When ChatGPT, Claude, or Gemini claims that data is king nowadays, there is no exaggeration. However, things are not as straightforward as they may seem at first.
Acquiring data is not a big deal; in fact, not many businesses complain that they lack any data. The complex things begin when they need to store data, systemize it, and use it effectively. If such questions arise, it is time to discuss the benefits of data warehouse – a solution that addresses most of the storage- and usage-related problems while providing all the needed tools for business intelligence and analytics.
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Databases are not a solution anymore?
A question that often arises in the context of having a data warehouse is, “We have a vast database, why do we need to change anything?” This usually indicates that people who ask it do not clearly understand the difference between a data warehouse and a database, and have never heard about the data warehouse benefits for business.
To make things crystal clear here once and forever, we have prepared a comparison of the two approaches to information storage discussed here.
Database
- The main goal of a database is transactional processing. It stores data from one or several sources that might be used for day-to-day tasks, such as adding, editing, and deleting information for business processes.
- Stores data in rows and columns using a relational model. It is optimized for processing frequent requests from the user, such as updates, edits, and retrievals.
- Is based on a dimensional model. Uses a combination of fact tables for quantitative data and dimension tables for descriptive data. It is optimized for complex analytics and queries.
- Is optimized for processing small and frequent requests.
Data warehouse
- Data warehouse is a perfect choice for analytical processing. It stores historical data from numerous sources. The main goal, in this case, is analysis and systematization, not day-to-day tasks. That is why it is considered one of the best Big data analytics solutions.
- Is based on a dimensional model. Uses a combination of fact tables for quantitative data and dimension tables for descriptive data. It is optimized for complex analytics and queries.
- Is built for processing complex requests. Can analyze multiple layers of historical data.
In simple words, it is not technically correct to talk about the benefits of a data warehouse over a database, as they are used for different things. A database is a good solution if you run an online store and need to update the list of available products on a daily basis.
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Data warehouses, on the other hand, can be used for analyzing how the customer needs and trends have been changing through the years and what they can be in the future. Thus, talking about the advantages of a data warehouse over a database is incorrect, as they have different goals. You can have both simultaneously.
Financial aspects of having a data warehouse
One of the advantages of using a data warehouse is its flexibility in terms of price. It is easy to configure one for a business, considering its needs, budget, and goals. There are several important factors to consider, though, when calculating a data warehouse price.
- Cost of the initial setup. Luckily, nowadays there are lots of titles for any purpose and budget, so choosing a solution should not be challenging (but still time-consuming). There are two main options: having an on-premise hardware+software setup or using a cloud-based service. A team of data architects and engineers may also be needed to configure and maintain it. Finally, consider the on-time cost of data migration services (if you already have a certain array of data you want to relocate).
- Ongoing costs. Most data warehouse use cases require a team. Depending on the level of seniority of such specialists, their salaries can be pretty high. Add to this system updates and technical support for the setup, together with the storage fees (usually paid for the amount of storage data).
A typical price range for data warehouses is vast: from $30 000 up to $1 000 000, depending on all the things mentioned above. Of course, the price can hardly be called one of the benefits of a data warehouse, but there is also another aspect – ROI.
The business value and advantage over competitors that a data warehouse can lead to often justify its high price.
For instance, it can save employee time and costs by automating data gathering, provide deep analytics needed for making effective decisions, and give a better understanding of a customer profile for better targeting. Add to this a large number of data warehouse companies for any budget and scale. All these aspects are later transferred into pure profits, which should be higher than the cost of the data warehouse.
10 advantages of a data warehouse
It is a common thing to wonder about the advantages of any decision before making it. Switching to a data warehouse concept often costs a reasonable amount of money, so such a decision should be well-thought-out and considered. We have prepared a list of 10 noticeable advantages of a warehouse for any business to help with this.
Focus on business intelligence and analytics
This is one of the most important benefits of a data warehouse in business, especially if the latter uses various tools for customer data collection.
A properly configured warehouse serves as a foundation for effective business intelligence and analytics. It is specifically architected and optimized for complex analytical requests. It uses different data models (for instance, snowflake deployment or star schemas) and indexing strategies developed for working with large amounts of data.
Another essential data warehouse benefit is that it may store data for extended periods, depending on the configuration, even for years. This is needed for business intelligence, as it allows for trend analysis and predictive modelling. Without being able to analyze past data, it is impossible to identify seasonal trends, understand long-term customer behaviour, and evaluate the company’s performance and progress in detail.
Moreover, any successful business operates in the present but thinks about the future. Analysis of historical data enables the prediction of future trends, which is essential for more informed strategic planning. Among all the advantages of a data warehouse, this is one of the most decisive.
Optimized budgeting and speed
What is better: to gather pieces of data from multiple sources, often asking colleagues or technical specialists to help, or to get everything one needs from one source? The first approach is extremely labor- and time-intensive, while the results it provides are not guaranteed to be 100% trustworthy.
Talking about data warehouse advantages, we cannot skip the fact that it gathers tons of data from different sources in one place. Moreover, with the help of AI algorithms, it can perform cross-checking of the available information and identify the most current and reliable data. This saves a lot of time for the analysts, who can now access everything they need in one place and make more effective decisions.
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This, in turn, leads to strategy and budget optimization. In Australia, for instance, the majority of businesses complained that the lack of evidence and proper analysis leads to devastating financial losses, and there is no reason to think that the situation is different in other areas. With deeper analysis, businesses and organizations can get better insights about the coming trends and proactively adapt to them.
Better data quality management
The flows of data coming from all possible sources are becoming bigger and bigger almost every day. This leads to several questions:
- how to distinguish between the reliable data and the data not from credible sources;
- how to ensure that at each particular moment one works with the most up-to-date information;
- how to organize the data storage in the required formats.
