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Does your organization have a clean & reliable data warehouse solution?

An excellent data warehouse is key for optimizing business intelligence.

How your data warehouse solution should work:

#1 – Data collection

First, your solution should collect data that resides in sources located both within and outside your organization.

#2 – Data organization

Then your solution should organize your data so that it’s conducive to positive business actions.

#3 – Performing deep queries

Your solution should empower users to perform deep queries in a quick and accurate manner.

#4 – Data retrieval

Your solution should also enable you to both retrieve your data at lightning speed and share it seamlessly.

#1 – Data collection

First, your data warehouse solution should collect data that resides in sources located both within and outside your organization.

#2 – Data organization

Then, your solution should organize your data so that it’s conducive to positive business actions.

#3 – Performing deep queries

Your data warehouse solution should empower users to perform deep queries in a quick and accurate manner.

#4 – Data retrieval

Your solution should also enable you to both retrieve your data at lightning speed and share it seamlessly.

Data warehouse architecture is an art to us.

The architecture of your data warehouse is the beating heart of your system. If it’s not excellent, your analytics and BI initiatives won’t be either.

Key2 Resources – Data Warehousing

Getting started with SQL Data Warehouse (SQL DW)

Getting started with SQL Data Warehouse (SQL DW)

As was mentioned in a previous blog post comparing the pros and cons of Microsoft Azure SQL Database versus SQL Data Warehouse, Microsoft announced at SQL PASS 2016 that they are offering a free, 1-month trial of SQL Data Warehouse. In this post, we wanted to take Microsoft up on their offer and show you how to get started using Azure SQL Data Warehouse (SQL DW)!
Building a Data Warehouse: Populating and Using a Junk Dimension

Building a Data Warehouse: Populating and Using a Junk Dimension

A junk dimension is seen occasionally inside of data warehouses. This type of dimension can be thought of as a flag table, or a collection of attributes that have low-cardinality. In this post, we show you how to build a data warehouse by populating a junk dimension.

You can have an accurate and reliable data warehouse.

An outstanding data warehouse solution is the lifeblood of any successful BI initiative.

We are an Atlanta data warehouse solution provider obsessed with data.