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Data Analyst

Data Analyst Job Filed

Data Analyst is now a very popular profession. Considering that nearly all industries rely on data to make crucial business decisions - which new products to develop, which new markets to enter, as well as which new (or existing) customers to target. Data Analysts also use data to identify inefficiencies and other business issues that need to be addressed. A Data Analyst will interpret data by gathering information from various sources and interpreting existing patterns and trends. Then, it becomes information that can be used as a reference to improve business. The daily job of a Data Analyst consists of various activities, starting from analyzing data, producing various types of outputs, compiling strategic studies (including detailed customer behavior analysis, market research, and competitive monitoring), to creating custom reports or marketing targets for inbound and outbound advertising.

Duties and Responsibilities of Data Analysts

  1. Collect and process data from various data sources, both primary and secondary data sources
  2. Identify, analyze and interpret patterns and trends in data sets
  3. Interpret data and analyze results using statistical techniques to support informed decision making
  4. Compile the data sets into a report
  5. Work with a team to define business needs and priorities
  6. Identifying new opportunities to improve product quality and business efficiency

Skills a Data Analyst Should Have

To become a Data Analyst, certain skills are needed so that the task can be done well. The following are skills that need to be mastered to undergo this profession.

Hard Skills :
  1. Proficient in programming languages
  2. High-level math skills
  3. Ability to analyze, model, and interpret data
  4. Have an interest in machine learning
  5. Mastering data visualization
Soft Skills :
  1. Problem-solving skills
  2. The methodical and logical approach
  3. Written and verbal communication
  4. Interpersonal skills
  5. Skills for working in teams
  6. Think critically
  7. Be thorough in the details
  8. Good presentation skills
  9. Ability to meet deadlines

Software and Tools that a Data Analyst Should Master

1. Databases (SQL, etc.)

SQL is a programming language that is used to manage data which is stored in relational databases, effectively handling structured data in database tools. This programming language is very popular and a tool that is widely used in various business cases and data scenarios. There are different types of SQL-based data management systems, such as PostgreSQL, MS SQL, Oracle, and most popularly, MySQL.

2. Analytics data warehouse tools (BigQuery, etc.)

The data warehouse is the center of information that can be analyzed by the Data Analyst which is then used as a basis for making decisions. Data is collected from transactional systems, relational databases, and other sources regularly. Business analysts, data engineers, data scientists, and decision-makers access data through business intelligence (BI) tools, SQL clients, and other analytical applications.

3. Business Intelligence Tools

BI tools are a type of software that is used to collect, process, analyze, and visualize past, current, and future data to generate actionable business insights, create interactive reports, and simplify the decision-making process. There are many applications and programs that fall into this category.

Some of the more well-known tools are Tableau, SAS, Looker, and Google Data Studio. Although these tools have important differences, their basic purpose is the same: They allow you to combine data from different sources to create dashboards and metrics for developing business strategy.

4. Programming (Python, R, etc.)

The most common programming languages for data analysis are Python and R. Through programming, a Data Analyst can perform sophisticated statistical analysis, create high-quality custom visualizations, and interact with data APIs to retrieve data.

Python is an open-source solution that has a simple coding and syntax process so it's quite easy to learn. And it can also be integrated with other languages, such as C / C ++, Java, PHP, C #, etc. Python is very accessible compared to other popular languages such as Java, and its relatively easy-to-learn syntax makes this tool popular with users looking for open-source solutions and a simple coding process.

5. Spreadsheet (Excel, Google Spreadsheet, etc.)

Spreadsheets are a form of data analysis that is quite popular in any industry, business, or organization. This tool can be used for simple analyzes that do not require special training or complex, large-volume databases to maintain.

Microsoft Excel is a popular spreadsheet that, as its name implies, is part of the Microsoft Office family. Although often considered a traditional analysis tool, Excel is still widely used throughout the world. From organizing, manipulating, calculating, and evaluating quantitative data, to building complex equations and creating charts and graphs.

6. Reporting tools (Business Objects, etc.)

Reporting tools play an important function in business operations, enabling Data Analysts to produce short, constantly updated reports that can be forwarded to other teams to monitor, adjust, or just find out about how things are going. The reporting tools will allow you to collect a subset that is relevant and specific to your business.

General Requirements to Become a Data Analyst

As a Data Analyst, mastery and understanding of the various skills described above are very important. There is also a need for discipline and high responsibility so that the work can go well. Not only that but a relevant educational background (especially IT) is also needed.

Educational Background and Experience of Data Analyst

  1. A bachelor's degree in a quantitative or relevant field of study
  2. Have previous experience as a Data Analyst
  3. Experience in using SQL and familiar with data analysis tools (python and MS Excel)
  4. Basic understanding of SEO and familiarity with Google Products; Spreadsheets, Analytics, Search Console, Data Studio, etc. will be a plus

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Information

Before submitting your job application form, please check the following important things that must be included in your Curriculum Vitae:

  1. Personal information, including: full name, email, date of birth and address;
  2. Education details, from high school to college; Work experience, including part-time work if any; Attach other things that can enhance your self-promotion;
  3. For further information, please ask via email at recruitment@cmlabs.co
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