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Ditto Duplicate Data Checker

Ditto automates the dreaded data audit. Keep databases duplicate-free for an effective migration to S/4HANA migration or simply to maintain data quality in existing records.

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Doubled Data, gone in half the time

In today’s business landscape, data plays a crucial role in every aspect of modern enterprises. From operational tasks like invoice processing to strategic decision-making through analytics, data serves as the foundation for success. However, the presence of duplicate data can lead to erroneous analytics and payment errors, demanding extensive time and effort for rectification.

Ditto addresses these challenges head-on. Ditto utilizes intelligent algorithms to churn data and locate duplicates. It provides valuable insights into the current state of Master Data, equipped with powerful selection criteria and simplified data analysis. With Ditto, identifying and eliminating duplicates from master data becomes an easy and effective process, ensuring data integrity and accuracy.

Why Ditto?

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Accelerate monotonous data checks and ensure no duplicate data set goes unnoticed. Gone are the days of manually sifting through data sets manually. Ditto streamlines the process by presenting its findings for your approval or editing. Knowing that your data is accurate and well-managed, you can proceed with certainty in business decisions. Say goodbye to tedious data checks and embrace the efficiency of Ditto.

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Removing redundant information allows businesses to rely on reliable insights and make informed decisions based on clean, trustworthy data. This certainty enhances the effectiveness of decision-making processes and empowers organisations to achieve their goals with confidence, ultimately leading to improved operational efficiency and business success.

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As organisations transition from SAP ECC to S/4HANA before 2027, challenges and setbacks may arise. Data inconsistencies or duplicates can lead to significant time and financial costs. Given that S/4HANA is purchased based on storage usage, wasted space due to duplicate or erroneous data can be detrimental. Avoid these issues and ensure that all your data is valuable with Ditto. Streamline your data management and make the most of your storage by relying on Ditto’s duplicate checks.

The Ditto Process

Ditto removes risks and uncertainty from your database. Equipped with a robust selection criteria, it swiftly identifies duplicate or similar data values within minutes. Manually performing such tasks would typically take hours or even days. With Ditto, organizations gain confidence in their data quality, enabling them to make strategic decisions and proceed with operations more efficiently. Here’s how:

Upload Data

Simply upload your master data records into Ditto at once. This can be done as a one-off data cleanse or regularly if multiple data sources inform master data records. Configure the powerful selection criteria to choose the parameters of search. Set to find duplicates, or inversely, to find missing data.

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Run the duplicate check

Automate duplicate checks to run in the background whilst employees focus on other jobs. Once done, Ditto delivers an overview of your master data. Use Ditto to identify duplicates in the data as well as find missing values. This improves user experience and data governance in one automated step.

Action the duplicate checks

Ditto churns through master data with smart algorithms to identify duplicates on the set parameters and weightings. Once duplicates or missing values are identified, users have full control over how they are processed via a simple report. Consolidate, fix or remove data sets efficiently with a real-world tested UX.

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Once data checks have been completed and processed, you’re good to go. Whether you are undertaking a routine master data cleanse, migrating or archiving data, Ditto creates the confidence for organisations to complete this and move on to strategic activities.

Demo Ditto Today

Get in touch today to arrange a live session of Ditto in action. Run duplicate checks in real time and discover just how streamlined this aspect of your data audits can be. Improve your data-driven decision-making with Ditto!

SAP Duplicate Checks FAQs

In SAP, a duplicate check refers to a process that aims to identify and prevent the creation of duplicate data entries within the system. When users enter or import data, the duplicate check functionality examines the data against existing records in the database based on specific criteria, such as key fields or unique identifiers. If a potential duplicate is detected, the system will prompt a warning or prevent the creation of the duplicate entry, helping maintain data accuracy and integrity. The duplicate check feature is essential in preventing data redundancy and ensuring the consistency and reliability of information stored in the SAP system.

Master data duplicate checks are essential for several reasons:

Data Accuracy: Duplicate data can lead to inconsistencies and errors in reports and analytics. By identifying and eliminating duplicates, organisations can ensure data accuracy and make informed decisions based on reliable information.

Cost Efficiency: Duplicate data occupies unnecessary storage space, which can lead to increased storage costs. By conducting duplicate checks, organisations can optimise storage usage and reduce associated expenses.

Process Efficiency: Duplicate data can create confusion and inefficiencies in business processes. With accurate and unique master data, operations become smoother and more streamlined.

Regulatory Compliance: Some industries have strict regulatory requirements concerning data accuracy. Master data duplicate checks help organisations comply with these regulations and avoid potential penalties.

Customer Satisfaction: Duplicate records can lead to inconsistent customer information, affecting service quality. By maintaining clean and accurate master data, organisations can enhance customer satisfaction and trust.

Data Integration: Duplicate data can complicate data integration efforts, leading to data conflicts and synchronisation issues. By identifying and resolving duplicates, data integration processes become more seamless.

Decision-making: Reliable master data is crucial for sound decision-making. Duplicate checks ensure that decision-makers have access to consistent and reliable information, leading to better outcomes.

Overall, master data duplicate checks play a critical role in data management, enabling organisations to maintain data accuracy, optimise processes, comply with regulations, and make informed decisions.

You can identify duplicate data using various methods and tools depending on the specific SAP module you are working with. Here are some common approaches to identifying duplicate data:

Manual Review: Manually review the data in SAP transactions or reports to identify potential duplicates. Look for identical or similar entries based on key fields or unique identifiers.

SAP Standard Reports: Many SAP modules offer standard reports to find duplicate data. For example, in SAP Customer Master, you can use transaction code "FD06" or "FD08" to search for duplicate customer records.

Data Quality Tools: Data quality tools like Ditto can perform data profiling and duplicate checks.

Data Governance Solutions: Implement data governance solutions, like Maextro that include duplicate checks as part of their functionality.

To address duplicate data, follow these steps:

• Conduct data profiling to identify potential duplicates.
• Define unique identifiers (e.g., ID, email) for accurate matching.
• Use matching algorithms (fuzzy or exact) to detect duplicates.
• Merge or remove duplicate records based on your data strategy.
• Cleanse remaining data by updating and validating entries.
• Establish data governance policies to prevent future duplicates.
• Utilise automation or data quality tools for streamlined management.
• Regularly monitor data quality and review governance policies. By taking these measures, organisations can ensure data integrity, improve decision-making, and optimise data utilisation.

Duplicate data can result from various factors, including human error during data entry or import processes. Incomplete validation checks, lack of standardised data entry guidelines, and system limitations can lead to duplicate entries. Data migration, integration of disparate systems, and data synchronisation issues may also introduce duplicates. Inadequate data governance, the absence of unique identifiers, or mismatches in data consolidation can further contribute to duplicates. Additionally, incomplete data cleansing processes and outdated data management practices can allow duplicates to persist. Addressing these root causes and implementing robust data governance and quality measures can help prevent and manage duplicate data effectively.