Understanding Data Warehousing and Its Importance for a Business
Modern businesses rely on data and data strategies for marketing, establishing brand identities, and gaining/maintaining a competitive edge. A crucial concept in data management is data warehousing. Let’s take a look at what this means and what role it can play for a business.
Data warehousing is a process through which a company collects data from a variety of sources, and pools it in one centralized location. The purpose of doing so is to discover business insights by diving into a sea of data with the use of various data analytical and mining tools. The concept of a data warehouse is different from the standard database that you usually hear about on the internet. A data warehouse is separated from an operational or transactional database for efficiency and productivity.
If an organization were to use its data warehouse for transactional purposes as well, any query run through the data would result in slowing down the transaction. This would negatively affect business operations. So, a data warehouse of an airline would be in one location and its operational database would be located in another. If they were the same thing, using a tool to find a specific pattern for business insight would result in slowing down or completely freezing the booking of a ticket.
The data that gets stored in a warehouse can be unstructured, semi-structured or structured data. Managers use BI (business intelligence) tools to find patterns, trends, and insights to help them with business decisions, forecasts, etc.
The Different Data Warehouse Types
These are data warehouse subsets – a small part of the data warehouse serving a particular group of users. A data warehouse is the central location where all the organizational data is stored, whereas the sales, marketing, finance, etc. departments might have their individual data marts.
This type of database benefits an organization’s daily needs because it gets updated in real-time. Keep in mind that a data warehouse does not necessarily update in real-time.
Enterprise Data Warehouse
This type of warehouse has the central position in an organization. It is this database that helps business managers with decision making, forecasting, predictions, etc.
Best Practices for Data Warehousing Implementation
Analyzing Requirements and Designing
The first step for data warehousing is analyzing your requirements i.e. why you want a data warehouse and what purpose it will serve. Keep in mind that the purpose of your data warehouse is to help you achieve the goals of your organization. At this point, you create dimensional models and decide what goes into each model. During the designing process, you also have to keep in mind the nature of various data sources that will pour data into the warehouse.
Deployment of a data warehouse is completely different to how an organization implements a transactional database. Deployment of a data warehouse is incremental in nature unlike transactional database implementation that can be done in one night. The rollout plan specifies which users the database will be implemented for first, and in which order.
While the incremental deployment takes place, you have to guarantee regular maintenance of your data warehouse. Maintenance includes taking care of the hardware as well as software components. You have to keep a check on backups to ensure that you are backing up the database without any issues. Update the software and upgrade your hardware continuously for safety and security purposes and better operability.
Your data warehouse is exposed to logical and physical dangers. Human errors and natural disasters form the physical threats to the warehouse, whereas logical issues comprise crashing of the operating system, conflicts in the system’s software, corruptions of system files, etc. You have to document a complete plan and set of regulations for the logical and physical security of your data warehouse.
In the end, the most important step that you can take for your business is having the right people on board who have the expertise to manage organizational data in any form. A top down approach can prove to be greatly beneficial for an organization when it comes to data management, analytics and warehousing. For example, you can take advantage of on-demand CDO (chief data officer) services from Cruz Street Digital. An outsourced chief data officer can create an infrastructure, hire the right IT staff, and lay the foundation for a system that helps managers with critical business decisions.