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Humanized Big Data

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Humanized Big Data is a technology that collects and analyzes the type of data created by Big Data processes. The strong point of these processes, the quantitative foundation, is at the same time their greatest weakness. It is difficult to derive concrete guidelines for action or actionable meanings from an analysis of current solutions, if the aim is to make business decisions based on the data collected. The idea of humanizing data may seem counterintuitive at first, but since data starts with people, at some point people need to be involved in data processing as well.

Instead of relying on specialized programming and statistical skills of experts, data can be humanized by adding the right context and providing simple tools for building analytical applications. Thus, in contemporary companies, the functions generally encountered in IT departments can be transferred to analysts. Humanized Big Data turns data into easily accessible and highly relevant information. It makes analyzes based on large amounts of data to be performed effortlessly and naturally. The main purpose of humanizing data is to focus on the element of greatest importance to business and industry, namely the customer or potential customer. This goal translates into creating a process of contextualizing digitally stored information and creating “stories” of information sources. By humanizing data, we can develop concrete action plans and extract adjuvant information in decision making.

The data humanization process is dependent on::
• Facilitating access to Big Data for business analysts in order to develop the strategy on which the decision-making process of the organisation is based
• Data processing to form the “story” that describes the source of the information

The following are useful principles that can be used in the process of humanizing data:

1. Correlation of patterns: the data collected show patterns that, once identified and correlated with the source of information, help to make predictions;

2. Ensuring accessibility: interpretations must be made available to the entire team responsible for the decision-making process;

3. Empathy with customers: while using a large volume of data for customer analysis, the process is humanized by the ability of analysts to empathetically understand the information held;

4. Focus on business outcome: the use of data must be solution-oriented and action-oriented for maximum business impact, aligning with strategic business direction and revenue-generating opportunities.

With the help of Big Data processes, companies can develop new ways to meet people’s needs. The goal of humanizing these processes is to add analysts’ human grade for improved results and streamline analytical workflows. Practical applications of Big Data and Humanized Big Data include:

• Determining consumers’ shopping habits: Past and recorded customer behavior allows companies to anticipate what customers will want, thus responding more efficiently to requests and encouraging repeat purchases;
• Personalized marketing: In the online environment, advertising and content that reach users targeted as potential customers by a company are personalized through data processing;
• Monitoring health conditions through smart accessories: Prompt and improved diagnostic reactions can be ensured with the help of biomedical data recorded by using smart accessories whose sensors constantly monitor the condition of patients;
• Designing real-time routes for autonomous vehicles: Data accessibility can also be a direct advantage for consumers when tools such as sensors and the car’s computer help determine optimal routes and avoid delays or even road accidents;
• Predictive inventory ordering: Logistics departments of companies can use their data and interpretations to establish early the materials and products needed to manage customer requests in a given period of time;
• Real-time data monitoring and cybersecurity protocols: Information from Big Data analytics tools can be used to detect cybersecurity threats, including malware / ransomware attacks, compromised or weak devices in the face of cyber attacks, and software of the “Trojan horse” type.

 

About the author:

Octavian C

Octavian Crivăț

Junior Marketing Consultant

Octavian is pursuing a BBA (Bachelor of Business Administration) program at the Academy of Economic Studies in Bucharest. At Idea Perpetua, Octavian implements projects in Entrepreneurship Consulting, Consulting in Online Marketing and Consulting in Branding. At the same time, Octavian is oriented towards reaching the clients’ objectives related to the increase of the turnover, the increase of the client portfolio, the development of the relationship with the stakeholders and the increase of the brand awareness in the online environment.

 

Published: 2020-05-14 21:20:31

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