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Three trending technical skills for 2023
In today's world, technology is evolving so rapidly that the technical skills required for development are constantly changing and being updated.

Tewris understands how important it is to stay up to date with the latest technology trends in order to provide the best services to our clients.

If you're looking for a job in 2023, here are some great in-demand skills worth investing in.

Data Science

Data science is a hybrid field that requires integrating different areas of expertise into your work: data analysis, statistics, strategic planning, strong communications, and more, depending on the industry you are in.

The main goal of data science is to help your company interpret data trends and make recommendations to management on how to proceed.
While the role of a data scientist may be the same as that of a data analyst, their work differs in breadth. A data scientist spends more time than an analyst on visualization and statistical interpretation, and they must also be able to communicate their interpretations and strategic recommendations in a language that management can understand.

What's that?

Because there are a whole host of new ways to collect and organize data, we have access to more information than ever before. This means that data science is becoming increasingly in demand for all kinds of businesses.

Data scientists can analyze information in different ways and use it for different purposes. For example, you can interpret data to:

  • Understand what is happening at a given moment (descriptive analysis)

  • Find causes (diagnostic analysis)

  • Predict outcomes (predictive analysis)

  • Develop an effective plan of action (prescriptive analysis)

Here are some real-world examples of how data science is being used in various industries:

  • The company turned to data processing and analytics experts to help create an artificial intelligence program to assess a patient's risk of stroke from their medical records. The development also added a feature to the program to compare treatment plans to determine which treatment plan would have the best chance of success.

  • A shipping company uses data science to optimize mail delivery and transportation, specifically by determining which routes are the most cost-effective and least impacted by traffic.

  • A fitness company has developed a portable fitness device that tracks the user's heart rate, blood oxygen levels, and sleep quality. The device interprets this data to make recommendations for rest, increased activity, etc.

Given how important it is to understand market trends and company performance, data scientists are crucial to the success of their organizations. Consider becoming one if you want to help management interpret data and shape strategic plans!

Why it's useful

Cloud computing

Cloud computing offers resources such as file storage, servers, and software through internet "cloud" access, rather than storing these items locally in a physical location that you have access to. Many people are now relying on cloud computing and the demand continues to grow.

What's that?

The tools and services we use, such as data backup, email, software development, analytics, and virtual desktops, are powered by cloud computing.
The popularity of cloud computing is driven by unique benefits such as increased program flexibility, lower costs, and easier scalability. These factors make cloud computing very attractive to companies looking to reduce costs, adapt to changing needs, and scale in a sustainable manner-in other words, just about everyone.
Here are some examples of how cloud computing is being used in different industries:
  • Media streaming: when you listen to music on Spotify or watch a show on Netflix, you access content stored on the companies' cloud servers.
  • File storage and sharing: when you add files to your Google Drive or Dropbox folder, you upload them to your organization's cloud storage. Those files can then be accessed from another device, freeing up space on your local hard drive and making them instantly viewable when you (or someone you've shared access with) have an Internet connection.
  • Cybersecurity: providing advanced protection for your customers' digital assets and information.
  • Virtually any company that offers IaaS, PaaS, or SaaS infrastructure-as-a-service, platform-as-a-service, and software-as-a-service respectively — depends on cloud computing
As cloud services and products become more popular, the demand for cloud-savvy developers also continues to grow.

Why it's useful

Machine learning

Machine learning is a new professional field that combines computer science with artificial intelligence. A program created with machine learning essentially mimics the way humans learn by evolving and learning from their mistakes. With machine learning, you can develop a program that learns and becomes more and more accurate over time.

What's that?

Machine learning has spread to almost every major industry. It takes a lot of time and effort for programmers to create a piece of software that produces human-like results. Instead, machine learning allows programmers to create software that can reprogram itself as it receives data from their experience.
Machine learning depends on skills such as statistics and developing algorithms that help the program identify and respond to data (such as words or images). As with data science, the insights gained from machine learning can help organizations make decisions about their products and services, business strategies, and more.
Here are some examples of how machine learning is being used all around us:
  • A camera with artificial intelligence that detects which baked goods a customer has chosen and then calculates the total amount owed. This software is also adaptable to other environments, such as hospitals or various warehouses.
  • The predictive text as recommendations you see when replying to a friend's iMessage depends on machine learning to identify and recommend what you would normally say in similar contexts.
  • Streaming recommendations, suggesting movies you might like, depend on machine learning. In the case of Netflix, the company collects data about its customers, identifies patterns in the content that certain users like, and then makes recommendations to you based on the viewing history of people with similar tastes.
  • Unlike humans, translation programs don't learn the grammar and syntax of different languages. Instead, their answers are based on machine learning to analyze human translations and identify patterns. These patterns allow them to generate translations for the program's users.
  • Chatbots, commonly used to facilitate communication with customers on retail websites, rely on machine learning to improve their responses to customer questions.

Considering how often we have to deal with machine learning in our daily lives, it's a great skill to invest in!
If you want to find a new path in your tech career, consider developing your skills in data science, cloud computing, or machine learning. These are sure to be popular in the hiring market in 2023! As interest in these specialties grows, you'll be able to use your new skills to land a job that matches your professional goals! Remember: working in technology means constantly learning and improving your game.

Why it's useful

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