Remove Dashboards Remove Data Analytics Remove Data Warehouse Remove Demo
article thumbnail

Centralize near-real-time governance through alerts on Amazon Redshift data warehouses for sensitive queries

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud that delivers powerful and secure insights on all your data with the best price-performance. With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers.

article thumbnail

Achieve near real time operational analytics using Amazon Aurora PostgreSQL zero-ETL integration with Amazon Redshift

AWS Big Data

and zero-ETL support) as the source, and a Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. Additionally, you can choose the capacity, to limit the compute resources of the data warehouse. For this post, set this to 8 RPUs.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Migrate from Amazon Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics Studio

AWS Big Data

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

article thumbnail

The 10 Best Business Intelligence Tools For Small And Big Business

Smart Data Collective

Microsoft Power BI transforms data into visuals, lets you explore and analyze any data easily, as well as share it with your colleagues. This tool also allows users to share dashboards and reports, and collaborate on them. Cluvio is a popular cloud analytics platform, created for the needs of startups and data-driven teams.

article thumbnail

Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

On the EMR Studio dashboard, choose Create workspace. S3FileIO" } } This sets the following Spark session configurations: spark.sql.catalog.demo – Registers a Spark catalog named demo, which uses the Iceberg Spark catalog plugin. impl – Iceberg allows users to write data to Amazon S3 through S3FileIO. Choose Create Studio.

Data Lake 118
article thumbnail

Build a serverless analytics application with Amazon Redshift and Amazon API Gateway

AWS Big Data

Use cases can include the following: Dashboarding – A webpage consisting of tables and charts where each component can offer insights to a specific business department. Reporting and analysis – An application where you can trigger large analytical queries with dynamic inputs and then view or download the results. Choose Run build.

article thumbnail

Getting started guide for near-real time operational analytics using Amazon Aurora zero-ETL integration with Amazon Redshift

AWS Big Data

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. With Aurora zero-ETL integration with Amazon Redshift, the integration replicates data from the source database into the target data warehouse.