Updated June 19, 2023
Introduction to Data Warehousing
The world of business and brands by storm is taken by data warehousing. With their rising popularity, they have become an integral part of business management as they help companies use data strategically and easily. However, before going in-depth into data warehousing, it is essential to step back and gain a better and clearer idea about data warehousing and how brands can create one that can cater to their needs and requirements successfully.
What is Data Warehousing, and Why is it Important?
Over the past few years, almost all companies have realized the importance of collecting and analyzing data to make better decisions and create better campaigns. Almost all companies have a record of all their transactions since their establishment. This data type might have been collected over many years and spread over sources like mainframes, proprietary systems, and sometimes client-server applications. Further, this data spread over several sources might be collected and integrated by different people. With so much data in a single company, it becomes difficult for the IT team to collect and use it to benefit the entire organization.
The answer to this question might seem straightforward, but its implementation is less so. To make sense of data, it is essential to assemble all the data in one place and create a database. But the person who collected the data ten years ago might have already left the company. In the same way, the consultants who were hired to build the proprietary system may have moved on to other jobs. In addition, while running reports against the client-server system, the reports may be fairly rigid, and once they are printed, they cannot be changed or customized. So every time a company requires a specific report, they might have to pay a premium rate to a programmer or an outside consultant to access that information. This defeats the entire process because the main goal of data warehousing is to help companies gain easy and simple access to their data history.
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It is here where advanced online analytical processing tools can help data warehouse users generate company reports with just a click of the mouse, enabling company representatives to look at their performance from various angles. The amount of data that needs to be examined depends upon the nature of the business concerned. For example, a manufacturing unit might be interested in knowing the number of products they manufacture at a particular time. The company might also want to know how many defective pieces were manufactured during that period. Data analysis can help companies decide the number of units being manufactured by the company over a particular period in an effective manner.
Similarly, a travel agent company might want to determine the number of people they serviced during a particular period. By analyzing trends of tourists and customers, travel agents can plan better campaigns and plans that maximize their reach and profitability. It is precisely here that companies can use data that are a part of their system by building a data warehouse.
Therefore, data warehousing is a dream for all business analysts as it gathers all the information about a company in one place, making it accessible for analytical analysis and research. However, before setting up a data warehousing system, companies must understand a few things because the purpose of data warehousing is to provide organizations with accurate information so that marketers can use it to create effective and successful campaigns to meet the goals and objectives of the company.
How to Implement Data Warehousing?
Here are a few steps that the company must invest in so that it can effectively implement data warehousing:
1. Determine the objectives of the company
Every company is unique, and they have its own set of goals and objectives. If a company is in its initial stage, its objectives are very different than when it would be in an established phase. Companies require a good mix of sales, production, administration, and support personnel. Proper data analysis can help companies make important decisions, like whether it is a good idea to improve resources like machines or staff personnel for growth. If the company invests in new campaigns and strategies, it will pay them well to know if they will work out as planned. While external forces may always change and remain beyond control, data warehousing companies should strive to adapt and respond to them in the best possible manner, like an atlas guiding their actions.
Further, it is essential to understand that different brands identify success differently. The main pillars of any organization include the owner, the president, and the managers. While the managers oversee the profit centers, they also have their areas of expertise and control.
In addition, the managers in a company would also share personnel, contacts, sales opportunities, and resources to reach goals and ambitions effectively. By measuring different the health and growth of a sector, managers ensure the smooth running of the entire brand. While everyone in the company enjoys gross profits, big decisions that affect them are usually taken at the top level. A small contract might sometimes require as much, if not more, hard work as a big contract. Also, sometimes many small contracts might contribute as much profit as one large contract. Therefore, brands and companies must focus on tracking contracts and ensuring they objectively meet their goals. That is why companies must track key performance indicators like units sold, net profits, gross profits, and customer targets achieved, among others, to help companies maintain their growth trajectory. Companies use data warehousing to track numeric data to effectively realize their goals and objectives.
