Article | April 29, 2021
We live in a world convulsed by new technologies and we are witnessing how more and more processes are automated in order to be executed with the same skill or even with better results than if they were carried out by a human, all this in order to be more efficient and effective.
In this context the world of work is becoming increasingly competitive, because to remain employable we need to learn to manage or find a way to adapt our knowledge and skills to new technologies.
With the spread of e-learning platforms and the tutorials that we can find available on the internet, acquiring new knowledge is within everyone's reach. For this reason, it is necessary to differentiate ourselves in order to stand out from other professionals, who have the hard skills similar to ours and this is precisely where Soft Skills play a very important role.
What are Soft Skills?
Soft skills are actually a combination of individual social skills, communication skills, personality traits, attitudes, social intelligence and emotional intelligence. Which facilitate relationships with others, making us more effective when interacting with other people.
We could say that Soft Skills are the human interface that allow us to adapt to different working environments and industries. They are powerful tools for personal and professional growth.
Why are Soft Skills key in our professional growth?
Nowadays, standing out in the world of work is getting increasingly difficult, regardless of whether you are part of a corporation or work independently, due to the great competition within the labor market. That is why we must develop certain skills and attitudes that help us to function properly and successfully meet professional demands.
Soft Skills are the point of differentiation that allows us to be selected for a position. The reason is very simple, we could be applying for a position and competing with people that are equal or even more qualified than us at a technical level, but to achieve the collaborative objectives of the company, more is required than just the technical and rational part. Also the way of communicating, values, ethics, as well as personality traits are highly valued factors since they help to drive organizations through high-performance teams, guaranteeing the achievement of their objectives.
The background of the Soft Skills that we have trained throughout our lives make us unique, because it is unlikely that two people have the same combination of Soft Skills and been trained in a similar way, and that makes us more competitive against certain job opportunities where perhaps many will have the same Hard Skills, but where our Soft Skills will be the ones that will make us stand out to continue advancing in our professional career.
How to sharpen our Soft Skills?
To perform in any job we necessarily need to interact with other people, even if we work independently or remotely, so we must have the necessary skills that allow us to connect successfully with our teammates and stakeholders.
Starting from the fact that Soft Skills are human skills, we can say that we have them pre-installed and the way to start using them (installing them) is through the experiences we undergo every day.
Imagine being able to communicate assertively in your work environment and in your personal life. Master the use of tools installed in you to improve your interpersonal relationships within your work teams and reduce conflict. This would allow you to foster a healthy working environment and be able to lead any team in any environment in a strategic and effective way.
Think of Soft Skills as a set of Apps that are ready to be used (like a toolbox) and that according to the experiences that are presented in our personal and / or professional lives, we are going to choose to use these applications to achieve our goals. Every time we access one of these applications, we are giving it the opportunity to collect data that will allow it to personalize its insights according to our needs and to fine-tune its effectiveness each time we use it.
One of the best ways to train our Soft Skills is by leaving our comfort zone, because that will allow us to 'install' more and more Soft Skills.
Another way to refine our Soft Skills is by participating in activities that involve people we do not know and even better if we involve people from other cultures, because we will achieve a beneficial exchange of experiences and knowledge for both parties that will enrich and make the training of our Soft Skills even more valuable.
Some examples of activities that will enhance your Soft Skills:
• Participate in competitions (e.g. Hackathons)
• Found or be a lead of a community that shares your interests, and organizes small or large projects.
• Organize a study group aimed at carrying out a technical or business project in order to confront professionals from various fields or industries.
• Find resources and experts to help you. There are Soft Skills trainers who know useful techniques and tips to develop/sharpen your skills.
• Participate in volunteer activities. You will meet new people with whom to put your Soft Skills in action.
These activities will train/sharpen your leadership skills, teamwork, delegation, interpersonal communication, persuasion, etc. These are skills that we do not have as much facility to train while we are students or when we have just started working after finishing our studies, and that are required in the labor market to continue climbing in our professional career.
