The Solix Data Fabric: A Multi-cloud Information Architecture

Data lakes are repositories of “current” data collected to feed data-driven applications. Advanced analytics, machine learning and artificial intelligence applications often require some data transformation, data cleansing or data enrichment in preparation for processing. Data lakes are the building blocks of data pipelines, and they provide a data preparation platform to make data “fit for use” by data-driven applications.

Archives are centralized repositories of “historical” data that improve data governance and compliance through the principle of data minimization, which states simply that data should be retained only for as long as minimally necessary, and only to fulfill a specific and defined purpose. By archiving historical data from production databases, file servers and email servers, organizations can improve the performance of their production applications, optimize infrastructure and reduce the high cost of production infrastructure because the data footprint is so much smaller. Archives also enable application retirement and decommissioning of legacy systems that are no longer in use. Significant cost savings may be realized, and improved data compliance is achieved by rationalizing application portfolios and retiring outdated applications and data consistent with ILM and compliance policies.

Consumer data privacy regulations are emerging worldwide, sparked by the broad adoption of the EU’s GDPR initiative. New privacy laws and regulations are now enacted by over 100 countries and states, and significant fines have been levied for non-compliance. Consumer data privacy applications establish “privacy by design” and equip data controllers with critical tools such as sensitive data discovery, data masking, legal hold, redaction and erasure in order to comply with regulations governing personally identifiable information (PII).