How do you best standardize your data collection procedures?
Data collection is the process of collecting and analyzing information on relevant variables in a predetermined, methodical way so that one can respond to specific research questions, test hypotheses, and assess results. Data is a collection of facts, figures, objects, symbols, and events gathered from different sources. Organizations collect data with various data collection methods to make better decisions. Without data, it would be difficult for organizations to make appropriate decisions, so data is collected from different audiences at various points in time.
Data collection is a systematic process of gathering observations or measurements. Whether you are performing research for business, governmental or academic purposes, data collection allows you to gain first-hand knowledge and original insights into your research problem.
While methods and aims may differ between fields, the overall process of data collection remains largely the same. Before you begin collecting data, you need to consider:
- The aim of the research
- The type of data that you will collect
- The methods and procedures you will use to collect, store, and process the data
To collect high-quality data that is relevant to your purposes, follow these four steps.
For instance, an organization must collect data on product demand, customer preferences, and competitors before launching a new product. If data is not collected beforehand, the organization’s newly launched product may fail for many reasons, such as less demand and inability to meet customer needs.
Although data is a valuable asset for every organization, it does not serve any purpose until analyzed or processed to get the desired results.
In a society in which information and data are the key to any activity or business, it is very important to know how to standardize data to be able to get the most out of it and performance.
With globalization and the information systems that are used in our daily lives, the amount of information and data we have at our disposal is immense. The problem is knowing how to manage such an amount of data, how to collect it, how to treat it, classify it and apply it . In this sense, data standardization can be of great help.
Aware of the importance of knowing how to standardize data, at Ayuware , as experts in big data, we have prepared this post with relevant information about the advantages that this procedure offers and all the benefits it provides, so that you can know exactly what it is about. treats.
What is standardizing data?
Data standardization is the data quality process of transforming data to fit a predefined and constrained set of values, relying on the power of uniformity to improve data efficiencies.
Data standardization, sometimes also known as normalization , is the process of adjusting or adapting certain characteristics so that the data resembles a common type, model or normal with the aim of making its treatment, access and use easier for people. the users or people who have them.
The very concept of open data implies a search for standardization in the use of information in open format so that it can be used and reused by citizens.
Therefore, it could be said that standardization is the way in which all people can compare and consult data and always find the information they need, being certain of uniformity in the way in which they will find it.
In statistics, normalization or standardization can have a wide list of meanings. In the simplest cases, standardization of indices involves adjusting the values measured on different scales with respect to a common scale.
On the other hand, in more complex cases, data normalization or standardization can refer to making more sophisticated adjustments where the objective is to obtain all those probability distributions that fit the determined values.
In short, it could be said that without standardization and, therefore, without uniformity in naming conventions and coincidences between macros and parameters, only unreliable results can be obtained.
Importance of data standardization
Before knowing how to standardize data, it is important that you know the importance of this process for the correct use and processing of information in an effective and functional manner.
Data standardization allows us to ensure that we will have useful, easily linkable and usable data at our disposal for any activity we require.
Data standardization not only helps us organize sets of complex information , but it will also facilitate its analysis since it breaks down multiple dimensions and transforms the information into viable insights.
Committing to standardize data is a way to ensure that we implement the uniformity necessary to maintain the effectiveness of your analysis . As we know, information, today, is power and, therefore, having standardized and optimized information is a great advantage both on a personal and business level.
In this sense, data standardization has gone from being a good practice or something recommended, to being a necessity for all those who want to get the most out of the data and information they have at their disposal.
Now that we are getting closer to knowing the process on how to standardize data, it is important to keep in mind that, for it to be possible, it is necessary for institutions to work together to develop standards since, for a standard to exist, it must be used by a large majority for it to be considered implemented.
Furthermore, data standards and normalization imply good practices such as monitoring, control, keeping in mind at all times that the information is useful to anyone who wishes to use it, etc. Thanks to these good practices, the process of how to standardize data is effective and provides all the advantages mentioned above.
To know how to standardize data correctly, it is necessary to pay attention to the planning prior to collecting the information , in addition to thinking about the feedback of said information from the publication of the data in an open and public manner.
Key moments in data standardization
To know how to standardize data, it is important to know that there are three key moments for the process, in which it is necessary to pay attention to carry out the process satisfactorily:
- Standardization in data capture : For the data standardization procedure to be correct, it is necessary that the data be collected optimally, following guidelines that will greatly facilitate the following steps.
- Standardization at the time of data storage : Once the information is collected, it is very important to pay attention to how the data is stored, to do so in an orderly manner and to provide all subsequent facilities for its recovery and consultation.
- Standardization in the presentation of data : This is a fundamental moment since, after carrying out a search for data that we may need, it is very important that these are displayed in a standardized way, so that we can make use of them in a useful and functional. If all the previous steps have been carried out correctly, this last moment should not present any problems.