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The efficiency of data discovery depends on the user-friendliness of the UI and the features integrated into it to make it easier for users to look up the data they need. This article explores significant components of a user-friendly UI. In addition, it looks into specific measures that can be employed to increase the quality of search in the Open Data Discovery (ODD) Platform.
Recently, I came across a great panel hosted by data mesh learning incorporation with the open-source data podcast — to discuss the significance of data discovery in data mesh architecture and other important issues surrounding data mesh delivery.
The panel consisted of expert solution architects, including Shinji Kim, CEO Select Star, Sophie Watson, Principal Data Scientist Red Hat, Mark Grover, Founder of Stemma, and Shirshanka Das, CEO Acryl Data.
Data loss prevention tools are often employed to discover and monitor personal data in the cloud, but how effective and costly are they?
Personal data laws have been a bit of a spanner in the works and made everyone have a bit of a rethink about how they store client data that could be classified as “personal”. The thing is, which data can be classed as personal can change depending on whether it is paired with other data. This means that data that has the potential to be personal could be pretty much anywhere.
To build a seamless API integration, you need to map data appropriately.
In other words, to create seamless cooperation between apps, you need to map the appropriate custom and standard data fields and objects from the endpoints your customers will be integrating to with your app.
As your business grows and evolves, so does the number of data formats and applications you must also support. Whether an enterprise is trying to onboard a new trading partner or ensure that it meets all the requirements a customer has, data is coming from many different places.
The last thing your enterprise wants is to be difficult do business with. You need to be able to communicate efficiently with the members of your digital ecosystem in order to expand and take on more customers. That’s why efficiency in the data transformation process is so valuable to an organization: companies that can handle data formats of any size, shape, or form are the ones that are going to thrive in the age of the cloud.
