Think for a second about employees in diamond mines. Their job can often seem like trying to find a needle in a haystack. But once they find what they’re looking for, the feeling of accomplishment is overwhelming.

The situation is similar with data mining. Granted, you’re not on the hunt for diamonds (although that wouldn’t be so bad). The concept’s name may suggest otherwise, but data mining isn’t about extracting data. What you’re mining are patterns; you analyze datasets and try to see whether there’s a trend.

Data mining doesn’t involve you reading thousands of pages. This process is automatic (or at least semi-automatic). The patterns discovered with data mining are often seen as input data, meaning it’s used for further analysis and research. Data mining has become a vital part of machine learning and artificial intelligence as a whole. If you think this is too abstract and complex, you should know that data mining has found its purpose for every company. Investigating trends, prices, sales, and customer behavior is important for any business that sells products or services.

In this article, we’ll cover different data mining techniques and explain the entire process in more detail.

Data Mining Techniques

Here are the most popular data mining techniques.

Classification

As you can assume, this technique classifies something (datasets). Through classification, you can organize vast datasets into clear categories and turn them into classifiers (models) for further analysis.

Clustering

In this case, data is divided into clusters according to a certain criterion. Each cluster should contain similar data points that differ from data points in other clusters.

If we look at clustering from the perspective of artificial intelligence, we say it’s an unsupervised algorithm. This means that human involvement isn’t necessary for the algorithm to discover common features and group data points according to them.

Association Rule Learning

This technique discovers interesting connections and associations in large datasets. It’s pretty common in sales, where companies use it to explore customers’ behaviors and relationships between different products.

Regression

This technique is based on the principle that the past can help you understand the future. It explores patterns in past data to make assumptions about the future and make new observations.

Anomaly Detection

This is pretty self-explanatory. Here, datasets are analyzed to identify “ugly ducklings,” i.e., unusual patterns or patterns that deviate from the standard.

Sequential Pattern Mining

With this technique, you’re also on the hunt for patterns. The “sequential” indicates that you’re analyzing data where the values are in a sequence.

Text Mining

Text mining involves analyzing unstructured text, turning it into a structured format, and checking for patterns.

Sentiment Analysis

This data mining technique is also called opinion mining, and it’s very different from the methods discussed above. This complex technique involves natural language processing, linguistics, and speech analysis and wants to discover the emotional tone in a text.

Data Mining Process

Regardless of the technique you’re using, the data process consists of several stages that ensure accuracy, efficiency, and reliability.

Data Collection

As mentioned, data mining isn’t actually about identifying data but about exploring patterns within the data. To do that, you obviously need a dataset you want to analyze. The data needs to be relevant, otherwise you won’t get accurate results.

Data Preprocessing

Whether you’re analyzing a small or large dataset, the data within it could be in different formats or have inconsistencies or errors. If you want to analyze it properly, you need to ensure the data is uniform and organized, meaning you need to preprocess it.

This stage involves several processes:

  • Data cleaning
  • Data transformation
  • Data reduction

Once you complete them, your data will be prepared for analysis.

Data Analysis

You’ve come to the “main” part of the data mining process, which consists of two elements:

  • Model building
  • Model evaluation

Model building represents determining the most efficient ways to analyze the data and identify patterns. Think of it this way: you’re asking questions, and the model should be able to provide the correct answers.

The next step is model evaluation, where you’ll step back and think about the model. Is it the right fit for your data, and does it meet your criteria?

Interpretation and Visualization

The journey doesn’t end after the analysis. Now it’s time to review the results and come to relevant conclusions. You’ll also need to present these conclusions in the best way possible, especially if you conducted the analysis for someone else. You want to ensure that the end-user understands what was done and what was discovered in the process.

Deployment and Integration

You’ve conducted the analysis, interpreted the results, and now you understand what needs to be changed. You’ll use the knowledge you’ve gained to elicit changes.

For example, you’ve analyzed your customers’ behaviors to understand why the sales of a specific product dropped. The results showed that people under the age of 30 don’t buy it as often as they used to. Now, you face two choices: You can either advertise the product and focus on the particular age group or attract even more people over the age of 30 if that makes more sense.

Applications of Data Mining

The concept of data mining may sound too abstract. However, it’s all around us. The process has proven invaluable in many spheres, from sales to healthcare and finance.

Here are the most common applications of data mining.

Customer Relationship Management

Your customers are the most important part of your business. After all, if it weren’t for them, your company wouldn’t have anyone to sell the products/services to. Yes, the quality of your products is one way to attract and keep your customers. But quality won’t be enough if you don’t value your customers.

Whether they’re buying a product for the first or the 100th time, your customers want to know you want to keep them. Some ways to do so are discounts, sales, and loyalty programs. Coming up with the best strategy can be challenging to say the least, especially if you have many customers belonging to different age groups, gender, and spending habits. With data mining, you can group your customers according to specific criteria and offer them deals that suit them perfectly.

Fraud Detection

In this case, you analyze data not to find patterns but to find something that stands out. This is what banks do to ensure no unwanted guests are accessing your account. But you can also see this fraud detection in the business world. Many companies use it to identify and remove fake accounts.

