The enormous amount of data and information that a company generates and consumes today can become an organizational and logistical nightmare. Storing data, integrating it and protecting it, so that it can be accessed in a fluid, fast and remote way, is one of the fundamental pillars for the successful management of any company, both for productive reasons and for being able to manage and give an effective response to the customers.
Good big data management is key to compete in a globalized market. With employees, suppliers and customers physically spread across different cities and countries, the better the data is handled in an organization, the greater its ability to react to market demand and its competitors.
Databases are nowadays an indispensable pillar to manage all the information handled by an organization that wants to be competitive. However, at a certain point of development in a company, when growth is sustained and the objective is expansion, the doubt faced by many managers and system administrators is whether they should continue to use a database system, or if they should consider the leap to a data warehouse. When is the right time to move from one data storage system to another?
As a company begins to accumulate terabytes of big data from multiple sources and growth forces multiple tasks and analysis with this information, having different databases scattered can become a big competitive burden. Having to query each database independently, without being able to cross-analyze seamlessly, is inefficient, insecure, slow, and costly.
When the integrated storage of all data is a pressing need for the development and expansion of a company, the solution recommended by leading system analysts is to implement a data warehouse.
What is a data warehouse?
A data warehouse (also known as DWH) is a database designed to store, filter, extract and analyze large collections of data (suppliers, customers, marketing, administration, human resources, banks, etc.). The particularity of these systems is that they are specifically developed to work with big data, allowing to visualize and cross analyze the information simultaneously, without having to mix and consolidate results from different data sources.
A data warehouse is designed to separate big data analysis and query processes (more focused on data reading) from transactional processes (focused on writing). This approach therefore allows a company to multiply its analytical power without impacting its transactional systems and day-to-day management needs.
The data warehouse is a highly recommended tool when you want to make sure that inexperienced users in the management of systems and databases don’t put at risk the information of a company. Given the three-tier architecture used in these solutions, DWH end users can query their data stores without touching or affecting the operation of the system in any way.
In short, the architecture of a data warehouse is based on three levels:
- Lower level - is the server, where the data is loaded and stored.
- Intermediate level - contains the analysis engine used to access the data.
- Upper level - the front-end client that presents the results of the analysis using data visualization tools.
Benefits of a data warehouse
If we were to summarize the benefits of a data warehouse, we could say that it is an indispensable tool for any modern and ambitious company, as it allows decision makers to access data quickly through business intelligence tools, SQL clients and other analytical applications. In addition, they are characterized by:
- Separating processing and analysis of big data from transactional databases, which improves the performance of both systems.
- Consolidating big data from different sources.
- Bringing greater quality, consistency and accuracy to the data handled by a company, resulting in better decision making by its management team.
- Since all the information is deposited in the same central warehouse, a higher quality of the data is guaranteed, and the time required for the generation of reports and analyses is optimized.
- Facilitating the elimination of duplicate records, errors and inconsistent information.
- Increasing consistency in internal reporting by standardizing and centralizing the data sources handled by different departments.
Basic differences between a database and a data warehouse
|Designed to store data from a very limited number of sources.||Designed to store data from an unlimited number of sources.|
|Efficient for processing transactional operations.||Efficient for analyzing and aggregating large volumes of data.|
|Its capacity for data analysis and integration is limited.||Allows to visualize data and extract reports from complex data quickly.|
|Fast and less costly implementation.||More costly and laborious initial implementation.|
|Ideal to see the current state of a company.||Ideal tool to study the evolution of a company and make medium- and long-term projections.|
In the cloud or on a local server?
Data warehouses can be installed on a corporate server or in a cloud warehouse. The latter formula is becoming increasingly common, as it allows companies to address in a more practical and scalable way the growing need to access more and more data.
Among the advantages of having a data warehouse in the cloud, the following stand out:
- Data security and protection throughout its life cycle. Cloud service providers need to take the daily update of their security and backup protocols to the next level.
- The scalability of the storage system is much easier.
- DWHs in the cloud are cheaper, as they do not entail high up-front hardware costs and proprietary software licenses.
- The installation and commissioning of a data warehouse in the cloud is generally faster.
- Cloud services connect more easily to other services in the cloud, which in turn results in greater system efficiency.
At the same time, installing a data warehouse on a local corporate server also has its advantages:
- Cloud solutions tend to be based on servers that are very far from the end customer, so there can sometimes be a slight delay in consulting the data that some companies cannot afford. Speed and latency on local servers can be better managed internally, at least in business cases that are confined to a particular geographic location.
- There is greater control over server security and data access, which for some companies is an absolute priority.
- If a company has a highly qualified IT team and state-of-the-art hardware, a fully internally controlled data warehouse is a winning choice.