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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.

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

AWS Big Data

In this post, we provide a solution architecture that describes how you can process data from three different types of sources—streaming, transactional, and third-party reference data—and aggregate them in Amazon Redshift for business intelligence (BI) reporting. This will be your OLTP data store for transactional data.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Data lakes are more focused around storing and maintaining all the data in an organization in one place.

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Configure monitoring, limits, and alarms in Amazon Redshift Serverless to keep costs predictable

AWS Big Data

It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance, and you pay only for what you use. Just load your data and start querying right away in the Amazon Redshift Query Editor or in your favorite business intelligence (BI) tool.

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Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

Because the data describing each transaction was in a database, this made it easy to retrieve and summarize multiple transactions together. This data retrieval and summarization capability gave rise to what we now know as the business intelligence industry. Add the predictive logic to the data model.

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Top 10 Reasons for Alation with Snowflake: Reduce Risk with Active Data Governance

Alation

A range of regulations exist: the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), as well as industry regulations like the Health Insurance Portability and Accountability Act (HIPAA) and Sarbanes–Oxley Act (SOX). With Snowflake, data stewards have a choice to leverage Snowflake’s governance policies.

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Simplify Online Analytical Processing (OLAP) queries in Amazon Redshift using new SQL constructs such as ROLLUP, CUBE, and GROUPING SETS

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Additionally, we disabled query caching so that query results aren’t cached.