appMDMTM

Brochure

appMIGRATETM

Brochure

Data Migration Platform

appTM

MIGRATE

DATA RECONCILIATION

DATA PROFILING

DATA COEXISTENCE

DATA MAINTENANCE

DATA QUALITY

MANAGEMENT

CUTOVER PLANNING

AND EXECUTION

DATA MIGRATION

Data migration done in the traditional way, writing your own conversion programs, is a painful and expensive proposition. Conversion programs don’t get ready before approximately six months into the project, pushing the exercise of examining data for correctness and standardization too close to the Go-Live date. Data quality issues do not get the needed attention.

“Data Conversion was a big part of enabling our successful milestone, ‘System Integration Testing’. Chain-Sys overcame many challenges, shortened the conversion cycle and completed conversions on time.”

-CIO of a major iconic EnergyCompany

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Problem

Solution

appMIGRATETM

Field proven appMIGRATE provides instant relief for data migration challenges. Being a product with ready to use configurable templates with no need for programming, appMIGRATE allows Business Users to see production data in the target instance as early as the first test cycle. It gives them ample time to correct, clean, consolidate, standardize and harmonize their data. The tool plays well with agile methodology. Data risks are identified early in the project and solutions made ready and applied.

The tool reduces production cutover time and the overall project timeline. appMIGRATE product and processes are battle tested. It helped several fortune 1000 companies including GE, Cummins, Caterpillar, Iron Mountain, Canon, CH2MHill, Lifeway Christian Resources and others to migrate their complex data in a scalable and repeatable manner.

The appMIGRATE Solution with 1000+ ready-made templates provides accelerated data conversion and ensures data quality. The appMIGRATE Solution has been recognized by the industry and is being utilized by Fortune 1000 companies for meeting their challenging data conversion requirements.

appMIGRATE tool provides end to end data migration processes right from Requirements Definition to successful Cutover. All these processes and activities come built inside the tool, allowing data migration SDLC processes to become repeatable, scalable and predictable.

“Never before we had all data converted before the first test cycle. With this tool and the methodology, we are free to concentrate on other business and process issues.”

-ERP Practice head of a majorSystems Integrator

Product Architecture:Template Adapters Interface Adapters Extract Adapters appLOAD Adapters Log & Notification

Handler

appMIGRATE

Schedule Engine appEXTRACT Service FTP Service appLOAD Service Log & Notification Handler

appINTERFACE

Template Processor Loader Processor Pre-validation Engine Error Correction Cleansing Handler

appLOAD

Instance Handler Data Processor Validation Engine Log & Notification Handler

Template Adapters

BASE COMPONENTS

Query Parser Extract Engine Error Handler

appEXTRACT

Accelerated ETL:

EBS LEGACY SAPSALES FORCE

DATA MART

TARGET*

TARGET*

DQM/MDM LOAD/DELTA LOAD

EXTRACTION

CLEANSE/TRANSFORM

Automated documentation for Audit & Reporting

Compare with target

Predefined Load

Predefined Extract

EXTRACTION

Ready-made extraction templates will provide earlier view of the source data in the Data Mart.

Predefined extraction templates available for Master and Transactional data (both open and historical)

All data fields are extracted from Legacy Systems

Raw data is profiled and map reduced using Hadoop

Ready-made templates accelerate target instance mapping

CLEANSE/TRANSFORM

Data is pre-validated prior to loading into target Oracle EBS/SAP environment

Automated sequencing of Data migration objects

Preserves the data linkages for all dependent data elements

Raw data is profiled and map reduced using Hadoop

Repeatable and flexible Change Data Capture(CDC) Cutover

HISTORICAL CONSIDERATIONS

Post processing builds reference to historical source

Pre-built historical sequencing of master/transaction data

Front-end screen to build historical mapping

Integrity for historical drill-down to the transaction level

Dimensional reconciliation engine for source and target

Includes standard fieldsIncludes user defined fields

* Oracle Cloud Applications or Oracle E-Business Suite or SAP ECC 6.0 or SAP S/4HANA or Other Enterprise Systems

appMIGRATE Architecture:

“For a large document management company we reduced Item Master data size to about 5% of the original size.”

Data Profiling approach :

DATA MART

ANYSOURCE

DATAPROFILING AT SOURCE INSTANCE

DATA MART

DATAPROFILING AT TARGET

Raw Data

Corrected Data

Clean & Lean Data

Hadoop

appMIGRATETM

Data Profiling

“appMIGRATE performs data profiling on the source data to reduce the data volume and explore data quality issues. Data profiling is done with the extracted data against the target Applications Reference data and Setup data dependencies with predefined rules. Business process verification is another highlight. Data profiling engine is also used for on-going ERP wellness activities”

Profiling source data improves data quality and reduces data quantity. Profiling the extracted data against the target reference data and business logic is built inside the appMIGRATE tool. Each Template comes packed with hundreds of pre-validations.

appMIGRATE helps investigate if existing data can be used for other purposes.