Market Basket Analysis

With data mining, you can get answers to an important question: “Which items are often bought together?” If this is on your mind, data mining can help. You can perform the association technique to discover the patterns (for example, milk and cereal) and use this valuable intel to offer your customers top-notch recommendations.

Healthcare and Medical Research

The healthcare industry has benefited immensely from data mining. The process is used to improve decision-making, generate conclusions, and check whether a treatment is working. Thanks to data mining, diagnoses have become more precise, and patients get more quality services.

As medical research and drug testing are large parts of moving the entire industry forward, data mining found its role here, too. It’s used to keep track of and reduce the risk of side effects of different medications and assist in administration.

Social Media Analysis

This is definitely one of the most lucrative applications. Social media platforms rely on it to pick up more information about their users to offer them relevant content. Thanks to this, people who use the same network will often see completely different posts. Let’s say you love dogs and often watch videos about them. The social network you’re on will recognize this and offer you even more dog videos. If you’re a cat person and avoid dog videos at all costs, the algorithm will “understand” this and offer you more videos starring cats.

Finance and Banking

Data mining analyzes markets to discover hidden patterns and make accurate predictions. The process is also used to check a company’s health and see what can be improved.

In banking, data mining is used to detect unusual transactions and prevent unauthorized access and theft. It can analyze clients and determine whether they’re suitable for loans (whether they can pay them back).

Challenges and Ethical Considerations of Data Mining

While it has many benefits, data mining faces different challenges:

  • Privacy concerns – During the data mining process, sensitive and private information about users can come to light, thus jeopardizing their privacy.
  • Data security – The world’s hungry for knowledge, and more and more data is getting collected and analyzed. There’s always a risk of data breaches that could affect millions of people worldwide.
  • Bias and discrimination – Like humans, algorithms can be biased, but only if the sample data leads them toward such behavior. You can prevent this with precise data collection and preprocessing.
  • Legal and regulatory compliance – Data mining needs to be conducted according to the letter of the law. If that’s not the case, the users’ privacy and your company’s reputation are at stake.

Track Trends With Data Mining

If you feel lost and have no idea what your next step should be, data mining can be your life support. With it, you can make informed decisions that will drive your company forward.

Considering its benefits, data mining will continue to be an invaluable tool in many niches.

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Il Sole 24 Ore: 100 thousand IT professionals missing
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
May 14, 2024 6 min read

Written on April 24th 2024

Source here: Il Sole 24 Ore (full article in Italian)


Open Institute of Technology: 100 thousand IT professionals missing

Eurostat data processed and disseminated by OPIT. Stem disciplines: the share of graduates in Italy between the ages of 20 and 29 is 18.3%, compared to the European 21.9%

Today, only 29% of young Italians between 25 and 34 have a degree. Not only that: compared to other European countries, the comparison is unequal given that the average in the Old Continent is 46%, bringing Italy to the penultimate place in this ranking, ahead only of Romania. The gap is evident even if the comparison is limited to STEM disciplines (science, technology, engineering and mathematics) where the share of graduates in Italy between the ages of 20 and 29 is 18.3%, compared to the European 21.9%, with peaks of virtuosity which in the case of France that reaches 29.2%. Added to this is the continuing problem of the mismatch between job supply and demand, so much so that 62.8% of companies struggle to find professionals in the technological and IT fields.

The data

The Eurostat data was processed and disseminated by OPIT – Open Institute of Technology. an academic institution accredited at European level, active in the university level education market with online Bachelor’s and Master’s degrees in the technological and digital fields. We are therefore witnessing a phenomenon with worrying implications on the future of the job market in Italy and on the potential loss of competitiveness of our companies at a global level, especially if inserted in a context in which the macroeconomic scenario in the coming years will undergo a profound discontinuity linked to the arrival of “exponential” technologies such as Artificial Intelligence and robotics, but also to the growing threats related to cybersecurity.

Requirements and updates

According to European House Ambrosetti, over 2,000,000 professionals will have to update their skills in the Digital and IT area by 2026, also to take advantage of the current 100,000 vacant IT positions, as estimated by Frank Recruitment Group. But not only that: the Italian context, which is unfavorable for providing the job market with graduates and skills, also has its roots in the chronic birth rate that characterizes our country: according to ISTAT data, in recent years the number of newborns has fallen by 28%, bringing Italy’s birth rate to 1.24, among the lowest in Europe, where the average is 1.46.

Profumo: “Structural deficiency”

“The chronic problem of the absence of IT professionals is structural and of a dual nature: on one hand the number of newborns – therefore, potential “professionals of the future” – is constantly decreasing; on the other hand, the percentage of young people who acquires degrees are firmly among the lowest in Europe”, declared Francesco Profumo, former Minister of Education and rector of OPIT – Open Institute of Technology. “The reasons are varied: from the cost of education (especially if undertaken off-site), to a university offering that is poorly aligned with changes in society, to a lack of awareness and orientation towards STEM subjects, which guarantee the highest employment rates. Change necessarily involves strong investments in the university system (and, in general, in the education system) at the level of the country, starting from the awareness that a functioning education system is the main driver of growth and development in the medium to long term. It is a debated and discussed topic on which, however, a clear and ambitious position is never taken.”

