PiLog data harmonization application, cleans and structure data to the ISO 8000 data quality standard, in the process duplicate records are removed and a master record index is established

The PiLog Data harmonisation service (cleansing,structuring) refers to the process of identifying and correcting or removing duplicates, errors, inconsistencies, and inaccuracies in any dataset/s. This process improves data quality and ensures accuracy of data to all business units. It also enhances the reliability of data for effective use in decision-making. Data cleansing and standardization are ongoing processes that require regular monitoring and maintenance to sustain data quality over time. By incorporating these practices into data management workflows, organizations can ensure the integrity and usefulness of their data assets.

Below follows a list of fundamental steps to cover during a data cleansing process:

• Identification of data issues

• Error / Duplicate correction

• Data Standardization

• Validation and verification of data

• Data enrichment

The following users will benefit from the using the PiLog Data Harmonisation software as a service solution:

• Data stewards tasked with data governance and data cleansing activities

• ERP end user searching for clean data records

• IT personnel requiring data cleansing API's to structure data, obtain access to ontologies, dictionaries and cleansed data record sets

Data cleansing and standardization, as part of a business solution, can offer several benefits that contribute to the overall success and efficiency of a company’s data management practices. Following are some key advantages it offers:

• It enhances data quality by identifying and rectifying errors, inconsistencies and inaccuracies in the dataset. Duplicates get removed during this process and inaccuracies get corrected. During this process data consistency is ensured so that companies can rely on accurate and reliable data for decision-making, reporting and analyzing purposes.

• It provides a solid foundation for data driven decision making. High-quality data reduces the risk of making decisions based on incorrect or incomplete data.

• It ensure data consistency and accuracy by applying predefined rules, formats, and conventions.

• It reduces errors, rework, and operational inefficiencies caused by inaccurate or inconsistent information. It streamlines business processes. Loads of confusion gets eliminated during this process and it enables smoother data integration across systems and applications. This leads to improved productivity.

• Integration across different systems is easier. It facilitates seamless data exchange, data synchronization, and process automation.

• It helps companies meet regulatory compliance requirements, especially regarding data accuracy, privacy, and security.

• Increased Operational efficiency

• It contributes to a better customer experience by ensuring that customer data is accurate and up to date.

• Cost Optimization

Automated Data Cleansing

Pilog has built data repositories with millions of data records available for reference as part of our AI data cleansing services. We also incorporate the best industry services from our PiLog Data Quality Hub cloud platform. These repositories are available to the steward to reference data, source data to fast and effectively obtain data to complete the data harmonisation process.

Azure platform Consultation.

PiLog Consulting Data services implements Azure software components to assist them in the Data Cleansing exercise. They PiLog data cleansing toolset runs on Azure and our Consultants will assists you with the provisioning of Azure SQL and Azure Application Services instances for your data project. In addition, integration to data management services on Azure such as Microsoft Purview, Fabric are available. PiLog can also deliver the cleansed data into an Azure Data Lake and we provide consultation on Microsoft Synapse and Power BI for all your reporting needs.