Data warehouses are an extremely popular storage system for companies of all sizes. Over the course of this blog post, we will speak about what a data warehouse is and how it could benefit you and your team. Let's get right into it!
A data warehouse (DWH) is a data storage system that acts as the source of truth for data reporting and analysis. DWHs are used to centralize data from multiple sources into one system so that it can be easier to analyze later on. For example, sales, marketing, and HR data would be aggregated in a company's data warehouse.
DWHs usually contain huge amounts of historical data from multiple databases and many other sources. In some cases, data is cleaned or transformed as it enters the warehouse so that it is more useful for business users. Data warehouses can connect to BI tools to allow business users and data scientists to put the data to use.
A few blog posts ago, we spoke about the difference between ETL (extract, transform, load) and ELT (extract, load, transform). ETL and ELT are the two main approaches for building a data warehouse. The difference between ETL and ELT data warehouses is the order in which the transform step occurs.
For ETL-based warehouses, data travels through staging and integration layers before reaching its final destination within the warehouse. Incoming data first reaches the staging layer, this is the part of the warehouse that stores the raw data that is extracted from your sources. This data is then passed on to the integration layer, where it is transformed and cleaned before being passed on to its destination within the data warehouse.
ELT-based warehouses do not transform incoming data immediately. Instead, there is a staging area within the warehouse itself that stores raw data. Data is moved directly into this area of the warehouse, and transformations are applied within the data warehouse. Later on, transformed data is loaded into tables.
There are four key characteristics of data warehouses that allow them to have a huge benefit.
There are many cloud data warehouse providers in the market. Amazon Redshift, Microsoft Azure, Google BigQuery, and Snowflake are a few of the industry leaders. Although each platform provides a cloud data warehouse, they each have strengths and weaknesses and different pricing plans.
It is also possible to set up an on-premise data warehouse, however, cloud options are easily scalable and do not require a significant upfront investment.
Historically, getting data into a data warehouse required engineering teams, however, many modern tools now exist to make this process much simpler.
If you are looking for an all-in-one solution, check out Dropbase. Dropbase allows you to easily ingest data from multiple sources and provides you with a private, secure cloud data warehouse for you to use how you want.
There are quite a few benefits to using a data warehouse:
There are many benefits to using a data warehouse, however, it is important to also be conscious of the time and resources that you'll need to allocate to maintain it. Getting data from many sources into a specified format takes time, especially when you have to manually correct inconsistencies. Dealing with an ever-growing data warehouse also has cost implications. Over time, your warehousing costs will likely only increase.
Data warehouses can be a powerful tool to allow you to better understand your business. As with any solution, there are benefits and pitfalls, so it is important to think about if a data warehouse would be beneficial for your specific situation.