Stagnant context and educational offer

In this stagnant context, the educational offer that comes from online universities increasingly meets the needs of flexibility, quality and cost of recently graduated students, university students looking for specialization and workers interested in updating themselves with innovative skills. According to data from the Ministry of University and Research, enrollments in accredited online universities in Italy have grown by over 141 thousand units in ten years (since 2011), equal to 293.9%. Added to these are the academic institutions accredited at European level, such as OPIT, whose educational offering is overall capable of opening the doors to hundreds of thousands of students, with affordable costs and extremely innovative and updated degree paths.

Analyzing the figures

An analysis of Eurostat statistics relating to the year 2021 highlights that 27% of Europeans aged between 16 and 74 have attended an entirely digital course. The highest share is recorded in Ireland (46%), Finland and Sweden (45%) and the Netherlands (44%). The lowest in Romania (10%), Bulgaria (12%) and Croatia (18%). Italy is at 20%. “With OPIT” – adds Riccardo Ocleppo, founder and director – “we have created a new model of online academic institution, oriented towards new technologies, with innovative programs, a strong practical focus, and an international approach, with professors and students from 38 countries around the world, and teaching in English. We intend to train Italian students not only on current and updated skills, but to prepare them for an increasingly dynamic and global job market. Our young people must be able to face the challenges of the future like those who study at Stanford or Oxford: with solid skills, but also with relational and attitudinal skills that lead them to create global companies and startups or work in multinationals like their international colleagues. The increasing online teaching offer, if well structured and with quality, represents an incredible form of democratization of education, making it accessible at low costs and with methods that adapt to the flexibility needs of many working students.”

Point of reference

With two degrees already starting in September 2023 – a three-year degree (BSc) in Modern Computer Science and a specialization (MSc) in Applied Data Science & AI – and 4 starting in September 2024: a three-year degree (BSc) in Digital Business, and the specializations (MSc) in Enterprise Cybersecurity, Applied Digital Business and Responsible Artificial Intelligence (AI), OPIT is an academic institution of reference for those who intend to respond to the demands of a job market increasingly oriented towards the field of artificial intelligence. Added to this are a high-profile international teaching staff and an exclusively online educational offer focused on the technological and digital fields.

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Times of India: The 600,000 IT job shortage in India and how to solve it
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
May 2, 2024 3 min read

Written on April 25th 2024

Source here: Times of India 


The job market has never been a straightforward path. Ask anyone who has ever looked for a job, certainly within the last decade, and they can tell you as much. But with the rapid development of AI and machine learning, concerns are growing for people about their career options, with a report from Randstad finding that 7 in 10 people in India are concerned about their job being eliminated by AI.

 Employers have their own share of concerns. According to The World Economic Forum, 97 million new AI-related jobs will be created by 2025 and the share of jobs requiring AI skills will increase by 58%. The IT industry in India is experiencing a tremendous surge in demand for skilled professionals on disruptive technologies like artificial intelligence, machine learning, blockchain, cybersecurity and, according to Nasscom, this is leading to a shortage of 600,000 profiles.

 So how do we fill those gaps? Can we democratize access to top-tier higher education in technology?

These are the questions that Riccardo Ocleppo, the engineer who founded a hugely successful ed-tech platform connecting international students with global Universities, Docsity, asked himself for years. Until he took action and launched the Open Institute of Technology (OPIT), together with the Former Minister of Education of Italy, Prof. Francesco Profumo, to help people take control of their future careers.

OPIT offers BSc and MSc degrees in Computer Science, AI, Data Science, Cybersecurity, and Digital Business, attracting students from over 38 countries worldwide. Through innovative learning experiences and affordable tuition fees starting at €4,050 per year, OPIT empowers students to pursue their educational goals without the financial and personal burden of relocating.

The curriculum, delivered through a mix of live and pre-recorded lectures, equips students with the latest technology skills, as well as business and strategic acumen necessary for careers in their chosen fields. Moreover, OPIT’s EU-accredited degrees enable graduates to pursue employment opportunities in Europe, with recognition by WES facilitating transferability to the US and Canada.

OPIT’s commitment to student success extends beyond academics, with a full-fledged career services department led by Mike McCulloch. Remote students benefit from OPIT’s “digital campus,” fostering connections through vibrant discussion forums, online events, and networking opportunities with leading experts and professors.

Faculty at OPIT, hailing from prestigious institutions and industry giants like Amazon and Microsoft, bring a wealth of academic and practical experience to the table. With a hands-on, practical teaching approach, OPIT prepares students for the dynamic challenges of the modern job market.

In conclusion, OPIT stands as a beacon of hope for individuals seeking to future-proof their careers in technology. By democratizing access to high-quality education and fostering a global learning community, OPIT empowers students to seize control of their futures and thrive in the ever-evolving tech landscape.

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