A Brief Overview of the Data Warehouse and BI Architecture

The needs of companies today are far outpacing their needs from just a few years ago. But in order to look toward the future with a modern approach, we need to look at what organizations have been doing for the last few decades in regards to their data warehouse and BI architecture.

It Starts with a Data Warehouse

A data warehouse (DW) is a place of storage and consolidation for an organization’s data and information that can come from multiple data sources. The data warehouse became popular in the 90’s as a fast, efficient alternative to batch reporting against siloed transactional systems. This enabled strategists to make critical business decisions based on the data gathered from the entire organization through Online Analytical Processing (OLAP).

Data warehouse and BI architecture Online Processing

For the last twenty years, OLAP and data warehouse architectures have remained relatively unchanged. This fact combined with the rapid speed of innovation in technology and need for instant, dynamic information has begun holding companies back digitally.

Then Came the Traditional BI Architecture

A typical BI architecture usually includes an Operational Data Store (ODS) and a Data Warehouse that are loaded via batch ETL processes. (To read about ETL and how it differs from ELT, visit our blog post!)

Data warehouse and BI architecture

Big Data Started to Change This Architecture

In the mid-2000s, a new buzz word came into play – big data. Having to deal with large amounts of data wasn’t a new concept, but now it had a name and began changing the traditional BI architecture. As companies scrambled to find out what to do with their big data problem, technologies like Apache Hadoop swooped in to take the load off their shoulders. Soon, Hadoop became synonymous with big data and many tried to augment or replace the data warehouse with a Hadoop-based solution.

Data warehouse and BI architecture Hadoop

But Hadoop is not a great fit for all big data use cases. It also requires specialized skills and a confusing array of open source software.

When Traditional Architectures Aren’t Cutting It

Though these architectures have been around and served organizations well for decades, they just can’t possibly keep up with the complexity and scalability needs of companies these days.

To see how Smartbridge is modernizing the BI and data warehouse architecture, look out for our upcoming “Accelerating Your Journey to Agile Analytics” eBook!

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