In this era of data explosion, it is important to have a data-driven concept. Compared to making decisions based on intuition, having data to support decisions can significantly improve accuracy and reduce risk. In this situation, "data transformation" plays a key role in how to obtain valuable intelligence from the flood of data.
DIKW Pyramid
From the perspective of Knowledge Management, the DIKW pyramid tells us a model with four data stages: Data, Information, Knowledge, and Wisdom. We often talk about "How to get insights from data?" is the process of transforming data from the "Data stage" to the "Wisdom stage", and each stage of transformation has its own significance.
Data: A collection of raw data, generally referring to various types of facts, figures, or signals.
Information: The data is cleaned up, filtered, and organized to make it easier to measure, analyze, and visualize.
Knowledge: A specific way or framework that connects different pieces of information and lets us know "How" to make decisions.
Wisdom: Putting knowledge into action and accumulating it through constant reflection and feedback.
Throughout the process, each stage not only changes the form of data but more importantly, adds value, which is the essence of "data transformation". Through data transformation, raw data can be turned into valuable intelligence, which can then be linked into "knowledge" for decision makers to understand how to take action and become "wisdom"!
Data transformation is the process of transforming raw data into valuable intelligence.
Limited data, infinite value
Very rarely does a dataset meet 100% of the needs of those using the data, or rather, different datasets can be transformed into valuable information to meet different needs. Data transformation is the process of applying many changes to data to make it valuable to you.
Therefore, the data transformation process from data collection to the final production of intelligence will go through various procedures, such as basic data sorting, segmentation, filtering, culling, etc., to data format changes, visualization, and even the addition of AI empowerment for analysis, according to different needs, there will be different procedures applied to the data, this process is called "data pipeline".
Data Pipeline
As the name implies, the meaning of data pipeline comes from the pipeline, which simply means the process of collecting, transforming, and outputting. Take water filtration as an example, lakes, rivers, reservoirs, etc. collect water from various sources (collection) and then undergo various processes such as chlorination, flocculation, and filtration (conversion) to become the initial water resource (output). Then, according to different uses such as agriculture, industry, people's livelihood, drinking water, etc., the water will flow to different places for other procedures such as pH adjustment, water quality adjustment, etc., and more different pipes will be extended.
And data is like water, flowing in the system through the process of collection, transformation, and outputting. Through different pipeline designs, we can let the data flow to where we want it to go, do the corresponding procedures, and finally become the intelligence we want.
Image data transformation
Although images are unstructured data, their uses are endless, especially in the context of today's increasingly mature AI technology, which can significantly increase the value of images through data transformation, such as transforming 2D photos into 3D models, or adding geographic information to images for presentation on maps, or even adding computer vision technology to do image analysis with AI, etc. These are all scenarios for image data transformation.
However, the cost of image data transformation is too high, including the technical threshold, equipment costs, labor costs, and time costs, so this task can only be left to a small group of people, so that the value of the data is not fully utilized, reducing many possibilities.
DataXquad is a Pay-Per-Use online image data transformation service platform that can meet all procedures without use costs. We simplify the most complicated part of image data transformation so that more image data can be utilized and more industry chains can derive value from it.
Reference:
Comments