2. Collection and analyze of information to help companies reach the said goal
A company can only gather credible and essential information by asking questions that matter. The leaders have sources of information that they use to make decisions. Start with data sources that are present in many organizations. Some data sources include reports from customer relationship management, account packages, and time reporting systems. By collecting reports and their copies, brands can access credible and valuable information. In many organizations, analysts, and supervisors create analytical and summary reports of the brand, which can be extremely helpful and valuable. Various sources can provide data, ranging from simple correlation reports to information stored in software, memos, and spreadsheets.
Sometimes many sources of information like telephone logs, a desktop database that tracks shipping dates, and daily reports of supervisors may be overlooked and stay hidden. This data source is also important from a company’s point of view; tracking them can benefit brands. One of the biggest challenges of data warehouse designers is finding a way for companies to collect the type of data mentioned above. Many companies do not keep track of this information as they consider it unimportant or incorrect. But brands must always remember that no data is inconsequential and that everything has a particular role in the company’s growth and development. Another aspect of this collection and analysis is understanding how people gather and process the information. Data warehousing can automate many reporting tasks that have been identified, requiring extensive interaction with the persons of the companies. All this can help a company to create a good warehouse system. When brands clearly understand the data warehousing process, they can design the warehouse.
3. Identify the core process of the business
After identifying the business process and key performance indicators, brands must identify the entities interlacing these two aspects. For example, if a company needs to start a new training program, it must consider several business and resource factors. When holding a training program, it is essential to consider the place, as not all clients or people can attend it. Sometimes the client might not share a relationship with the said company. Also, the client might need to adapt to new products such as Windows 2000.
The data warehouse is a collection of interrelated data structures. Each structure stores key performance indicators for a specific business and correlates them with factors that generate them. Gathering key performance indicators into a fact table becomes extremely important from a business point of view. Data warehousing has a group of fact tables based on each subject. Fact tables can share dimensions and relate them with other tables. In short, a data warehouse can help brands use key indicators of their companies to achieve bigger goals and objectives on the one hand and create effective sales campaigns and solutions on the other hand.
4. Construction of a conceptual data model
Once a business has identified its process, it must create a conceptual data model. For this, the company must determine the subjects expressed in fact tables and dimensions related to these facts. It is important that brands identify the performance indicators and how they should be stored. Data must be consistent; most facts must be put together in an OLAP cube format. While the process might seem simple, in reality, it is not. For instance, if a company is international, they must choose a currency format.
The currency will convert or change the stored currency according to the exchange rate. So exchange rates will also be a separate factor in the data warehouse system. Populating and maintaining data warehouse structures is a complex and time-consuming process that involves intricacies and challenges in construction. That is why companies need to plan their data structure carefully to avoid restructuring at a later stage.
5. After locating data sources, companies need to plan data transformations
Companies must identify the critical source of data they require and then transfer it to the data warehouse structure successfully. For instance, some sources of information may include custom-in-house applications and CRM package sources, and there might not be any correlation between them. As different systems do not share similar information or systems, and that is why companies need to reconcile different platforms so that they can be copied seamlessly into data warehousing tables.
Further, companies need to scrub the data and ensure no blank spaces are left in the data system. If there is a blank space, it can affect the entire data warehouse project. That is why source data needs to be complete before data warehousing is finally implemented in the companies. Simultaneously, it is crucial to keep bad data out as it significantly impacts the entire process and incurs substantial costs for the company. By correcting the data at the source, companies will ensure they generate all the corresponding data at every stage.
6. Set the duration of tracking for the data warehouse
Such large amounts of data in the data warehouse structure will consume a lot of space. However, as a data warehouse will track performance over time, data must be permanent and virtually available at all times. But then, this would require unlimited storage capacity, which is impossible. That is why it is possible to summarise and store data in different structures in data structures, thereby reducing the space it takes up in the entire structure.
7. Implement the plan
After a business has developed a plan for data warehouse structure, create a basis for estimating the work and scheduling the project. As the scope of a data warehouse is large, it is essential to have a phased delivery system to keep the entire project on track. In addition, data warehousing systems provide decision-makers with consolidated and consistent data about their organization. A company can move through the growth trajectory impressively and successfully.
Conclusion – Data Warehousing
The data warehousing system is critical in today’s business environment as it can help companies deliver solutions on the one hand and successfully understand market trends. In conclusion, a data warehouse is one of the most important systems through which brands across categories can realize their goals and objectives, both within and outside the organization.
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