Why do Soft Skills matter in the Data Science universe?
A consequence of the use of Artificial Intelligence and Data Science is that many of the jobs that we know today will be automated and this is a matter of concern for many professionals who see their careers are in danger, but the good news is that in the future many new jobs the Soft Skills will be the main protagonists, this is what John Thompson explains us in his book "Building Analytics Teams"
In other words, it is precisely our human skills that will allow us to be more employable in the future, and they will be highly requested skills because according to what the experts envision which is, that the machines will not be able to match us in this field, and that is why training our Soft Skills becomes a priority because they will allow us to be the key players of the future.
On the other hand, Data Science is an interdisciplinary field where Soft Skills such as cooperation and communication are essential to achieve the goals set. Denis Rothman, author of the book "Transformers for Natural Language Processing" in an interview that I conducted, mentioned that The Human Quality is the most important thing for him when choosing the members of his work team.
These are some considerations to take into account to generate a culture of cooperation:
• People work harder and need less supervision, when they themselves control their work and have more freedom to choose how to do it. When they work as a team, they show greater motivation, their sense of pride increases and productivity reaches higher levels.
• Solid teams that seek quality and excellence correct themselves; that is, they identify problems and correct them very quickly. Thus, they gain work experience and increase their performance.
• Forming a solid and efficient work team requires patience. You need to give them time to see your results. They will have to establish procedures to complete tasks, handle administrative functions and work together efficiently, they will even have to adapt to their own decisions and accept their consequences.
• A manager or team leader must recognize the team building process without expecting immediate results. The group will have to go through a learning process and this will take longer in some groups than in others.
Another key component to achieving high levels of cooperation is fluid communication among team members and stakeholders. For instance defining the communication channels and the contact points in the different teams involved, guarantees the constant flow of communication during the life cycle of a Data Science project.
One of the most critical moments is the presentation of the results to the stakeholders. In some cases the results of a project are not taken into consideration not so much because the expected results are not achieved, but because the way in which these results are presented are not meaningful for the stakeholders, and this, in most cases, it is due to the existence of communication barriers that is a consequence of the use of a language (terminologies) used in the technical world but not in the business world.
After taking a tour of the world of Soft Skills, we can conclude by saying that Soft Skills are like superpowers that are waiting for the opportunity to be put into action, to make you a superhero or superheroine.
Keep climbing positions in your professional career depends on you, on how much you use these superpowers but above all on your skills to refine them and make them available to the work team of which you are part. Don't wait any longer and start discovering your potential, start training your Soft Skills!
If you want to know more about Soft Skills, I invite you to visit The Soft Skills Show
Article | April 29, 2021
Today when we look around, we see how technology has revolutionized our world. It has created amazing elements and resources, putting useful intelligence at our fingertips. With all of these revolutions, technology has also made our lives easier, faster, digital and fun. Perhaps at a point when we are talking about technology, Machine learning and artificial intelligence are increasingly popular buzzwords used in modern terms.Machine Learning has proven to be one of the game changer technological advancements of the past decade. In the increasingly competitive corporate world, Machine learning is enabling companies to fast-track digital transformation and move into an age of automation. Some might even argue that AI/ML is required to stay relevant in some verticals, such as digital payments and fraud detection in banking or product recommendations.To understand what machine learning is, it is important to know the concepts of artificial intelligence (AI). It is defined as a program that exhibits cognitive ability similar to that of a human being. Making computers think like humans and solve problems the way we do is one of the main tenets of artificial intelligence.
THEORY AND STRATEGIES
Article | April 29, 2021
Since the internet became popular, the way we purchase things has evolved from a simple process to a more complicated process. Unlike traditional shopping, it is not possible to experience the products first-hand when purchasing online. Not only this, but there are more options or variants in a single product than ever before, which makes it more challenging to decide.
