In the era of information and data management, data integration is a necessity rather than an added value. Without data integration, organizations cannot leverage the value of their data or transform it into business intelligence. We reflect on the importance of data integration in the business world.
“We're not in an information age anymore. We're in the information management age.” Chris Hardwick, actor.
The information age describes a context in which the abundance of information is something extraordinary. This places us in the age of information management, where the abundance of information is no longer news and, instead, the difficulty lies in managing the massive amounts of information.
This is where, data integration, which is the ability to group and merge data assets that originally live in different places and have disparate formats, becomes important.
Data integration is one of the essential requirements for achieving good data management and fostering a data-driven culture within a company. It could be said that data integration is the basis in which data-driven decisions are built.
The primary goal of data integration is to bring together all of a corporation's data in one place, whether it is a standard database, a data warehouse or a data lake. However, a fundamental part of data integration involves data transformation, validation and consolidation. Therefore, data integration is a process that goes beyond the integration itself. For data to be useful, it must be transformed and the teams responsible must be able to validate its veracity and quality (data quality).
La integración de datos parte de la recopilación de todos los datos de los que dispone una compañía, extrayéndolos de los múltiples sistemas, softwares, dispositivos y aplicaciones donde puedan estar almacenados. Una vez se han recopilado, los datos son limpiados. El proceso de limpieza de datos consiste en eliminar todo aquello que sea innecesario —valores nulos, información redundante, datos que no contienen valor para la empresa, etc.—. A continuación, se filtran y se validan: se comprueba que todos los datos sean verídicos, que estén actualizados, que no contengan errores y que sean de interés. Una vez los datos están completamente ‘pasados a limpio, se convierten a un mismo formato para que puedan ser trabajados y analizados en su conjunto y la empresa pueda realizar todas las agregaciones y comparaciones que desee. Por último, los datos ya curados se integran en data warehouse.
If we have data stored in different places and in disparate formats, analyzing them as a whole is virtually impossible. This is precisely the purpose of data integration, to make all data compatible with each other and accessible from any device, system, application or software, so that all team members can access the information they need and base their work on reliable and valuable information.
Furthermore, this is a never-ending process and, once the first integration has been carried out, the new data must be integrated with the existing data, as well as being inventoried and updated from time to time.
A glimpse of reality
Data integration is a process much older than technology and has been going on for as long as data has existed. Before digitization transformed our lives, data integration took place physically in libraries and archival classification buildings. These spaces are still environments where information is integrated, sorted and filtered to facilitate access to it by third parties. If data integration has been done for as long as data has existed, not doing so in the digital environment would be a big mistake.
There are many reasons why every company should have an internal or external data integration process. The first and most obvious is that it is the process by which all enterprise data is made functional, reliable and comparable. In other words, it mitigates the complexity of the data and makes it operable.
Companies often store large amounts of data, either consciously or unconsciously, and typically, different departments store different data in different formats. This is exactly where data integration comes into play and why it can help improve your business performance.
What is the point of having a large amount of information if it cannot be analyzed as a whole?
If you think about it, there is no point. Having different data sets in different formats and not being aware of where they are, what they mean and what they are for is useless. Raw data is worthless because it is impossible to understand and analyze. For data to be transformed into valuable information, it must first be unified, formats must be made compatible and validated.
In fact, studies show that data scientists spend almost 60% of their time collecting and preparing data for analysis. This means that more than half of their work time is spent doing tasks that data integration can ease.
Furthermore, data integration is the only way to achieve a global and complete vision of the business and business activity, as well as to ensure that all departments, operations, middle management and business strategies move in the same direction, respond to the same objectives and, ultimately, are based on the general interest of the company, which, thanks to this comprehensive overview, will be much more conscious, clearly defined and present in the conscience of the entire team.
Let's see it from an example. Imagine that your company wants to launch a new product or service on the market. Before doing so, you will have to carefully study various aspects related to the launch strategy: the performance and characteristics of previous products, the competition, the market, the profiles and behavior of target customers... Just considering the most basic things, we are already talking about at least 10 different data sets to analyze, which are probably stored in different systems. Normally, each set is analyzed by different people who, in turn, have different perspectives, since they only have the information that is relevant to them and do not have access to the big picture. This, needless to say, is a mistake. In order to bring a new product to the market or to carry out any business operation, it is essential that the data can be compared with each other and analyzed as a whole. This is the only way to reach truly valid conclusions and make informed decisions that will lead to good results.
With data integration, all departments in the company have access to the information they need - obviously, access to the data can be managed and restricted as desired. In addition, the data has already been cleansed, filtered and consolidated, so drawing conclusions is much more agile, reliable and secure.
For all these reasons, data integration can increase the knowledge you have about your company and, consequently, optimize the business intelligence area, drive new business strategies and facilitate better decision making, which, in turn, will lead to better results. In short, data integration can have a significant impact on the productivity and performance of your business.
In addition, on a more practical side, it greatly streamlines the work of all team members and allows you to work with far fewer technological resources, since, through this system, it is not necessary to move data from one place to another and transform it every time we need to use it.
If the global progress of the company in all its areas is not enough reason to go for data integration, we show you 10 other more tangible and immediate advantages:
The data is processed, filtered and validated so the information you get from it will be 100% reliable. In addition, the data will always be updated and without any errormistakes, ready to help you!
The automation of data collection, processing, transformation and consolidation will result in an incredible reduction in the workload for analysts and data scientists, who will be able to dedicate this time to other more productive tasks.
Integration makes it possible for all company data to be managed from a single centralized location, which also helps to identify errors or mismanagement and reduces management and administration time.
Data integration standardizes all types of data and makes them accessible, no matter what format they are in. In many cases, companies miss important data in their analysis because it is either lost along the way because analysts do not have access to it, or it is in formats that are too complicated to extract and unify with other data sets. Data integration solves this problem and makes it possible to leverage the value of all the data.
Data integration can become the engine for creating new business strategies that are more conscious and beneficial to the company.
The process helps to ensure the security of your data, which will have been managed and transformed so that no one other than the relevant people can access it.
Centralized and single administration also facilitates compliance with data protection-related laws. In the European case, the most important is the GDPR.
Having the data integrated in a single storage location that is updated allows for a historical record of information.
Gaining knowledge and validating data involves mitigating the risks that can arise from poor data management.
The automation of tasks and the release of part of the company's physical and human resources leads to significant cost savings. In addition, data integration does not have a high cost, so the return on investment of this process is high.
Before you go...
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