should take one of the following paths:-

a.       Send the transaction back to the initiator

b.       Send the transaction to next person in approval chain

 

3.       Better User Interface and validations

There should be way to control the display of fields if any of the function is defined as Special Information Type in self-service via personalization. In several cases, we need that an employee should not see certain fields however the same function when accessed form Manager self- service should see the complete list of segments in a function. Personalization should be more flexible and user- friendly in controlling display at different levels along with setting preferences in HRMS system.

 

4.       Enabling validations for 'Special Information Types'

Currently when any SIT is defined as Self-service function in Self-service page, it doesn't support the validations. Because of this, mostly Self- service functions are configured as Extra Info Types where we can apply user hook validations and control functionality as per requirements. EIT's if compared with SIT is more flexible to capture in Self- service. However SIT is user friendly, so we should ensure SIT's to be more flexible in future edition.

 

5.      Develop Oracle SSHR as standalone Mobile App

Currently external systems like Applaud is integrated with SSHR to enhance the user interface and make it accessible with Mobiles, Tablets, etc. However, the system should be flexible enough to create App preferences to access different functions anytime, anywhere and from any device.


Summary at a Glance

HRMS Self Service application is significant for any Industry as it supports HR Best Practices. Organizations are not interested in impressive reorganizations and superficial plans that fail to improve upon core processes. A highly productive workforce depends on driving technology and automation. In the emerging era, this product is not likely to abate anytime in near future & perhaps not ever.

 


 [CJ1]just check the sentence

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