Here’s why – plus how businesses use data warehouses.
So, who’s seen the episode of Law & Order where the investigation was stalled because “lost” evidence was sitting on a shelf in the crime lab – untested – for years and years? Oh, you have? Right of course – that’s a trick question because many, many episodes have followed this route. That’s the thing with any large body of information. It’s very hard to analyze and form correlations with other pieces of evidence when, you know, you can’t find it.
Data warehouses and databases are two different systems that help organizations manage boatloads of data. But they are not the same thing at all. Picture a library. You remember going to those, right? Checking out actual books. A database would be like the record librarians have of who has which books checked out at a given time. It’s an up-to-date, transactional record. The data warehouse, on the other hand, is like that record plus the card catalogue plus member records plus book orders and more, all in one place and with the ability to answer, “Do members aged 45 to 55 check out more books in the winter or in the summer?”
Data warehousing – here’s the basics.
Bottom line, the term “data warehouse” is fun to say and it gives us a tangible image of data sitting in neatly organized piles on a shelf. It helps us wrap our heads around something that exists in unseen digital spaces. At its most basic level, a data warehouse is a relational data system that pulls together data from different sources to make it easier to access and understand.
Right, so how is that different from a database?
Good question. Both data management tools house giant volumes of data, and both are relational. But the similarities more or less stop there. The easiest way to differentiate between a data warehouse and a database is to think about the purpose of each. A data warehouse aggregates different types of historical and cumulative data from various systems with the purpose of offering fast, query-based analysis. Sort of like an easy, self-serve way to get analytics. It supports business intelligence and allows decision-makers to understand ongoing business needs.
A database, on the other hand, stores secure, real-time data centered on specific day-to-day operational processes, like billing, inventory, customer management and more. Its primary function is to provide secure record-keeping and fast access. Unlike a data warehouse, which runs on an online analytical processing (OLAP) system, a database uses online transactional processing (OLTP), lacking the analytical layers but providing targeted, up-to-date info fast. Another key difference is that hundreds, sometimes thousands, of people may need to access a business’s database. Whereas, only select stakeholders and select personnel access the data warehouse. This results in different levels of security and maintenance.
To simplify: a car dealership may use a database for billing records, but it would use a data warehouse to help develop limited-time promotions based on customer trends.
What’s the main benefit of a data warehouse?
Data warehousing is especially awesome at enabling cross-functional collaboration and decision-making. By aggregating data from what can typically be siloed departments and systems, it allows everyone with access to view a unified system of truth based in real data. Data warehousing eliminates the gray area of human reporting and interpretation, as well as opportunities for miscommunication. Plus, it does all this waaaaay faster and better than humans can. Sort of magical, right?
Common data warehousing uses
So, just like the library and car dealership examples, the most common use cases for data warehousing are about identifying trends that can help companies predict and plan. Businesses rely on data warehousing to help:
Improve logistics
Manage seasonal business shifts
Analyze customer behaviors
Develop loyalty programs
Set pricing structures
Track market changes
Bottom line, most businesses are collecting a ton of data every day. Both databases and data warehouses can help make that data worthwhile. Artificial intelligence, predictive analytics, custom dashboards – there are a lot of tools out there that can make sense of your data. Hit us up if you have questions about what’s right for your business.