Quais são os principais passos para preparar seus dados para a migração do ERP?

I agree with this statement. Regarding data profiling tools, there are a number of tools that can be used including simple SQL queries and tools that support such queries. But for more complex data analysis, tools such as SF Tableau, Qlik, or MS PowerBI offer many data visualization capabilities that raw queries can't provide.

Let’s say a manufacturing company is migrating to a new ERP system. First, they assess their current inventory data, which includes thousands of product entries, some of which are outdated or duplicated. They clean this data by removing obsolete products and correcting any errors. Next, they map the cleaned data to the new ERP’s format, ensuring that fields like product codes and descriptions align with the new system. Before proceeding, they back up all their data to prevent any loss. After migration, they test the data in the new ERP to ensure that all product information is accurate and properly categorized. Finally, they train their team on using the new system, so they can quickly adapt and maintain smooth operations.

When discussing data migration, the first step is to classify data based on the media it is stored on, such as digital documents, databases, or paper records. This helps us understand which data should be migrated first based on its current usage and impact on business processes. Particular attention should be paid to data that requires more attention in the business process, eats up more of the employees’ time. It is also important to consider “non-existent” data – information that is critical but is currently missing from our data sets. Early identification of these gaps can direct our migration strategy not only to data migration, but also to its improvement and completion.

In every ERP deployment project that I have worked the data migration scope is a key risk and challenge for organizations transitioning to a new ERP system. From my prior experience, typical challenges often circle around outdated and data inconsistency across various systems or departments. Approaches to address these challenges include data assessment, data mapping, transformation, and data cleansing to enhance data quality before migration, establishing robust data governance practices for maintaining data integrity and quality, and employing specialized tools to ease the data mapping and transformation during the data transition process.

Establish clear data quality metrics and reporting mechanisms to track the effectiveness of data cleansing efforts and ensure ongoing compliance with quality standards.

To cleanse your data for ERP migration, follow these precise steps: Audit: Identify all data sources and understand the current data state. Remove Duplicates: Eliminate duplicate records. Standardize Formats: Ensure consistent data formats. Validate: Verify data accuracy and update as needed. Enrich: Fill in missing information. Delete Irrelevant Data: Remove unnecessary data. Governance: Establish data management rules. Test: Run tests with the cleansed data before full migration.

While emphasizing the importance of cleansing data for accuracy, completeness, and relevance, it’s crucial to also consider the operational implications of data management. In particular, we must focus on both the data available and the time employees devote to managing this data. Areas requiring excessive management time are prime candidates for optimization, as they are often the most susceptible to errors. By targeting these data points during the cleansing process, we can not only enhance data quality but also streamline operations, reducing the likelihood of mistakes and improving overall efficiency.

In addition, frequently the best place to cleanse data is in the legacy/source systems it resides in, and to do this well ahead of the ERP launch. This gives the advantages of clean data in legacy as well as the new ERP system. The catch here is that some legacy systems can't control the integrity of that cleansed data, which is often why the data got dirty to begin with. In such cases, manual procedures in the legacy systems can often be used for short time periods to keep the cleansed data clean. In some cases, this is not possible, and more sophisticated routines for cleansing the data immediately after extract from legacy systems and before import into the ERP need to be employed. This is risky and should be avoided if possible.

Cleaning up data before an ERP data migration is paramount to the success and efficiency of the implementation process. Poor data quality, including inaccuracies, duplicates, and inconsistencies, can significantly hinder the effectiveness of the new ERP system, leading to operational inefficiencies and decision-making errors. By conducting thorough data cleansing activities, organizations can ensure that the data being migrated is accurate, reliable, and consistent, thus minimizing the risk of data-related issues post-implementation. Cleaning up data also streamlines the migration process by reducing the volume of unnecessary or redundant data, which in turn helps minimize migration time and costs.

