Why do you need a Data Assurance Framework?
Data is the most valuable asset for any business in a highly competitive and fast-moving world. Maintaining the integrity and quality of your business data is therefore crucial. However, ensuring data quality assurance often comes with its own set of challenges.
Lack of data standardization: One of the biggest challenges in data quality management is that data sets are often non-standardized, coming in from disparate sources and stored in different, inconsistent formats across departments.
Data is vulnerable: Data breaches and malware are everywhere, making your important business data vulnerable. To ensure data quality is maintained well, the right tools must be used to mask, protect and validate data assets.
Data is often too complex: With hybrid enterprise architectures on the rise, the magnitude and complexity of inter-related data is increasing, leading to further intricacies in data quality management.
Data is outdated and inaccurate: Incorrect, inconsistent and old business data can lead to inaccurate forecasts, poor decision making and business outcomes.
Our iDAF Services
With iDAF, you can streamline data assurance across multiple heterogenous data sets, avoid data quality issues arising during the production stage, move away completely from the inaccuracy and inconsistency of sample-based testing and increase 100% data coverage. iDAF leverages data best open-source big data tools to perform base checks, data completeness, business validation, reports testing and 100% data accuracy. Ensure data completeness, accuracy, improved decision making and make the most of your business data with our iDAF services.
1. 30% – 45% faster time to market.
2. Manage the testing of your large and diverse data sets better
3. Reduce human efforts in running tests across multiple data sets
4. Handle heterogeneous source and target combinations effectively
5. Ensure end-to-end data migration with detailed reporting
With iDAF, you can streamline data assurance across multiple heterogenous data sets, avoid data quality issues arising during the production stage, move away completely from the inaccuracy and inconsistency of sample-based testing, and increase 100% data coverage.
iDAF leverages data best open-source big data tools to perform base checks, data completeness, business validation, report testing, and 100% data accuracy
We leverage iDAF to carry out automated validation between target and source datasets for
1. Data Quality.
2. Data Completeness
3. Data Integrity
4. Data Consistency
Automate and optimize your data assurance practices with iDAF’s exclusive data validation framework.
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