Analytics and business intelligence platforms — enabled by IT and augmented by AI — empower users to model, analyze and share data. Analytics and business intelligence (ABI) platforms enable organizations to understand their data. For example, what are the dimensions of their data — such as product, customer, time, and geography? People need to be able to ask questions about their data (e.g., which customers are likely to churn? Which salespeople are not reaching their quotas?). They need to be able to create measures from their data, such as on-time delivery, accidents in the workplace and customer or employee satisfaction. Organizations need to blend modeled and nonmodeled data to create new data pipelines that can be explored to find anomalies and other insights. ABI platforms make all of this possible.
Data masking is based on the premise that sensitive data can be transformed into less sensitive but still useful data. This is necessary to satisfy application testing use cases that require representative and coherent data, as well as analytics that involve the use of aggregate data for scoring, model building and statistical reporting. The market for data protection, DM included, continues to evolve with technologies designed to redact, anonymize, pseudonymize, or in some way deidentify data in order to protect it against confidentiality or privacy risk.
To reduce both infrastructure costs and manual workloads in postmodern ERP projects, SAP application leaders and SAP Basis operations leaders should evaluate specialized software tools for automating the regular refresh of their SAP ERP test data. SAP selective test data management tools perform selective copying of SAP test data, but they vary in their approach to data selection, scrambling and performance optimization. There are two user constituencies for these tools: (1) Basis operations teams require repetitive data copy operations that must be as automated as possible (2) SAP application data objects for ad hoc data copying. Some of the tools also enable Basis operations teams to produce a 'shell system,' which is an identical copy of a complete production system, but without the transaction data. This is very useful in many projects for testing purposes.