Remove Analytics Remove Dashboards Remove Data Warehouse Remove Optimization
article thumbnail

5 misconceptions about cloud data warehouses

IBM Big Data Hub

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

article thumbnail

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

AWS Big Data

When data is used to improve customer experiences and drive innovation, it can lead to business growth,” – Swami Sivasubramanian , VP of Database, Analytics, and Machine Learning at AWS in With a zero-ETL approach, AWS is helping builders realize near-real-time analytics.

Insiders

Sign Up for our Newsletter

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

article thumbnail

Sisense Q2 2021: Build Extensible Insights and Infuse Analytics Beyond the Dashboard

Sisense

The Sisense Q2 2021 product release is packed with exciting innovations and enhancements that offer users a more extensible experience when it comes to analytics. Analytics adoption has stalled; only infused analytics can help. Sisense Explanations deepens your understanding of your data. Learn more. Learn more.

article thumbnail

Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

Trade quality and optimization – In order to monitor and optimize trade quality, you need to continually evaluate market characteristics such as volume, direction, market depth, fill rate, and other benchmarks related to the completion of trades. This will be your OLTP data store for transactional data. version cluster.

article thumbnail

Sisense’s Q2 Release: A Modern Data Experience Across the Analytics Continuum

Sisense

Today’s organizations are more data-driven than ever. Over a third of respondents to our State of Analytics and BI survey reported that they are currently focused on growing their use of analytics across their businesses. In-Warehouse Data Prep supports both AWS Redshift and Snowflake data warehouses.

article thumbnail

Top 5 Tools for Building an Interactive Analytics App

Smart Data Collective

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Why Use an Interactive Analytics Application?

article thumbnail

Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. We think of this concept as inside-out data movement.

Data Lake 109