There are measures in terms of processes, people and technology that an organization would need to take in order to untangle the data hairball.
I've previously discussed how too much data can cause various challenges and issues - this was elaborately detailed in the 'Hairball of Data' article. An overwhelming stream of data without any efficient means to organize them can lead to a chaos of information. (Read more: https://oneconnectsolutions.com/blog/hairball-of-data)
However, the article did mention that data is manageable. So continuing where we left off, in this article I will cover the steps and approaches an organization can take to untangle the hairball of data.
In order to sort out your data and arrange them accordingly to their context and meaning, let’s first cover the basic steps:
- Identify the key systems generating data.
- Create a business domain model or a semantic data model.
- The semantic data model helps an organization achieve an enterprise-wide definition of various domain data. How an entity should be represented and consumed for various analytics purposes. For example: ‘Customer’
- Data Transformations: Join various source systems data to create the business domain data based on the semantic data.
- Make this business domain data available to users for various analytical purpose.
The outcome from following the foregoing steps is achieving one version of the truth in the organization, as all analytics are served via this data layer and retrieving better insights using quality data.
The term ‘semantic data model’ which was repeated in the basic steps above is defined as the method of structuring data to represent it in a specific logical way. Semantic information adds meaning to the data and the relationships that lie between them. To put it simply, a semantic data model is focused on providing the meaning of the data allowing for data consistency, collaboration, and efficiency across different systems.
Many advantages lie in using the semantic data model, easy maintenance of data consistency is just among the several benefits. Here are some of the other advantages of using this approach:
- It translates your data into usable information that can be helpful in the decision-making process
- It provides meaning to your data and creates relevant insights from your analytics
- It places your information into context and identifies matches across your data
- It can unify similar data or entities across different systems by finding the inherent and common relationship
- It helps reduce cost and standardize agreed data definition vis-a-vis integrating business systems
As organizations continue to receive information, they can leverage the semantic data model to consistently provide meaning to incoming data and organize it in a way where it would be easy to identify its definition and arrange it according to its context resulting in strategic decision-making and streamlined business process.
This is one of the steps in the semantic data model approach. There are additional measures in terms of processes, people and technology that an organization would need to take in order to untangle the data hairball.
If you would like to know more, reach out to One Connect Solutions.