Every day, organizations obtain an immense volume of data that they use to develop their strategies.
However, to get valuable information from vast amounts of raw data, they need someone who understands data and knows how to convert it into insights. This professional is a data analyst.
A data analyst’s job is to analyze a lot of information about consumers, goods, and business results to produce metrics that can be used by decision-makers.
As a result of the input generated by the data analyst, businesses will identify which products are the best fit for the needs of different customer profiles, which promotional channels are the most targeted ones and the features that should be added so that the products are more personalized.
A survey by World Economic Forum discovered that 96% of enterprises have agreed or were expected to commit to recruiting new permanent hires with appropriate expertise to fill potential big data analytics positions by 2022.
This means that the data analyst profile will become one of the most demanded ones. Many people are already interested in making a career shift and diving into a data-oriented position. So, how can you become a data analyst? Keep reading.
What are the responsibilities of a data analyst?
Data analysts have to figure out what questions the company wants to answer and then see how they can be resolved by data. They must be familiar with the scientific aspects of data collection, analysis, and documentation. They should be prepared to spot relationships and trends.
If you want to become a data analyst, you first need to understand what this person does daily. The truth is, they have a lot of tasks, so good organizational skills are mandatory for this role.
Here are some of the most common responsibilities of a data analyst:
Analyzing the objectives. Before starting to work on anything, the data analyst has to understand the goals and objectives of the company. This way, their work will be more targeted and precise.
Preparing for data collection. To collect, process, manage and extract data from database systems such as MS SQL Server, Oracle DB, and MySQL, data analysts develop database queries and scripts. SQL is the most widely used querying language by data analysts, and it comes in a variety of types, including PostgreSQL, T-SQL, and PL/SQL (Procedural Language/SQL).
Data warehousing. Some data analysts are tasked with creating a data warehouse by linking databases from different sources and searching for and handling data with querying languages.
Data mining. Analysts mine data from a variety of sources and organize it to extract new information. They build data models as a result, increasing the system’s reliability.
Data cleaning. A data analyst’s main roles include data cleaning and manoeuvring. Initially, collected data is often sloppy and contains incomplete values. As a consequence, it’s important to clean the data gathered to optimize it for review.
Data analysis. By using a combination of coding and tools, data analysts have to examine the data to detect trends and patterns.
Extracting insights. The correlations that data analysts spot in data lead to insights that will help decision-makers improve company performance.
Reporting. Data analysts use data visualization tools to create overview reports. Managers will use reports to get informed about potential trends as well as areas that the sector will need to improve.
What are the skills a data analyst needs?
A good data analyst has a combination of technical and soft skills.
You should be able to work with at least one programming language as a data analyst. It is, though, safer if you are competent in several languages. R, Python, C++, Java, MATLAB, PHP, and other programming languages are commonly used in the field of data analysis.
- Data Management
You must be comfortable with languages like R, HIVE, SQL, and others as a data analyst. Data processing requires the development of queries to retrieve the requested information. You’ll need to produce reliable reports after you’ve processed the results. SAS, Oracle, Microsoft Power BI, Cognos, Tableau, and other common software will help you achieve this.
- Mathematics & Statistics
For the interpretation of data to have true value, you’ll need a clear understanding of statistics and the appropriate level of familiarity with formulae. As a data analyst, you should have a deep knowledge of mathematics and be prepared to find out basic market questions such as compound interest or inflation. You should also be able to use tables, diagrams, graphs, and other data visualization methods. It is necessary to be familiar with some algebra to make data visualization more understanding.
- Advanced Microsoft Excel
Data analysts’ core responsibilities include organizing data and estimating figures. That’s why having advanced skills in Excel is advantageous. There is a multitude of excellent learning resources available to teach you how to use Excel to its full extent.
- Domain knowledge
A data analyst’s role is to provide decision-makers with comprehensive and reliable data. To achieve this, data analysts must have a detailed knowledge of both the customer expectations and the data. This means that you can’t be successful as a data analyst if you don’t know the industry you’re working for and the profiles of the target customers.
- A logical & creative mindset
It’s important to grasp mathematical methods, but it’s much more important to address issues with a creative and analytical attitude. This will help the analyst come up with insightful research questions that will empower the company to get a better understanding of the topic.
- Communication skills
Data analysts must accurately express their findings to a wider group of people or a small group of executives making business decisions. The way you communicate your conclusions is key to your performance as a data analyst.
Allied Market Research forecasts that the big data and business analytics market is going to hit $420.98 billion by 2027, with a CAGR (Compound Annual Growth Rate) of 10.9% between 2020 and 2027. This means that the demand for data professionals will grow, and companies will keep looking for advanced skills.
If you love technology and approach problems with a logical mindset, this could be the right career direction for you.