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warehousing

Building a Data Stack: An Overview on Google BigQuery

Get an overview on Google BigQuery the petabyte-scale and cloud-based data warehouse from Google. This blog post will cover concurrency, throughput, security, data operations and cost for Google BigQuery. Read to learn more.

Building a Data Stack: An Overview on Amazon Redshift

Get an overview on Amazon Redshift, the petabyte-scale and cloud-based data warehouse from AWS. This blog post will cover concurrency, throughput, security, data operations and cost for Amazon Redshift. Read to learn more.

Calculating Your Data Warehouse Cost

As data becomes more voluminous, accessible and cost efficient—businesses must leverage data for their advantage. Learn how to calculate the cost of popular data warehouse solutions including Amazon Redshift and Google BigQuery.

An Overview on Amazon Redshift and Google BigQuery Security

In this blog post, we cover features that Amazon Redshift and Google BigQuery provide to manage data warehouse security for their customers.

Warehouse Maintenance: Amazon Redshift and Google BigQuery

Examine the differences in how cloud-based Amazon Redshift and Google BigQuery perform maintenance on their cloud-based systems, which is often seen as a point of contention for many users. Read about the differences.

How to Load Data into Amazon Redshift or Google BigQuery

In this blog post, examine how data warehouses Amazon Redshift and Google BigQuery handle how data loads, its speed, accessibility, and more.

How Amazon Redshift and Google BigQuery Handle Provisioning

Data warehouses, like Amazon Redshift and Google BigQuery, are meant to handle a large volume of data. Read this blog post as we examine how Amazon Redshift and Google BigQuery handle data provisioning.

Impact of Throughput and Concurrency on Your Data Warehouse

In this blog post, we discuss throughput and concurrency on your data warehouse and the impact it has on your ability to run analyses.

Leveraging Your Data Warehouse as a Competitive Advantage

Data warehouses are optimized to analyze data by turning massive amounts of data into analytics that are easy to understand. Learn the advantages in using a data warehouse for analysis and how they are a competitive advantage.

When to Invest in a Data Warehouse

A data warehouse, or a reporting database, is an online analytical processing (OLAP) database and acts as a layer on top of an operational database. Learn when you should invest in a data warehouse for your data stack.

Why Compose uses Postgres and Chartio to Analyze Mongo data

Chris Winslett, product manager at Compose, joined us for a webinar on why a company with deep roots in NoSQL chose PostgreSQL for its analytics database.

Producing and Analyzing Rich Data with PostgreSQL

Learn best practices on how to produce and analyze rich data in PostgreSQL in a presentation with a Chartio data engineer at his presentation at Rich Data Summit 2015 here in San Francisco. Watch the on-demand video.

Roundtable: Amazon Redshift Best Practices for BI, Part 2

In part two of our panel discussion on Amazon Redshift best practices, our panelist spoke about schemas designs, tables and overall Amazon Redshift performance optimization. Read this blog post to learn more.

Roundtable: Amazon Redshift Best Practices for BI, Part 1

In this blog post, watch our panel discussion on Amazon Redshift best practices with speakers from Amazon Web Services, Clever, Chartio and Lumosity. Get Amazon Redshift performance optimization and ETL best practices.

Six Questions to Save Time and Money on Data Warehousing

You've decided on business intelligence tool, but it's still easy to get lost in questions about data storage. In this blog post, learn the six questions to answer when evaluating and deciding upon a Business Intelligence tool.