From raw data to data with value

March 18, 2022 · 3 min read


Technological milestones within their historical contexts, such as the telegraph, the telephone, radio, television or artificial satellites, marked changes in our habits and transitions in social interactions. Of course, the Internet was not going to be an exception, and going from the first web pages, and more recently, as a consequence of the COVID-19 pandemic, environments for virtual meetings and the adoption of teleworking, such as the new paradigm of our corporate culture at APSL: remote first.

Digitization and its expansion has transformed us into a 'glocal' (global + local) society, since in practical terms we can communicate locally and carry out commercial transactions at a global level. In addition, the use of the Internet through web pages or mobile applications has made our daily tasks easier, for example being able to access our bank account and make transactions, Obviously this territory is not exempt from risks, which is why it is important to adopt and implement good cybersecurity practices).

A brief overview

According to DATAREPORTAL, it was estimated that by January 2022 there would be 4.95 billion Internet users and the number is growing every second. This figure represents 62.5% of the world population; Additionally, the number of users in the various existing social networks is estimated at about 4,620 million (58.4% of the world population). Have you ever wondered what happens on the Internet every minute? There are 3.8 million searches done on Google, people create about 380 websites, about 400 new users create an account on Facebook. Additionally, people send 41.6 million messages on Facebook Messenger and WhatsApp; 87,500 tweets are generated on Twitter, and over 100 hours of new video material is uploaded to YouTube.

Added to the sample of figures offered, the online activity of the commercial transactions of purchase and sale; financial services, communications, education, public administration, among other areas. Take into consideration also the impact of the COVID-19 pandemic which has accelerated the implementation and development of digital solutions.

Internet users spend an average of 4 hours and 25 minutes a day, while regular users of social networks spend 2 hours and 16 minutes a day. About 20% of the world's population uses Facebook, which is a staggering 1.42 billion active users worldwide. When it comes to browsers, Google Chrome has a substantial advantage over the competition.

It is not surprising that English is the first language used on the web (Internet World Stats), representing 25.2% of Internet users worldwide. Of the estimated 97,025,201 people who speak German, 95.1% are Internet users. And the number of Japanese-speaking Internet users has grown by a staggering 152% in the last 19 years. In Spain, according to BOE No. 51, of March 1, 2022, the use of the Internet frequently by people over 16 years of age it is over 83.1%, while for people between 65 and 74 years of age it is over 60 %, according to data from the INE.

What does this all mean? A huge flow of data and metadata (data from data) is generated. By way of analogy, data alone (raw data) is raw material; to which, duly processed (ordered, processed and interpreted), become a valuable resource of added value, producing useful and valuable information for better decision making. This is what the people of the APSL Department of Data Science and Artificial Intelligence do for a living.

Corporate Information Factory: un nuevo paradigma para dar valor a tus datos

The Corporate Information Factory (CIF) paradigm is a model created by William H. Inmon, and is based on the creation of a centralized repository that brings together, at the highest level of detail, corporate data as a consolidated source of information, to guarantee their future use.

From this paradigm, we can see that the knowledge and experience provided by data science will vary depending on the objective (or objectives) of the company and the sector in which it operates. Take, for example, sales and marketing departments, which can mine customer data to create individual marketing campaigns. Banking institutions generate data to improve fraud detection. streaming and music services to determine the interest of users and use that data to know what TV shows or movies to produce. Data-driven algorithms are also used to make personalized recommendations based on a user's viewing history. Shipping companies like DHL and FedEx are already using Data Science to find the best routes and optimize delivery times, as well as the best modes of transportation for their shipments.

In future articles of this blog, we will continue expanding information on this fascinating paradigm in which various disciplines converge.

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