In the early stages of business technology, a company’s operational data was often a handful of records and analytical reports. As IoT devices and business applications become more ingrained in today’s industry 4.0, companies now sit on large data from disparate sources.
The daily operations of many data users and data scientists currently run into trillions of bytes. Have you ever thought of where this unstructured data end up? If so, continue reading as this article delves into data warehouses and their benefits for businesses and data consumers.
Data Warehouse Defined
The concept of data warehousing has evolved a great deal since the late 1980s. So, what is data warehousing? Today, this question brings up over 600 million specific data results on Google. That alone is a testament to the popularity and scale of this data warehouse topic.
A data warehouse stores all types of data from various sources, including SQL, PDF, MySQL, NoSQL, etc. There are several different ways to build a high-performance data warehouse. However, the most common way is to either opt for an on-premise data warehouse or a more modern data warehouse solution like a cloud data warehouse. The latter has become the best way to go today, considering the large amounts of data companies process today from computer systems.
Companies rely on computer nodes for all key functions, from human resources to processing last month’s total sales. Thanks to the ETL process, data engineers can deal with data from different sources more efficiently. Data professionals first extract the data. Then they can transform it all into a usable format that can be loaded into a data warehouse system for business users.
All in all, data warehousing has become a favorable option for market research, auditing, and the insurance sector. The use cases range from artificial intelligence, business analytics, marketing automation, predictive analysis, etc.
Data Warehouse Architecture
A data warehouse architecture is an information system that arranges an enterprise’s data in different databases. The typical architecture often has three layers. It starts with the front-end tools, the OLAP server as the middle layer, and the data warehouse sever at the bottom. Some common architectures include virtual warehouse, data mart, and enterprise data warehouse.
Data Warehouse Benefits
The benefits of data warehousing are endless. Some specific data warehousing perks include:
1. Ease of Use
Think of a typical data warehouse as a file cabinet with several wardrobes. Usually, all these small compartments have are ID numbers. But imagine you had to open each of these wardrobes just to check which ones were available and the no-go areas. These lags can limit real-time data access. Lags in data access are a nemesis of the modern data user. It can even affect the data analytics capabilities of an operational database.
For starters, a modern data warehouse doesn’t have the storage limits of a physical server. Data warehouse serves as a central repository for all datasets across an enterprise’s heterogeneous sources. And many data warehouse systems have a dashboard feature built with data visualization resources. This makes it easy to generate a summary or snapshot of an enterprise’s data set. It creates a more convenient data access approach compared to checking one data cluster after the other.
2. Good Data Quality
In the data transformation process, warehouses ensure data cleaning of similarities and duplicates. The process which helps render a company’s metadata into a fine golden copy also ensures quality.
3. Efficient Decision Making
Using cloud-based data warehouse solutions makes it easier to comb years of data and historical analysis. Data warehouse systems can help generate business insights for accurate predictions and business decisions. That’s why data warehouse is a core component of business intelligence today.