Data warehouses are a straightforward solution where you generally collect data from a source with ETL and load it in. The you access those data sources with BI and analytics tools.
Data lakes ingest data by batch or stream where you can they choose whether or not to process or transform that data. A huge advantage of the data lake architecture is that you have access to the raw data which allows all kinds of users to process and transform data for their specific use cases.
Multiple views of your data. Get your well-structured data ready to be consumed to generate reports and KPI's or maintain in it metadata form connected with external data to be used by your research team and generate advanced analytics.
Expands the dataset for analysis beyond the traditional internal data held on ERP, CRM and supply chain management (SCM) systems.
Full-featured data lake for the rapid ingestion, consolidation, cleansing, unification and sharing of all available internal and external data sources.
Monitors data and metadata using algorithms for quality and assurance.
Integrates both new and existing data sources to boost predictive models.
Direct access to all unified customer data, via API, R6 dashboard and 3rd party systems (SalesForce, Odoo, etc.), for increased shareability across systems and teams.