Tag: Lake House

The modern data lake has solved a number of challenges associated with the traditional data warehouse, such as the ability to store unstructured, semi-structured, and structured data in one cost-efficient location. Explore the best practices for structuring your data lake analytics with Starburst Galaxy and AWS. Starburst Galaxy is a cloud-native service which provides fast access and flexible management of data, without adding the complexity of data movement.

Without following an adequate data governance framework, data quality remains elusive, especially as the data is managed and retained in silos and organizations struggle to achieve a holistic enterprise-wide view of all of their big data assets. Hear from AWS and Mactores Cognition experts how data lake house technology helps overcome the limitations of data lake and data warehouse systems, and explore architectural characteristics of the data lake house and how these help users optimize data orchestration workflows.

Databricks SQL is a dedicated workspace for data analysts that comprises a native SQL editor, drag-and-drop dashboards, and built-in connectors for all major business intelligence tools as well as Photon. In this post, Volker Tjaden, an APN Ambassador from Databricks, shares the technical capabilities of Databricks SQL and walks through two examples: ingesting, querying, and visualizing AWS CloudTrail log data, and building near real-time dashboards on data coming from Amazon Kinesis.

Unlocking data intelligence and implementing modern data architectures can turn organizations into data-driven enterprises and help drive business outcomes. Learn how AWS and Accenture are helping customers transform to data-driven organizations through Accenture’s Data Lake Accelerator built on AWS. It’s a one-stop solution for automated data platform creation, managed data transformation, and data and analytics performed in a cloud-native way.

Many organizations leverage unstructured data collected from social media feeds, stock streaming, and data clickstream to gain insights about the needs of their customers. The EZ Lake Access (EZLA) solution developed by TCS centralizes and simplifies access management of the Data Lake House by codifying most of the enterprise access controls in the form of a rule engine. This provides increased efficiencies and easy adoption of the Data Lake House.

There has been a lot of buzz about a new data architecture design pattern called a Lake House. A Lake House approach integrates a data lake with the data warehouse and all of the purpose-built stores so customers no longer have to take a one-size-fits-all approach and are able to select the storage that best suits their needs. Learn how to couple Amazon Redshift with a semantic layer from AtScale to deliver fast, agile, and analysis-ready data to business analysts and data scientists.