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Which technologies combine to make data a critical organizational asset

Which technologies combine to make data a critical organizational asset

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Which technologies combine to make data a critical organizational asset

(a) The practice of penetration testing and intelligence
(b) Machine Learning and Artificial Intelligence (AI)
(c) Speech Processing and Natural Language Processing (NLP)
(d) Electronic devices and the Internet of Things (IoT).

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The correct answer for the given question is Option (b) Machine Learning and Artificial Intelligence (AI)

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Which technologies combine to make data a critical organizational asset

Answer Explanation for Question: Which technologies combine to make data a critical organizational asset

Machine Learning (ML) and Artificial Intelligence (AI)

Machine Learning and Artificial Intelligence (AI) are the technologies that combine to make data a critical organizational asset. The terms Artificial Intelligence and Machine Learning are much discussed and also confusing these days. A subset of Artificial Intelligence is Machine Learning (ML).

In machine learning, one designs and applies algorithms that are able to learn from past experiences. It is possible to predict if or when a behavior will recur based on its past behavior. Therefore, there is no prediction if the behavior has never occurred before.

We can apply machine learning to solve tough problems such as credit card fraud detection, self-driving cars, and facial recognition.

A machine learning algorithm analyses large data sets on a constant basis, finding patterns in the data and allowing the machine to respond to situations that it hasn’t been explicitly programmed to handle. To produce reliable results, the machines learn from the past.

They predict rational outcomes using Computer Science and Statistics. With the abundance of available data and the rising cost of computing power, Artificial Intelligence (AI) techniques are increasingly being deployed in finance, including asset management, algorithmic trading, credit underwriting, or blockchain-based finance.

With machine learning (ML) models, predictability and performance can be improved by automatically learning through experience and data without any programming on the part of humans. 

Data is an Important Organizational Asset

Data is an Important Organizational Asset

We live in an increasingly data-driven world. In response, businesses are working diligently to collect information and use it, ensuring that they have an edge over their competitors. Since data is more valuable than ever before, businesses don’t see spreadsheets or databases as mere entries.

It should be treated as a critical organizational asset, one that must be managed and leveraged appropriately. If your company does not recognize the full power of its data, it will suffer. It could lead to an organization missing out on an opportunity, negatively impacting its bottom line.

Today’s data-driven world requires companies to recognize that all of these sources of information are valuable, even if they come from unconventional sources.

In order to gain insights from the information, they create mechanisms for collecting, capturing, and categorizing it. In addition, they are diligent in protecting the information. The information is kept out of the hands of ne’er-do-wells and is not damaged, either intentionally or by accident.

The management of data often requires both technical solutions and skilled professionals. Companies require different things based on the types and amount of data they collect, as well as what they hope to accomplish with it.

Lastly,

I hope after going through this post you might have clearly understood the Question: Which technologies combine to make data a critical organizational asset

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Smirti
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