At this stage, it is assumed that the ERP system has been implemented or developed taking into account the requirements of a specific business (all typical business models are present)

When preparing your data for ERP migration, focus on these key steps: Data Inventory: List all data sources and types. Data Cleaning: Correct errors, remove duplicates, and ensure consistency. Data Mapping: Align old data fields with the new ERP system’s structure. Data Validation: Check that data formats meet the new system’s requirements. Testing: Perform test migrations to catch and fix issues. Backup: Secure a complete backup of all data. Final Migration: Transfer the data and verify its accuracy. This structured approach will help ensure a smooth ERP data migration.

Develop a comprehensive data mapping strategy that encompasses not only the technical aspects but also the business requirements and objectives. Beyond simple field-to-field mapping, consider the broader context of how data flows and interacts across different modules and functionalities within the ERP system.

In addition, you also want to map how data will factor into your reporting and business intelligence needs. The data only has value if it can be reported to provide real-time insights into business results and trends. Predictive analytics, business intelligence, and artificial intelligence all require clean data as inputs.

Mapping your data during an ERP data migration involves the process of identifying, categorizing, and structuring data from the existing system to match the format and requirements of the new ERP system. This entails creating a blueprint or roadmap that outlines how data elements from the old system will be transformed and transferred into the new system. Data mapping involves fields, tables, relationships, and business rules between the old and new systems to ensure a seamless transition of data. Mapping your data is crucial for maintaining data consistency, integrity, and usability in the new ERP system.

Running a test import and validating the results are essential steps in ERP data migration to ensure the accuracy, completeness, and integrity of the migrated data. Testing the import process allows organizations to identify and address any potential issues or discrepancies before migrating data into the production environment. By conducting a trial run with a subset of data, organizations can evaluate the effectiveness of data mapping, transformation rules, and migration procedures, thereby minimizing the risk of data corruption or loss during the actual migration.

Migration is an extensive and intricate process, requiring a meticulous verification approach to ensure seamless integration into the new system. It's essential that both business stakeholders and technical specialists collaborate closely to develop a robust testing methodology that maximizes efficiency and minimizes effort. This methodology should encompass a phased approach where testing phases are clearly defined—initial tests are conducted, outcomes are reviewed, and subsequent tests are iterated based on findings. This not only assures the technical integrity of the migration but also maintains business continuity.

Test your data: After migrating the data to the new ERP system, perform rigorous testing to ensure its accuracy and functionality. This involves: Data Integrity Checks: Ensure no data has been lost or altered during migration. Functionality Tests: Verify that the data works correctly within all relevant processes and modules of the new ERP system. User Acceptance Testing (UAT): Involve end-users to test the data in real-world scenarios to confirm it meets their needs and expectations. By thoroughly testing your data, you can identify and address any issues before fully deploying the new ERP system, ensuring a smooth transition and reliable operation.

Before the big move, do a trial run. Create a test environment and migrate a sample of your data. This allows you to identify any issues with your mapping or data quality that you might have missed. It's like a dress rehearsal before the main performance, giving you a chance to fine-tune your approach.

It depends on what kind of migration it is... It's possible to do it from the bottom up( like many other things in life :) ) Is a single field compatible with the new data types? Maybe a conversion is needed. SAP, for example, has domains that hold optional values. From the technical requirements - do we have a full key with valid values for a single record Does the above record qualify as a business transaction with all the system validations? To complete an E2E process, can we complete multiple records from the steps above We should also validate integrations - maybe the records came from another system some of those activites can be done in parallel with a smaller population

On Day 0, the day we transition to the new system, choosing the right timing is critical to minimize disruption. It's advisable to select a period during which business operations can afford to be temporarily suspended to facilitate a comprehensive data refill. This ensures that we can manage the migration smoothly without impacting daily business activities unduly. Moreover, securing robust backups is crucial at this juncture—not only of the existing data in its current format but also immediately post-migration. This dual-backup strategy safeguards against data loss and provides a fallback option, enabling a swift recovery should any issues arise during the initial stages of going live with the new system.

Key Steps to Prepare Your Data for ERP Migration: Assess Data: Review current data to identify what needs to be cleaned or updated. Cleanse Data: Remove duplicates, correct errors, and standardize formats. Map Data: Define how old system data will map to the new ERP system. Validate Data: Verify accuracy and completeness through testing. Backup Data: Ensure a full backup and recovery plan. Test Migration: Conduct a test migration with sample data. Train Users: Train your team on the new system and data procedures. Execute Migration: Perform the actual data migration. Review Post-Migration: Validate and review the migrated data for accuracy.

