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Our team of specialists wanted to share some articles on technologies, services, trends and news of our industry in the era of digital transformation.

Data is present on the everyday of organizations like yours and data analysis skills are key for business success. Data helps us learn from the past and make better business decisions in the future. The advancement of data science in the business worls makes us understand the importance of a correct management of the life cycle of your company’s data.

We are now in the age of the data revolution. Increasingly, organizations have greater volumes of data that allow them to optimize their decisions. Big Data, as one of the foundations of many companies, represents a challenge but also an opportunity for organizations.

  • The opportunity lies in being able to satisfy consumer needs in a more effective way, understanding their wishes but also optimizing operations and reducing associated costs.
  • On the other hand, the challenge is related to the necessary infrastructure for this type of processes, as well as being able to count on trained personnel to carry them out.

It is therefore essential that companies have collaborators who are capable of analyzing, managing, reporting, and adding value to the data. The digital economy, digital transformation and globalization accelerate this process rapidly.

Professionals in the world of data science, business intelligence and data analytics generally have high levels of education and training. A very solid educational background is generally necessary to develop the depth of knowledge required to be a data or business analyst. The reality is that most of the professionals in this field are in constant training. Data analysis skills are key for success.

 

What Are the Data Analysis Skills You Need?

We cannot give a single answer to this question. Depending on the profile of the professional and the tasks demanded by the position, data and business analysts will need to have different types of skills. We have developed a list of what we think are the most important skills to consider. This list is not necesarilly comprehensive, and it is not a requirement to be an expert in all these areas to be able to develop in the world of data science and business analytics. However, we have developed this list based on the work we have done for our clients. Let’s explore it!

 

Spreadsheets like Excel and Google Sheets. They allow handling mainly small volumes of data, focusing on the use of descriptive statistics, pivot tables, formulas, and simple visualizations. It is an interesting tool for developing a BI profile, but it could be somewhat limited for more comprehensive Big Data processes.

Visualization. The results of the data analysis are finally presented to other teams and to other people and users. In this sense, visualization skills are key for any profile. We need to make sure that we are choosing the correct type of graph for the data we are visualizing and that the visualization and narrative is done in a clear and easy-to-understand way. Some tools that business analysts use are Tableau, Power BI, and Google Data Studio. However, companies focused on data and information often develop ad hoc and tailored dashboards and monitoring platforms, adapted 100% to the specific needs of each project. You can find out about the work we performed for Aeropuertos Argentinos, where we developed a platform for surveys, automatic data analysis and reporting of results.

data analysis skills: dashboard

Dashboard example by Power BI

Statistics. Statistical skills are key for any data analyst. From basic descriptive statistics, to inferential statistical analysis and more advanced models of Machine Learning (e.g. Artificial Neural Networks) can help your organization to enhance its data strategy.

 

SQL – Structured Query Language. It is a programming language that can help you perform operations such as adding, removing, and extracting data from a database. It can also help you perform analytical functions and transform database structures. Database managers must be familiar with databases and languages ​​for their administration, as well as with environments that allow the management of databases (some widely used environments are: Oracle, SQL Server, MySQL, MongoDB).

It is important that you be able to master SQL if you want to be a data scientist. SQL is specifically designed to help you access, communicate, and work with data. It contains concise commands that can be useful to save time.

 

Programming languages. Mastering certain programming languages can make data analysis much more flexible. The languages we would like to highlight are R and Python.

  • R is designed specifically for the statistical needs of data science and data analytics. You can use R to solve a wide variety of problems, but most analysts use R for statistical work.
  • Python is one of the most popular programming languages, along with other highly acclaimed languages such as Java, Perl, or C/C ++. Python is a great programming language for scientists and data analysts. Due to its versatility, you can use Python in almost every step of your business operations.

data analysis skills: programming

As you can see, you need various knowledge to develop in the world of data science, business intelligence and data analytics. As we have mentioned, your organization may need a particular profile that requires different knowledge than those presented above. In order to adapt to the needs of each project, companies like Huenei offer you outsourcing solutions for specific software developments.