To not make a bad investment, the consumer has to rely heavily on the customer reviews posted by people who are using the product. However, sorting through relevant reviews at multiple eCommerce platforms of different products and then comparing them to choose can work too much. To provide a solution to this problem, Amazon has come up with sentiment analysis using product review data. Amazon performs sentiment analysis on product review data with Artificial Intelligence technology to develop the best suitable products for the customer. This technology enables Amazon to create products that are most likely to be ideal for the customer.
A consumer wants to search for only relevant and useful reviews when deciding on a product. A rating system is an excellent way to determine the quality and efficiency of a product. However, it still cannot provide complete information about the product as ratings can be biased. Textual detailed reviews are necessary to improve the consumer experience and in helping them make informed choices. Consumer experience is a vital tool to understand the customer's behavior and increase sales.
Amazon has come up with a unique way to make things easier for their customers. They do not promote products that look similar to the other customer's search history. Instead, they recommend products that are similar to the product a user is searching for. This way, they guide the customer using the correlation between the products.
To understand this concept better, we must understand how Amazon's recommendation algorithm has upgraded with time.
The history of Amazon's recommendation algorithm
Before Amazon started a sentiment analysis of customer product reviews using machine learning, they used the same collaborative filtering to make recommendations. Collaborative filtering is the most used way to recommend products online. Earlier, people used user-based collaborative filtering, which was not suitable as there were many uncounted factors.
Researchers at Amazon came up with a better way to recommend products that depend on the correlation between products instead of similarities between customers. In user-based collaborative filtering, a customer would be shown recommendations based on people's purchase history with similar search history. In item-to-item collaborative filtering, people are shown recommendations of similar products to their recent purchase history. For example, if a person bought a mobile phone, he will be shown hints of that phone's accessories.
Amazon's Personalization team found that using purchase history at a product level can provide better recommendations. This way of filtering also offered a better computational advantage. User-based collaborative filtering requires analyzing several users that have similar shopping history. This process is time-consuming as there are several demographic factors to consider, such as location, gender, age, etc. Also, a customer's shopping history can change in a day. To keep the data relevant, you would have to update the index storing the shopping history daily.
However, item-to-item collaborative filtering is easy to maintain as only a tiny subset of the website's customers purchase a specific product. Computing a list of individuals who bought a particular item is much easier than analyzing all the site's customers for similar shopping history. However, there is a proper science between calculating the relatedness of a product. You cannot merely count the number of times a person bought two items together, as that would not make accurate recommendations.
Amazon research uses a relatedness metric to come up with recommendations. If a person purchased an item X, then the item Y will only be related to the person if purchasers of item X are more likely to buy item Y. If users who purchased the item X are more likely to purchase the item Y, then only it is considered to be an accurate recommendation.
In order to provide a good recommendation to a customer, you must show products that have a higher chance of being relevant. There are countless products on Amazon's marketplace, and the customer will not go through several of them to figure out the best one. Eventually, the customer will become frustrated with thousands of options and choose to try a different platform. So Amazon has to develop a unique and efficient way to recommend the products that work better than its competition.
User-based collaborative filtering was working fine until the competition increased. As the product listing has increased in the marketplace, you cannot merely rely on previous working algorithms. There are more filters and factors to consider than there were before. Item-to-item collaborative filtering is much more efficient as it automatically filters out products that are likely to be purchased. This limits the factors that require analysis to provide useful recommendations.
Amazon has grown into the biggest marketplace in the industry as customers trust and rely on its service. They frequently make changes to fit the recent trends and provide the best customer experience possible.
Article | April 29, 2021
Microsoft recently announced that it’s leveraging a new global strategic partnership with Telefonica to jointly develop “go-to-market plans for regions the company does business.Last year during Mobile World Congress 2019, Microsoft took the veil off its newfound relationship with the international telecommunications giant, Telefonica.Highlighted during this year’s announcement was Microsoft’s opening of a new datacenter region in Spain. Microsoft’s new data center comes at a time where the company looks to help expedite Spain’s digital transformation.