This is the main event - moving your cleaned and mapped data into the new ERP system. Depending on the size of your database and the complexity of your systems, this could take anywhere from a few hours to several days. Have a detailed plan in place, including a timeline and assigned responsibilities for your team.

Bei der Migration kommt der Faktor Geschwindigkeit immer mehr zum Tragen, wenn es um eine Kommunikation via API geht. Eine API validiert die eingegebenen Daten nochmals und ist somit viel langsamer als ein direkter Import in Tabellen einer Datenbank. Somit sollte die Migration in mehreren Schritten erfolgen: Die Stammdaten sollten bereits einige Tage vorher migriert sein und es sollte unmittelbar vor Go-Live nur eine Delta-Migration stattfinden. Ebenso die Bewegungsdaten. Offene Vorgänge sollten bewertet werden: Evtl. ist das als Schulungsmaterial für Anwender brauchbar, ein Import offener Vorgänge stellt alle Beteiligten immer vor große Herausforderungen. Das Projektmanagement sollte dafür sorgen, dass möglichst wenige Vorgänge offen sind.

Start by clearly defining the objectives and scope, detailing which data sets will be transferred. Engage key stakeholders and maintain regular communication throughout the process. Assess and prepare the data by profiling, cleaning, and mapping it from the old to the new system. Choose a migration strategy—big bang, phased, or parallel—based on your specific needs and risks. Select appropriate migration tools and define transformation rules for data conversion. Conduct thorough testing, including dry runs and user acceptance testing, to validate the migration process. During execution, back up all systems and perform the final migration at a low-activity time.

Validating data post-ERP migration is crucial for maintaining its quality in the new system. Through my journey, comparing and reconciling data meticulously between old and new systems proved invaluable in identifying discrepancies. Utilizing validation tools and engaging with stakeholder feedback highlighted areas needing refinement, enhancing data integrity. This process not only ensures smooth operational transitions but also reinforces stakeholder trust in the system's reliability. It's a critical step that should never be overlooked in the ERP migration process.

Once the migration is complete, it's time for a thorough check. Verify that all your data has been transferred correctly and is functioning as expected in the new system. Run reports, test processes, and have key users from different departments check their relevant data. This step ensures that your new ERP system is ready for prime time.

Ensure data completeness, accuracy, and uniqueness by checking for missing records, validating data values, and eliminating duplicates. Verify access controls, ensure audit trails are working, and confirm regulatory compliance. Log and categorize any errors found during validation, establish a process for resolving issues, and revalidate data and functionalities after resolving issues to ensure fixes. Maintain detailed documentation of all validation activities, findings, and resolutions, and obtain formal sign-off from key stakeholders confirming the validation process is complete. Implement continuous post-go-live monitoring to catch any issues that might arise and establish a feedback loop with end-users for ongoing system improvements.

validation from multiple aspects - data completness - smoke test - create transactions with migrated data - technical errors during the migration - validate balances before and after -validate authotizations to the data - review any manual interventions in the data during the migration

Backup: Always have a backup of your original data in case something goes wrong during the migration. Stakeholder involvement: Keep key stakeholders in the loop to ensure business needs are met and there is no interruption in operations. Training: Ensure users are familiar with the new system and any changes to data handling. Compliance: Make sure your data migration process aligns with data privacy and regulatory compliance requirements

One key task with Major ERP transformation/upgrade is to ensure adequate training is provided prior to the upgrade to the systems users to ensure smooth operations post migration.

Migration is a big word in the ERP world, some examples which are not the classic ERP to ERP migrations might be DB migration ( for example move for Oracle to HANA in SAP ), OS migration on a running ERP. Even a change between two versions of the same ERP might be considered a migration if the standard code changed. Understanding whether this is a technical or functional migration (introducing new functionality as part of the migration) will dictate a lot of steps