Improves the ability to search the data by tagging it with keywords, descriptions or assigning categories.

Allows assessment of risk involved in integrating data for new applications, including the challenges of joins.

Helps understanding data challenges early in any data intensive project, so that late project surprises are avoided. Finding data problems late in the project can lead to delays and cost overruns.

Provides enterprise view of all data, for uses such as Master Data Management where key data is needed, or Data Governance for improving data quality.

TARGET*

* Oracle Cloud Applications or Oracle E-Business Suite or SAP ECC 6.0 or SAP S/4HANA or Other Enterprise Systems

“DQM is a prime mover of any successful Data Migration project. It is a mandatory process and cannot be wished away.”

appMIGRATE provides extensive features and functions for Data Quality needs of Data Migration projects. The major features offered include:

Data Quality Management

appMIGRATE Data Migration process specifies Data

Data De-Duplication

Data Cleansing

Data Harmonization

Data Consolidation

Data Enrichment

Data Standardization

ANYSOURCE

Raw Data

Corrected Data

DATAMART

DATAPROFILING

Hadoop

INSTANCE

Data Cleansing Data Consolidation

Data Enrichment Data Standardization

Data Construction

+

Quality Management activities as “Mandatory” for all Data Migration projects. The DQM activity is generally carried out in the early phase of the project and it is a precursor to Data Migration activities. The appMIGRATE tool has powerful features to collect high volume of master data into its data mart for performing DQM activities. It uses consolidation algorithms along with Hadoop technology to identify the matches and no matches for the collected data. Provides a good user experience in classifying the matches into “false positives” or “false negatives”. When the user merges the matching records, individual values can be copied from one to another. Using “Merge” activity, data gets harmonized using data cross references.

Data Coexistence

Enterprises do not adopt simultaneous “big bang” Go Live into a single ERP system from all their geographies and divisions. In a phased approach, existing data interfaces cannot be interrupted for the legacy systems, when feeder systems have already been migrated over. appMIGRATE Module fits the bill for quick interface building between systems, both batch and real time.

During ERP Implementations, appMIGRATE is used for building the integrations which are needed for the coexistence of the old and the new applications. The appMIGRATE Extract and Load Adapters are reused for the coexistence tasks.

Clean & Lean Data

TARGET*

* Oracle Cloud Applications or Oracle E-Business Suite or SAP ECC 6.0 or SAP S/4HANA or Other Enterprise Systems

Data Reconciliation

“Chain-Sys Reconciliation engine is used for validation of the Data Migration results. Also it is used for on-going ERP wellness activities”

Technical and Functional reconciliation is a mandatory step in Chain-Sys Data migration process. It ensures smooth transition to the target application. It also helps with the ongoing Data Maintenance efforts. appMIGRATE consistently delivers 99.999999% data reconciliation success in every project.

appMIGRATE tool provides out of the box data reconciliation processes and functions for both Technical and Functional reconciliations. The tool provides complete drill down capable dashboards for identifying the discrepancy between source and target systems. During cutover, appMIGRATE helps you with the reconciliation needs between Sub Ledger and Main Ledger (Finance and Cost). Within Sub Ledger accounting transactions and activities modules are tracked and reported using this engine.

“The reconciliation on USD 500 million came to USD 7. The CFO pulled out USD 7 from his pocket and presented it to the CEO during go live. The technical team worked on it later and brought reconciliation to zero.”

LOADINGLoading into Target, Build Cross Reference

VALIDATE AND TRANSORM

Data Mart, Simulation,Bulk Transform

SOURCE RECONCILIATION

Extracted Vs Transformed

EXTRACT SOURCE

Database, File Systems,Queues, Webservices

TARGETRECONCILIATION

Extracted vs Loaded,Fieldwise, Dollarwise, Quantitywise etc.

General Ledger Journals Reconciliation Results with Drill Down features (Periodwise, Journal Categorywise, Journal Sourcewise, View overall data, View Mismatch data):

appMIGRATETM

“appMIGRATE achieved a record 3 hours cutover time at a very Transaction Intensive major Travel site.”

Cutover Planning

“appMIGRATE Cutover has always been smooth – with no data issues after Go Live.”

appMIGRATE provides features and functions for a smooth cutover. Smooth cutover is achieved by a combination of features including: Change Data Capture, Data Scalability functions and Configuration Management.

