Data Migration and Governance
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One of the primary goals for any organization implementing SAP solutions is to use the project momentum to cleanse the data and keep the data clean. SAP facilitates the consolidation of the master data objects from the decentralized legacy data sources into a single data platform, whether it is SAP itself, and tools like SAP MDM, or MDG. Use your SAP transformation initiative to build increased consistency and confidence in decision making by use of clean data, and decrease the risk of penalties, regulatory fines, improving data security, and distribution policies. Maximize your data quality by better planning and automation of processes eliminating human error and re-works. Data governance is a quality control mechanism for assessing, managing, using, improving, monitoring, maintaining, and protecting your organization’s core information that runs the heart of your business.
Data Quality is Key to Implementation Success
“People using the data for decision making can pretty quickly tell bad data because it doesn’t match their expectations. Or, more Precisely, they see something that doesn’t match something they know to be true”
Data quality issues such as completeness, validity, consistency, timeliness, and accuracy are major issues in any enterprise system. The complexity of maintaining the quality of data increases tenfold within the Business Process Networks that span multiple companies.
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Extract
Identify sources and extract all data needed as building blocks of your new enterprise master data repository.
Cleanse
Data cleansing eliminates errors, identifies overall quality of existing data, deduplication, and column segmentation.
Analyze
Analysis is discovery, and distillation of business requirements into a scope of work and match to available data.