Top 5 In-Demand Data Analyst Skills to Get Hired in the UK

A skilled data analyst job can imply a long-term, stable profession in a high-paying industry. Indeed, once you have the right data analyst skills, you’re not limited to success.

Data analysis is a highly growing sector. And skilled analysts are in higher demand across different fields. From the look of things, the need for experienced analysts will keep growing. This is anticipated in the UK and also in global corporations.

We say this because data analytics career prospects have been growing by the day. For instance, are you aware that in 2020, the data generated daily amounted to 2.5 quintillion bytes? 

Such data explosion creates the need for organizations to use the data. Thus, skilled data analysts are in demand to continually meet this high trend. Even better, giant corporations like Google and Microsoft initiated global skills initiatives. 

They’re trying to make more people access the needed data skills. Why? They do this as a move to make people a part of Big Data. Such initiatives give more people the digital skills that are in demand in today’s data analytical world.

That’s why many job seekers don’t want to be left behind. They stay connected to Onlydatajobs. Once registered, you get the latest data insights, analytics roles, and business intelligence in the UK. You receive the notifications straight into your inbox. Thus, you can never miss out on important posts. This may include relevant job postings by employers.

Our article below looks at the in-demand data analyst skills to get hired in the UK. Let’s delve in.

1. Structured Query Language (SQL)

Learning SQL allows you to read, update, and organize data stored in relational databases. You can also modify, manipulate and retrieve data structures. It will enable you to generate valuable insights. As a result, you can make informed decisions for a company.

Almost every data analyst needs to use SQL to access data from the company’s database. It’s no surprise that this is the standard language for communicating with databases.

It’s almost becoming the primary skill for data analysts to secure a job. In fact, most interviews for data analysts may include some practical screening for SQL. Fortunately, SQL is one of the quick-to-grasp skills.

2. Data Visualization

This skill makes identifying trends and patterns in large data sets easier. Using data insights to tell a story is crucial. It forms a part of the data analysis process. This helps you to get your point across and keep your audience engaged. 

Anytime your data findings can’t be easily identified, it becomes difficult for you to get through to the targeted audience. This means that data visualization can have a make-up or break-up effect. This is when it comes to the impact your data has. 

Data analysts need to use visually appealing, high-quality graphs and charts. This helps to present findings clearly and concisely. 

For example, telling a story using your data insights can help make better business decisions. This is where data visualization comes in. 

So, as a data analyst, it helps to use charts, maps, graphs, and other visual data representations. They make it possible to present your findings in a friendly and quick-to-understand way. 

Today, data visualization is vital in almost every career. For example:

• Teachers can use it to display students’ test results.
• Computer scientists can use it to explore advancements in artificial intelligence (AI)
• Executives need data visualization to share information with their stakeholders. It helps them understand the presented data better. 
• It plays a significant role in big data projects. There were times when businesses had massive data collections in the early years of the big data trend. This was when they needed a quick way to overview their data. In this case, visualization tools were a perfect fit.

3. Econometrics

Are you a data analyst looking for a job in the financial sector? It helps to know that understanding econometrics is a significant skill. This is crucial, especially at hedge funds and investment banks.

Data analysts use econometrics to apply statistical data models to economics. It helps to forecast future trends based on historical data. 

Econometrics enable economists to translate economic theories into measurable standards. This skill is crucial in establishing trends between datasets. From these trends, economists can predict future financial trends. They can also get a specific pattern or result from scattered data.

Financial econometrics is also necessary for risk management. Most employers are looking for data analysts with this skill; why? Because such data analysts can often predict how regular ‘bad’ investment outcomes are projected to occur in the future years, months, weeks, or days.

Other applications of econometrics in the financial field include:

• Predict the price to earnings ratio
• Estimate and forecast volatilities 
• Aids in developing trading strategies

4. Machine Learning (ML)

ML forms a part of artificial intelligence (AI). It’s now one of the most significant developments in data science. This skill helps in building algorithms formulated to find patterns in big data. It helps to improve data’s accuracy over time.

With machine learning, the whole data analysis process is automated. As a result, it provides faster, deeper, and more detailed insight. Most importantly, the algorithms work with no human bias or time limitation. 

The ability to compute data combinations enables the holistic understanding of data. The more data a machine learning algorithm processes, the more intelligent it becomes. This allows for even more accurate predictions by data analysts. 

Let’s say that you’re asked to establish changes in a company’s sales figures. You can use machine learning skills. It can detect the difference between a 300 USD fluctuation and a 300,000 USD increase. In return, it will only report the latter result. This is because that’s the information that impacts the company most.

So, machine learning tests out hypotheses to answer critical business questions. And it can test all the assumptions in a short period. This is where things work in seconds instead of weeks. 

The machine then reveals a data story that’s accurate and comprehensive. The resultant data is also appropriate to the one asking questions.

Basically, it isn’t a must that data analysts master machine learning. But, when you develop your machine learning skills, you’re at a competitive edge. And, it could give you an added advantage. For example, employers may consider you more to pursue a data scientist career.

5. Critical Thinking

Critical thinking as a skill is crucial to data analysts. This is because sometimes, you may have to think for yourself. And, you won’t have to rely on the information that already exists.

As a data analyst, you need to use data to find answers to your questions. This means that you must figure out initially what to ask. Often, it can be a bit tricky. So, employers need data analysts that can think beyond the scope. 

It’s the data analyst’s role to reveal meanings and make connections. They should do this from information that may seem unclear. For some people, critical thinking ability is usually inborn. But, you can also improve your critical thinking skills.

For instance, asking yourself basic questions about the issue at hand can be impactful. It helps you to stay alert when finding a particular solution. So, you won’t get overwhelmed with an explanation that appears more complex than it should be. 

Key Takeaways

Many companies today know the importance of data-driven business strategies. That’s why there’s high demand for talented data analysts. Companies want such individuals to provide insight into the constant channels of collected data. 

As the world continues to transform into a digital playfield, the demand for skilled analysts will only grow. As a data analytic professional, you will always be at the center of decision-making in your company. Thus, it’s significant to know the skills you need to scale the heights of data analytics. This is what will help you advance your career.

Furthermore, continuous improvement of your data analytics knowledge implies more growth and opportunities. Such is true even as the world’s technology advances faster.

A helpful website where women can get assistance on artificial intelligence can be found at https://www.deepbrain.io/