A Data Analyst is a person who obtains, examines, and conducts a geometric interpretation of data to get substantial results.
These days, companies receive a large amount of data daily that is very useful in optimizing their strategy if correctly analyzed. To fully understand information obtained from the massive data acquired, they require the services of an individual who has gone through professional data analytics training.
The objectives of a Data Analyst are to process the various data that relates to his clients, and the performance of the product or company, in order to give signals that are useful for the decision-makers.
Information provided by a Data Analyst assists companies in the following ways:
- Determine the products to be offered to customers relating to their requirements.
- Pick the best marketing tactics to take up.
- Discover and implement the improvements needed to improve the production process.
Responsibilities of a Data Analyst
Depending on the level of professionalism gotten from their data analytics training, Data Analyst can:
- Classify code problems and data-related complications
- Work with technical teams, and data scientists to complete organizational goals.
- Blueprint, build and maintain comparative databases and data systems.
- Shred data to throw out inappropriate information.
- Give summarized data records and understandable data visualizations for management.
- Investigate and decode results using standard statistical tools and methods.
- Discover untapped opportunities for process improvement.
- Locate patterns and interrelations in complex sets of data.
Qualifications of a Data Analyst
There are several skills required for becoming a Data Analyst, and they can be easily achieved by signing up for data analytics training:
STATISTICAL PROGRAMMING LANGUAGE
This is the computing skill that assists in data analysis; techniques like MATLAB, SAS, and R are statistical programming packages that give a diverse variety of graphical and statistical skills to analyze massive data sets and create a graphical representation for a more fundamental understanding.
There are several dominant programming languages used in performing advanced analysis and predictive analytics for big data sets. Python is faster and more efficient than Microsoft Excel and is a top programming language that would help in complex data analysis.
MATHEMATICS
Analyzing and translating data into real-world value needs proper knowledge of statistics and formulae. Data Analysts should have excellent skills in mathematics, and you should be able to solve fundamental business problems like Calculating compound interest and statistical measurements (Mode, Modal, Median, Mean). Using charts, tables, and graphs to make visual data is also necessary, and college-level algebra.
Linear algebra and Multivariate calculus are extensively used in data analysis, so it is vital that a Data Analyst possesses this skill.
MICROSOFT EXCEL
Microsoft Excel is an important program used in calculating, analyzing and displaying data and information. It helps a Data Analyst to plan and process data using columns and rows with formulas, and there are over 30+ functions that a Data Analyst needs to perfect in order to used Advanced Microsoft Excel in data analysis.
SQL DATABASES
Structured Query Language (SQL) is a domain-specific programming language, designed for data management and data stream management system.
This skill is essential in managing structured data among entities and variables.
CRITICAL THINKING
Successful Data Analysts are good investigators, using data to find solutions to specific questions means figuring out what to initially ask.
Data Analysts are required to disclose and synthesize bridges that are not usually visible, so a Data Analyst is expected to have skills in critical thinking.
DATA PRESENTATION
Critical thinking and data presentation are two interconnected skills; presenting analyzed data is an essential skill that an Analyst needs to help explain the data reading to their employers and clients.
MACHINE LEARNING
Machine learning is rapidly becoming one of the most sort-after topics in the field of data science and analysis. Although not every analyst uses machine learning, this is an important skill to learn as it would help you advance your profession as a Data Analyst.
To understand machine learning, one is expected to have statistical programming skills, and several programs can assist you in developing your machine learning skills.
Other Data Analyst Skill:
- Practical and Strong Communication Skills.
- Data Mining
- XML
- VBA Server
- Data Warehousing
- Database querying Languages
- APIs
Most candidates for entry-level jobs might require a bachelor’s degree in Mathematics, Information Management, Finance, Statistics, Computer Science, and Economics because these courses give significant attention to analytical and statistical skills.
HOW TO START A CAREER AS A DATA ANALYST
Get a bachelor’s degree in computer science, statistics or info Tech.
Taking computer science lectures that focuses more on project management and Database management, study applied statistics and data analysis.
Earn Data Analyst Experience
Getting a professional job without work experience is extremely difficult, and this isn’t different from Data Analyst; applying as an intern is an excellent method to gain invaluable experience and will help with understanding the additional skill in development and data analytics training. Take several online and in-house training classes, especially ones on analytical software programs and big data management.
Advance Degree or Certificate Program
Getting an advanced degree will improve your job opportunities and boost your experience. Employers always want their employees to have a vast knowledge and first-hand experience with the latest technologies and tools. Certification courses for data analytics training programs will generally give exposure to the latest software programs related to the field.
ORGANIZATIONS FOR DATA ANALYST
Data Analysts organizations give opportunities for extensive learning, professional tutoring, and development in the new trends of the tech world. Registered Members of these organizations usually meet to deliberate about these trends, plan on the future of data analytics, and also work on large projects, belonging to these groups would surely help a data analyst.
- International Machine Learning Society (IMLS)
- Digital Analytics Association (DAA)
- International Institute for Analytics (IIA)
- Data Management Association International (DAMA)
- Institute for operations research and management sciences (INFORMS)
- Data Science Association (DSA)
Data analysts should brace themselves for a change because automated business artificial intelligence software is being programmed to understand and accomplish regular tasks that usually require the services of a Data Analyst to handle.
Extensive Data analytical training is the best way to understand these changes and advance one’s skill as a Data Analyst.