A data warehouse is a repository where large amounts of data can be stored and made available for decision support systems, business intelligence, analytics, reporting, research, and other related activities. Despite the ubiquitous association with large data sets, data warehousing refers not only to massive amounts of storage but also to decision-makers ability to access different types of data from various sources. This article describes the idea behind data warehouses, how they are created and used, and when is the right time to get a data warehousing system for your organization.
Understanding The Use of Data Warehouses
Large amounts of structured and unstructured data from various sources can be managed and stored in a data warehouse, which is a specialized type of database. Data warehouses are ideal for business intelligence and data science applications because they are designed to handle complex queries and analyze better than standard databases. The main goals of a data warehouse are data consolidation, data quality, and a single source of information for reporting and analysis.
Who Uses a Data Warehouse?
Data warehouses are used by all organizations that process large amounts of data or collect information from different sources. They are also used by organizations that want to simplify access to data.
Data warehouses can be helpful to all organizations that want to benefit from decision support. This includes users who wish to manage reports, charts, or graphs based on data. However, they are used differently depending on the industry.
Aviation industry: Airlines use them to provide customized offers or assess the profitability of routes.
Banking: Banks use data warehouses for asset management, market research, and product performance analysis.
Healthcare: In the healthcare sector, data warehouses report patient conditions, predict patient outcomes, and share information with insurance companies.
Insurance: The public sector uses technology to collect data and analyze tax and health policy reports. The insurance sector uses them to study consumer behavior and market trends.
Retail: Retailers use data warehouses for marketing, distribution, inventory management, logistics, customer research, price optimization, and customized advertising campaigns.
Telecommunications: In this sector, promotional activities, sales, and distribution decisions are based on data.
Tourism and Hospitality: Finally, advertising and promotions in these sectors can be inspired by the tastes and habits of visitors.
When Is the Best Time to Buy a Data Warehouse?
In a nutshell, it depends on the company’s development stage, the amount of data, financial constraints, and other factors.
Premature use of a data warehouse can be avoided by connecting a business intelligence (BI) tool directly to the production database.
Still, trying to convince you that a data warehouse is the best solution for your company? Follow the tips below:
Analyze Information from Different Sources
Your organization needs to integrate data from different internal technologies to make smarter, more informed business decisions.
For example, to measure the relationship between orders and service (i.e. when staff are busiest during the week and when they are most available), a restaurant needs to combine sales data from its POS system with staff data from its HR system.
Doing these analyses is much easier if the data is collected in one place.
Transactional Data Be Separated from Analytics Data
As mentioned above, analytics is not the true purpose of transactional systems. Therefore, it is generally not a good idea to store activity logs or other potentially valuable data in an application database and allow analysts to work directly with the production database.
Instead, it is recommended that you purchase a data warehouse capable of handling complex queries and feed analytics data into it. This way, analytical activities will not impact application performance.
Queries To Run on The Original Data Source
Most BI tools, for example, need to work better with NoSQL data sources such as MongoDB. For data analysts to work effectively with applications that use MongoDB internally, the analytics data must be moved to the data warehouse.
Perform Analytic Queries Better
Creating aggregate tables that summarize transactional data in a more query-friendly format is usually good if the data contains hundreds of thousands of rows. Otherwise, queries will be extremely slow and overload the database. You should purchase a data warehouse if you want your analytic queries to perform better.
Given the low cost of data warehouses in the cloud computing era, purchasing a data warehouse is generally a good idea.
Final Words
A data warehouse is a powerful tool that improves decision-making by transforming data into a single source of truth, conducting sophisticated analytics, simplifying data access and interpretation, and fostering collaboration and idea sharing. By harnessing the power of a data warehouse, organizations can improve their success by making more informed decisions based on data.
At ExistBI, we pride ourselves on being leaders in developing data solutions, no matter the size of your organization. With decades of experience, you’ll gain the competitive advantage you need to succeed.