Change Data Capture

The appMIGRATE product offers powerful Change Data Capture functionality. Using this feature, the source application tables redo log files are monitored at a scheduled time frequency and the changes are moved into the Change Data Capture tables. From the Change Data Capture tables, the data is extracted, transformed and loaded into Target Application. appMIGRATE offers Templates for “Update” of the data entities along with “Create” option, which will be used for updating the target Application. Templates for timestamp based CDC are available.

Data Scalability Functions

For Data Migration situations of large data volumes, complex validations and intricate transformations, appMIGRATE offers the following features:

“appMIGRATE successfully processed over 520 Million records of installed base for a major appliances brand in USA”

Clustering multiple application servers to load balance

Create multiple JVMs under the application server to process more threads

Process Extractions in parallel and Process Loads in parallel

Execute multiple threads simultaneous based on number of cores and processors

Split the loads into smaller batches of data and process in parallel

Reduce the IO against the database drastically

CLUSTER

MULTIPLE JVM

PARALLEL PROCESSING

MULTIPLE THREADS

SPLIT PROCESSING

MERGE OPTION

FEATURE DETAILS

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Copyright © 2016 Chain-Sys Corporation

CHAIN SYS

Define Data Object, Attribute, Validation, Transformation and Cleansing Rules and Requirements

appMIGRATE Adapters are Configured

appMIGRATE Loader is Configured

appMIGRATE Server

Initial Purging, Archiving, Cleansing Transformation and Pre-Validation is Performed

Target Update Data File

Upload Programs areExecuted

Target System

appMIGRATE DataStaging Table

Data is ManuallyCleansed andTransformed

Purge and ArchiveData Files

Error and Exception Reports

Errors are Corrected

Source Systems

appMIGRATE process diagram:

appMIGRATE DataStaging Table

Pre-Validation is Performed

Target System

MDMTM

appMaster Data Management

There are multiple challenges with traditional Master Data Management approaches. The products and processes are cumbersome to implement. They need many other add on tools and technologies for making the core MDM product to work. The MDM products are compartmentalized by domains such as: products, customers, suppliers etc. Most MDM solutions are tightly coupled with the vendor’s own ERP products. It takes a long time for implementation mainly due to activities such as Analysis and Discovery for the Hub Data Model, Configuration and Development of the Hub, Creation of the workflow governance for Activation, and Approvals and Confirmation for create/update of the master data. Traditional MDM Products do not offer industry specific solutions for the master data attributes and inter dependencies of the attributes, which leads to a long time taken for the clients to create attribute mappings. Due to these shortcomings, many enterprises are apprehensive about implementing traditional MDM products for their businesses, even though they are fully aware of the benefits of MDM.

? Problem

Chain-Sys has critically analyzed the above problems and offers a complete MDM Product, appMDM™. appMDM™ focusses on and satisfies all the MDM processes. It is highly configurable and enables master data on-boarding and maintenance. appMDM™ provides industry focused templates for all verticals. The unique and powerful templated approach for Hub modeling and configuration helps you to create a complex Hub within hours rather than months. The Cloud enabled integration engine enables you to connect the MDM Hubs with Mobile, On Premise and Cloud Applications with no programming for both in bound and out bound transactions. The inbuilt features support high volume scalability and complex business validations for your data management needs. appMDM™ customers are getting full comfort with their master data quality and data governance policies, with the unique “Get Clean Stay Clean” preventive control approach. appMDM™ satisfies the end to end Master data management process and system needs.

? Solution

Cloud Enabled.

Single Product solving all MDM challenges.

Accelerated implementation using templated approach.

Minimized data risks and Improved Security.

Improved data quality and data ownership.

Approval Workflows for assured data success.

Integrates with Oracle E-Business Suite, SAP, MS Dynamics, SFDC, Chain-Sys ERP, PeopleSoft, JD Edwards, Oracle Fusion Applications, and Oracle Cloud Applications.

The value propositions:

A Single Source System is designated as the “System of Record” for Master Data.

MASTER DATA MANAGEMENT

Chain-Sys provides a configurable Platform for users to create their Data Model, User Interfaces, and Business Validations for the MDM Hubs. The Platform automates the code creation for the MVC architecture. The Data Architects can create any complex Data Hubs using this platform rapidly.

CHAIN-SYS PLATFORM

Chain-Sys Platform:

Chain-SysPlatform

Multiple DomainHubs

No Programming

Data QualityManagement

appMDM provides “Central Data Hub” to process Master Data Maintenance Transactions (Add, Change, Archive, Purge).

