Data lakehouse is modern data architecture that combines the best of data management worlds—flexibility of data lakes and reliability of data warehouses.
Our data lakehouse technology provides businesses with a unified platform for data storage, processing, and analytics, making it easier to derive insights from operating data. You can scale your data infrastructure on-demand, transcend data silos or vendor lock-ins, reduce data management costs, and eventually improve time-to-insight with a single source of truth.
Ingest, Cleanse, and Analyze
Start with ingestion of raw data from various sources, such as databases, APIs, IoT devices, and logs. The data is collected and transferred to the cloud.
Next, enrich raw data and make it usable for downstream applications. This includes cleaning, normalization, aggregation, and filtering of data.
Any sensitive PII data that doesn’t contribute to analytics will be redacted, filtered, tokenized, and cleansed.
Snowflake enabled architecture lets users benefit from a pay-per-use model, on-demand scalability, no infrastructure management, and zero capacity planning costs.
Analyze data to identify patterns, trends, and relationships between variables. Build statistical models to predict outcomes, estimate probabilities, and identify factors affecting the outcomes.
Use machine learning algorithms to build predictive models and uncover insights from large and complex datasets.