We understand that efficient and effective data handling is a core capability. Our approach to data management is collaborative; we work with : you to uncover
Who owns specific data objects within your organization?
Once we find the answers to these questions, we deliver strategies that make your data work better for you. Our experience in data management is complemented by our extensive expertise in providing organizations with business research services. We thrive to find the special attributes in your data that provide the right insights to solve for the end goal.
The experience gained over the years bridge all industries with services including primary data collection via
telephone interviews, focus groups, recruiting services and online surveys, in addition to data compilation, management and advanced analytics enabled insights for meaningful conclusions and actionable recommendations.
Our focus would begin with our consultants drawing up a detailed plan to decide for more than one data source and information
We identify the data gathered by different teams relevant to your business. Accordingly, we select on the data to be migrated as well as specific info needed from which system.
Data Preparation is done by ensuring each source system has a unique identifier. If there are no backend IDs for sales records in CRM, we initiate data cleansing and data deduplication.
We migrate data from other source systems using the lattest ETL tools, We choose a migration method based on data volume and complexity of source data.
After the migration of data to Salesforce platform, we do Qualitty Assurance test. We ensure all data is transferred rightly with formatting and no errors.
Data integration solutions from AttributeX offer enterprises a scalable data integration capability using our proprietary platform, AXLean . The platform allows you to transform data in any style and deliver it to any system, supporting faster time to value and reduced IT risk.
The integrated platform delivers a wide range of data quality capabilities from data profiling, standardization, matching and enrichment to active data-quality monitoring.