A “Master Data Governance” group controls the Master Data Management process and safeguards the data.

appMDM consolidates master data from multiple sources into a Central Data Hub (Data Mart) using Data Quality Management features. The Data Hub allows consolidated reporting and query of master data, inventory, cost, and account balances etc.

Work Flow functionality supports data governance and approval processes and procedures.

Control of privileges at organization/object/attribute level ensures data integrity.

DM with

appMDM provides complete flexibility on the Domains. It provides the following out of the box domains for Products (Products, BOM Structures, Formulas, Routing, and Recipe), Contacts (Customers, Customer Sites, Customer Contacts, Suppliers, Supplier Sites, Supplier Contacts, Employee and Employee Contacts) and Operations (Fixed Assets, and GL Code Combination). Designing a custom domain is easy. Users can create domain hubs for their specific needs with no programming efforts, by simple configurations. Chain-Sys strongly believes in the template based approach for creating Hubs. appMDM provides templates for all their standard domains against major applications such as: SAP, Oracle EBS, Oracle Fusion, JD Edwards, PeopleSoft, Microsoft and Chain-Sys ERP.

MULTIPLE DOMAIN HUBS

Screen Design Workbench:

Build MDM Hub easily using Chain-Sys Platform:

Product Hub rapidly created using Chain-Sys Platform:

Chain-Sys provides a state-of-the-art Data Management tool for configuring Migration and Integration objects. Chain-Sys offers the Industry Gold Standards: appMIGRATE and appINTERFACE tools for performing the Data Migration and Integration for MDM efforts.

appMDM DATA MANAGEMENT – NO PROGRAMMING, SIMPLE CONFIGURATIONS

Outbound Interface to Consumer Application:

The appMDM’s Data Management solution satisfies complex data management needs such as: Data Profiling, Data Assesments, Data Synchronization, Change Data Capture, Data Harmonization, Data Visualization and Data Classification.

Design and maintain the enterprise data model that supports desired business application landscape and capabilities

Ensure that Data Management efforts (Business or IT) are accelerated and consistent with enterprise core process performance

Accountable for data quality; resolve information and cross process issues

Enforce global data rules and standards monitoring master data quality metrics and initiating corrective actionCorrect Pre-validation Errors

Maintain an enterprise wide consolidated “data mart” for reporting , query and analysis

Establish a centralized Data Governance Organization to:

appMDM’s Data Quality Management comprises Data Consolidation, Data Standardization, and Data Harmonization activities. Consolidating the data into the Hubs is a critical activity. The system collects data from multiple source systems and sends it to target MDM Hubs to perform Consolidation. Hadoop technology is extensively used. appMDM provides the “Matches”, and the Data Stewards or the Data Owners can classifythe matches as “False Positive” or “False Negative” and perform the merge, drop or migrate actions.

DATA QUALITY MANAGEMENT

Source System

appMDM

appMDM Governance

System ofRecord

appMDMData Steward

ConsumerSystem

Workflow

Extract newMDMTransactions

Corrected andApprovedTransactions

Extract andWorkflowNotify

Updated withLocal Attributes

“Work Flow functionality supports the data governance and approval processes and procedures”

Chain-Sys provides multiple roles to the MDM users such as: Operations, Data owner, Data Steward, Data Guardian, Data Architect etc. All these roles are used in configuring the workflow for any new Master Data introduction into the hub and also for processing the inbound master data that is interfaced from other Consumer Systems.

DATA GOVERNANCE

Data consolidation engine is key for identifying duplicate data and consolidating them. Data harmonization is achieved using data cross referencing of merged data against parent data. The data consolidation engine uses multiple string based mathematical algorithms to identify the groups for de-duplicates. It also identifies matching percentage for the match records. The matching percentage should be equal or greater than the threshold percentage assigned to the consolidation project task. If the data comes up with less than the threshold percentage, the system marks them for No-Matches.Data owners get an opportunity to review the apMDM dashboard for the results of the consolidation project execution and can drill into the Matches and No-Matches data. They classify data for merge, migrate, drop and on hold. Figures below illustrate data consolidation. Main screen shows process summary results, and the Consolidation Results screen shows the results for sample Customer, “Alcoa”. The results are used for merging, dropping and migrating. Data hierarchy for the Customer and Supplier data are also established.

Data Consolidation - Process Summary and Match/No Match Dashboard

Consolidation Main Page:

Consolidation Result for Companies related to “ALCOA”:

Shows the results of the data consolidation for “ALCOA”:

www.chainsys.com1-855-appLOAD Option 1

Copyright © 2015 Chain-Sys Corporation

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