Access Management 

DataFlow

Overview

The dataflow can be divided in 3 main steps:

1. check that no other run are in progress (a) and then extract data from BW to PCM 
   1. Extract master data in full mode to csv files through openhub
   2. Load FIAR and CAMS data into specific DSO build for PCM project (DBFIAR20 and DBFIAR21),then extract to csv through openhub
   3. Load the data from the file via Talend 
2. treatment on PCM GCP
3. Load full with deletion DPFIAR13 from Big Query with new data source DTS_FI_PCM_01 by PC_FI_PCM_10. SQL server was replaced by Big Query

BW to Talend

DBFIAR20 loading process

Big Query to BW

DPFIAR13 data loading

Data source DTS_FI_PCM_01 get from remote source GBQ_Predict_Credit and get from table core_perimeter_future_bw (GCP project predict-credit-mgt-v2-prod)

Report to get back from BigQuery after calculate by Data Science

WIth new version 2.0, BW get only 3 key figures

PRED_NOT_PIM     → K_PFNPI
PROBA_NOT_PIM  → K_PPNPI
AMOUNT_EUR      → 0DEB_CRE_LC

Note: DPFIAR14  is obsolete

Architecture Overview

Obsolete 

SQL server was replaced by Big Query and after files are generate, they will be loaded by Talend by Data Engineering team

Objective of the application

Provide predictive information on Credit Management.

• Define which payer is a priority based on its history and the due amount.

Tool Leader: David TONDA

IT leader of the application: Guillaume THEVENET

Name of project: PCM Predictive Credit Management

PMO Project: 6958 Big Data for Credit Management

Reporting Coordinator: David TONDA

Usage information

Number of users: tbd

Critical period: none

Geographical perimeter: worldwide

InfoArea:

• All objects are stored in FIAR infoarea: IA_FMCO_FIAR
  
  

Process chain Display Component:

• 134 - PROJECT - PCM
  COMP_PCM
  

History

In Mar 2020, the data flow was updated to PCM 2.0

In 2021, BW change the source system SDK_PCM (SQL) to BigQuery(#4749200)

In Feb 2023, Po2 project requires to segregate data of Eco/Sco, therefore, company master data file is modified to add C_AUTHMA(authorization scope) to the openhub OH_PCM_05

Technical Rules on Workbench

The whole process can be summarized has follow:

• Extraction of BW data (master and transactional data) in flat files (csv with "|" separator)
• copy and loading of these file into a SQL database
• Calculation of predictive information on SQL side to produce two table which define Priority per Amount & Priority per Payer
• Loading of these data in BW to be used on standard reporting

Openhub

Updated on 12 Mar 2021: 18 Openhub (2 Transactional and 16 Master data)

All master data openhub are loaded in full mode. All extract data from master data except the TCURR one which is connected to a datasource.

All transactional data openhub are loaded in delta mode. (remark delta is not possible with multiprovider).

All openhub use a "|" separator because some field already contain ";" in the value and openhub doesn't encapsulate data.

All openhub use logical file name defined through FILE transaction. All files are stored in the following folder

Reporting

Dependencies with other applications

We should have the information where the application is sending or receiving information (e.g. APD open hub) 

Data Loading

Info Providers and objects loaded 

PC_FI_PCM_07 (Main PC) modify by ticket 5915436

  PC_FI_PCM_01 Generate 18 files from Open Hub by job RSPROCESS weekday at 10:00 AM CET

  PC_FI_PCM_11 Same as PC_FI_PCM_01 just in case 01 can't generate files completely

  PC_FI_PCM_10 Delete DSO then load data to DPFIAR13 from BigQuery  and DPFIAR14 from SDK_PCM  job RSPROCESS weekday at 11:00 AM CET

  PC_FI_PCM_V2 generate 1 file:/exploit/BW/PREDICTCM/V2/dbfiar20_<DATE>_<TIME>_delta.csv from Open Hub by job RSPROCESS 3 times( 7am, 1pm , 7pm CET) per weekday

Target folder

Loading frequency

  PC_FI_PCM_01 load by job RSPROCESS workday at 10:00 AM CET

  PC_FI_PCM_10 load by  job RSPROCESS workday at 11:00 AM CET

  PC_FI_PCM_V2 load by  job RSPROCESS workday at 7am, 1pm , 7pm CET

Average performance

Record Keeping

DSO are loaded with full historical data but we only send today - 3 years to SQL server.

Detail of process chain, list + link between or special event done for the loading

Data Quality Control

Operational Documentation

Procedures

If the service account:bqtobw@predict-credit-mgt-v2-dev.iam.gserviceaccount.com in Google Cloud Platform is expired, then the configuration of remote source:GBQ_Predict_Credit in BW/HANA should be adapted accordingly.

1. Copy the new JSON file to the folder defined in gbqadapter_prod.properties on dp agent server (acew1dhcahca1)
2. Change the KeyFilePath to the folder of the new JSON file (JSON file provide by DataOps team: dataops@solvay.com)

Remote source in BW configuration is not required to change.

The properties file in dp agent server is required to change if the project name or the location to keep the JSON file is changed.  

The new JSON file must be the same as the detail in the properties file at KeyFilePath

Scheduling

<Describe the scheduling in place for the application (eg. existing jobs, trigger time/event based, dependencies)>

Monitoring

<Describe the monitoring checks to confirm the application is performing well (eg. check the overall status, check performance metrics like runtime/data volume/memory/disk/CPU, maintain and react to alerts/notifications)>

Error Handling

<Describe how to handle errors (eg. error codes, description and respective resolution, alert users)>

Known Bugs

<List the existing bugs, its criticity, workarounds and resolution plan.>

Roadmap