Data source standardization is a process of converting the data that you cannot compare into a common data format. It is a data processing workflow. Data source standardization pulls required data from a source, transforms the datasets, and loads the data into target systems. In other words, it allows you to analyze and use the data in an accurate way.
When you create and store the data in the source system, most of the time, consumers do not understand its structure. Also, sometimes the data can be represented differently. It can create confusion and conflicts too. Similarly, the difficulty to compare and analyze the data increases. As data is one of the most crucial asset of an organization, data source standardization is necessary.
USE CASE CATEGORIES IN DATA SOURCE STANDARDIZATION
Mainly, there are two data source standardization use cases. They are:
- Source to Target Mapping
Source to target mapping is further divided into two sub-categories. They are:-
-Simple mapping from external sources
It is a use case that handles onboarding data from external sources of an organization. Then, it maps its value to an output schema.
-Simple mapping from internal sources
It is a use case that handles internal data that have inconsistent definitions. Then, it transforms the data into a credible data set.
- Complex Reconciliation
It is a use case that creates complex, calculated metrics. The metrics define its business logics that are semantics-based.
HOW TO STANDARDIZE THE DATA SOURCE
- Conduct a data source audit
Information flows through a data source into your database. So, you need to check all the sources that supply data in your business. The data sources should have comprehensive information. It makes the data standards effective. You need to know:
- Each kind of source that supplies data
- How often the sources supply data
- Which department owns the sources
- Which team uses or wants to use each source
- Brainstorm Standards
There are no rules to brainstorm the standards. Every company has its own needs, goals, and sources. So, there is no particular step to follow to brainstorm the standards. However, you need to know the relationship between the size of the data and how precise the standards should be to control the data. Data standards should be specific and cover every bit of the data. Therefore, this point is necessary while brainstorming the standards.
- Standardize Data Sources
Data sources can be internal or external. You need to pay attention to both cases. The managers, stakeholders, and employees require data in a certain way. So, you can modify or improvise the sources to fulfill the needs. Also, there is a close relationship between data sources and online customers. So, it is crucial to standardize the data sources.
- Standardize the Database
Standardizing the database can be costly. Also, it requires a considerable investment of time and skills. But all the investment is worth the results. Standardizing the database allows you to provide access to everyone in the company. They can use data of the same depth and quality for their projects. Thus, it makes the work efficient and effective.