Moreover, managing data can become extremely difficult and time-consuming, especially when several platforms are involved. This is when combining data in a data warehouse solves all the issues.
Among the many advantages of using a data warehouse is that it allows comparison of multiple sources and identifies data duplicates and inaccurate instances. Most warehouses also include an automated algorithm for cleaning the dubious information, eliminating the need to buy additional software or hire a specialist. Most Big data development services do not consider any other data management solutions except for warehouses.
Increased security
With the amount of data increasing, new cyberthreats also appear. The Council of the European Union reports that cyber threats cause losses of trillions of dollars every year. Data security becomes one of the first priorities for all businesses, especially for those dealing with sensitive information, such as banks or medical companies.
One may say that storing all the data in one place cannot be considered an advantage of a data warehouse. When localized, information is easier to steal. On the other hand, it is easier to protect as well, and that is what centralized data storages constantly work on.
Data warehouses implement encryption techniques to protect both data that is already stored and data that is being moved. They also protect information by providing access only to authorized users, preventing unsanctioned copying and processing.
All in all, when such a warehouse is configured accordingly, data is much safer there than anywhere else, which makes it one of the most significant benefits of data warehouse in banking and healthcare.
Space for business automation experiments
It would be weird to live in the XXI century and not think about process automation where it is possible. Working with various databases and data lakes makes it more difficult due to many sources in the first case and a lack of systematization in the second.
When all the data is stored in one secure and organized place, data warehouse automation becomes possible, preventing the human-related mistakes that can cause big financial losses.
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An enterprise data warehouse, for example, can use different software-defined workflows to make the processes of data extraction and transfer automatic, reducing in such a way the time required to collect and process information for any possible need. Even data analysis can be automated to get the results faster. In other words, any automation idea is easier to implement with a data warehouse.
Compliance with privacy policies
It is impossible to review any operations with data nowadays out of the context of privacy policies, such as GDPR, HIPAA, or CCPA. Any organization that operates with data must have a clear audit of how it accesses and when.
Talking about the benefits of a data warehouse in this context, it has built-in auditing features that log user activity – all the changes and accesses. Moreover, it records the full life cycle of any piece of data – where it was acquired from, where it was used, and how it was transformed.
All the sensitive information that is not supposed to be accessed by unauthorised personnel can be masked by a realistic-looking value, which data analysts can use without compromising anyone’s privacy. Moreover, every piece of information can be encrypted for secure storage and transmission between systems.
Scalability and growth
There are two main ways a warehouse can scale:
- vertically (scaling up): adding more hardware power to the server – storage, RAM, etc.;
- horizontally (scaling out): adding more machines to distribute the workload equally.
These two data warehouse concepts ensure that while the amount of data a company processes grows, the performance of the warehouse does not suffer, and all the usual operations do not take longer.
Another important point here is that such a model can be easily adapted to any business’s new requirements without global changes in data warehouse architecture. It is a common practice for modern data warehouses to have the processing power separated from the storage. This means that should a company face more requests at some point, they can independently add more compute power, and if the amount of data increases – vice versa.
International hosting and cloud
Many businesses nowadays operate internationally. This brings several serious considerations to how they can operate effectively, which can be solved by having a cloud data warehouse.
- Different countries have different laws and regulations on how data can be processed and gathered. For instance, in Europe, it is GDPR, and in the USA, it is CCPA. A general rule for data to be compliant with corresponding regulations is that it is hosted in the area where they operate.
- Global companies with international staff face serious problems with latency when all the data is stored in one physical location. The benefit of a cloud-based data warehouses is that they can be hosted in different regions, placing the data closer to the end user, improving general performance.
- Hosting cloud data warehouses in different regions increases the business’s resilience to natural disasters, power shortages, blockages, and other types of events that can disrupt the company’s operation flows.
Although there are many misconceptions about cloud data warehouses, most of them do not stand up to any criticism. They are not more expensive, they can also be compliant with all the needed regulations, and the control over their deployment is the same as if you had their physical equivalent.
Perspective for machine learning
Among all the benefits of a data warehouse, there is often forgotten: it provides an ideal environment for machine learning and data science. Considering how a warehouse operates – structures data, analyzes it, checks for credibility – it does all the preparation work needed for starting building artificial intelligence models.
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Furthermore, all data from different sources is gathered in one secure place, which creates ideal conditions for training and testing different models on the same data sets. Data analysts can be sure that everything is checked under the same conditions. This drastically accelerates the development of AI-based applications and modern AI initiatives.
Improved customer experience
We have already mentioned a lot of benefits of data warehouses, but there is one more we would like to talk about before rounding up. It concerns companies that directly sell products and services to their customers. Such businesses gather information about their clients to provide better services and understand the directions for further development. When such data is stored in a data warehouse, companies get significant advantages in several aspects:
- Thanks to centralized data analytics for business, they can understand client behaviour better;
- They can observe patterns in customer complaints and clearly see in what areas they need to improve;
- They can link the customer profiles with their products and recommend more relevant services or products in the future.
Forbes highlights that, compared to data lakes and silos, data warehouses are the most reliable and modern solution for data storage and analytics, and it is hard to argue that more and more companies and businesses will switch to using them every year.
Conclusion
We are not mentioning the limitations of data warehouses here, not because there are none, but because their benefits outweigh all the potential issues, especially compared to their alternatives. For business users and decision makers, switching to a data warehouse brings better analytics, better insights, better security, and a better understanding of their customers.
For business intelligence specialists – a faster and more convenient environment with better-quality data. Considering that nowadays hosting a cloud warehouse is not a problem at all, and data warehouse consulting is a service available to everyone, there is no better solution for international companies that operate massive arrays of information.
