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Data Reconciliation is a process within the field of Data Analytics that involves comparing data from multiple sources to ensure accuracy and consistency. It is used to identify and correct discrepancies between data sets, allowing for more reliable and accurate analysis. Data Reconciliation is often used in financial and accounting applications, where it is important to ensure that data is accurate and up-to-date. It can also be used to detect fraud and other irregularities.
Data Reconciliation is a critical component of any data analytics process, as it helps to ensure that the data being analyzed is reliable and accurate. It is also used to identify and correct errors in data sets, allowing for more accurate analysis.
Companies in the Data Reconciliation market include Oracle, IBM, Microsoft, SAP, and SAS. Show Less Read more
