Architecture-options-for-building-an-analytics-application-on-aws

A lake house is a modern data architecture that integrates a data lake, a data warehouse, and other purpose-built data stores while enabling unified governance and seamless data movement.

Giving the decision-makers the opportunity to explore and interpret information in an interactive visual environment helps democratize data and accelerates data-driven insights that are easy to understand and navigate. Building a BI and data visualization service in the cloud allows you to take advantage of capabilities such as scalability, availability, redundancy, and enterprise grade security.

Operational analytics refers to inter-disciplinary techniques and methodologies that aim to improve day-to-day business performance in terms of increasing efficiency of internal business processes and improving customer experience and value.

Processing real-time streaming data requires throughput scalability, reliability, high availability, and low latency to support a variety of applications and workloads.

On AWS, analytic services, such as Amazon EMR , Amazon Redshift , Lake Formation Blueprints , and AWS Glue family services namely Glue ETL , Glue Workflows , AWS Glue DataBrew , AWS Glue Elastic Views allow you to run batch data processing jobs at scale for all batch data processing use cases and for various personas, such as data engineer, data analyst, and data scientists.

people have been talking about the data-driven organization model for years, which consists of data producers and consumers. This model is similar to those used by some of early adopting consumers and has been described by "Zhamak Dehghani of Thoughtworks", who coined the term data mesh.