Data development that continues yearly requires more and more competent data analysts. This one job focuses more on various types of data for specific needs—generally, the use of data for companies or institutions to make critical decisions for business development.
There are also government agencies that use it as capital to make policies.
What is Data Analysis
A data analyst is responsible for conducting data analysis and research (data analytics) using specific tools.
In the business world, data analysts conduct research for marketing or product development purposes, where they see the activity of the target market on the internet.
It can be from what the target market is often looking for on search engines and social media.
A data analyst is now very much needed in the business world because behavior, tastes, and trends close to the target market change quickly.
Compared to Manual Research
Compared to manual research, which takes a long time because they have to create and collect questionnaires for respondents, this data analytics process saves time with more accurate data.
Data analysis capability makes it very easy to conduct research with dense, accurate, time-efficient data. In addition, researchers and lecturers with this skill have an excellent opportunity to get other research projects with various parties that are very “cheap,” guys!
The Differences of Data Analyst and Data Science
Because they both come from the data science family, many think that data analysis and data science are the same professions. Both have significant differences, you know!
The first difference between a data analyst and a data scientist is in terms of the origin of the data being worked on. Generally, a data analyst retrieves data based on the tools or programming language he uses, for example, R, Tableau, or PHP.
Meanwhile, data scientists need the help of tools to summarize data. More complex than data analyst tasks, a data scientist needs to work with specific algorithms to find data sources.
The second difference between data analysts and data scientists is the difficulty. Based on the explanation above, data scientists have more challenging and complex tasks than data analysts. However, you can become a data analyst, too, after becoming a data scientist.
Data Analysis Duties
After knowing what data analysis is, it’s time to determine their duties and responsibilities. As you know, data analysts must be able to turn raw data into valuable information.
They start from the analysis process to the implementation of the results to answer existing problems into solutions or strategies for the company’s business.
The Data Analyst will convey the results of his work to stakeholders or decision-makers for further implementation of the solution.
1. Gathering the data
Data analyst’s primary and most basic task, namely collecting data. You can start by getting data from company databases or extracting it from external sources for further research and analysis.
2. Cleaning the data
Before starting the analysis, the data analyst must carry out a thorough data cleansing process. The excellent analysis rests on clean data. Cleaning involves deleting data that could interfere with your research or not fit the purpose of your study.
3. Think logically and analytical
When performing data analysis, data analysts follow the data evaluation process using analytical and logical reasoning to examine each existing data component. Usually uses, statistical tools to analyze and interpret data. Here, various tools and programming languages are generally data analysts to help them do their analysis.
4. Find trend, collaboration and pattern
Once the data is analyzed, data analysts find trends, correlations, and patterns in complex data sets. Here, data analysts look for short-term and long-term trends.
Later, the results of these findings can help understand how a business is performing and predict current business practices.
Through these findings, companies or institutions can improve or make decisions necessary for the sustainability of the company or institution.
5. Good at presentation
If you think a data analyst will stay silent in front of the computer. So your estimate needs to be corrected. A data analyst must be able to communicate well.
Even being required to be able to tell an exciting story with data is critical to getting the point of your analysis across and defending your ideas.
Therefore, data visualization is reasonably necessary too. Data analysts generally use attractive, high-quality charts and graphs to present their findings clearly and concisely.
6. Storage
Data analysts must ensure that the storage, availability, and coherence of data stored electronically meet the organization’s needs.
Data analysts need technical expertise regarding data models and database design development to make the most of it.
Hard Skills
1. Operates Microsoft Excel
Microsoft Excel is generally required for data analysis because the data form was in numbers. Various formulas can answer processes and conclusions from Microsoft Excel.
2. Mastering programming languages
To be a data analyst, you should take advantage of this complex skill: Programming language. Typically, data analysts use R or Python to analyze large data sets.
3. Operate SQL
SQL is a database that stores a lot of data for you to process into information.
SQL is software that data analysts commonly use in data analysis. It can work faster than Microsoft Excel, accommodating a more significant amount and data capacity.
4. Data visualization
A data analyst will visualize data after collecting, compiling, and analyzing data. Data visualization is translating large data sets into information with conclusions that companies or clients can understand.
You will use SAS, Tableau, or Cognos tools if you are a data analyst.
5. Machine learning
The data you get based on search results on the internet adjusts to the algorithm. Search engine algorithms and every social media are undoubtedly different, which can influence internet users’ decisions to search, review, and purchase decisions.
Therefore, data analysts must understand how machine learning works with AI or artificial intelligence that is not controlled by human reason.
6. Statistics
Data Analysts set a form of numbers. They need statistical skills to interpret the data, so information from it can be understood and relevant based on the company’s or client’s problems.
7. Data warehousing
Your responsibility as a data analyst is to monitor and ensure data is stored safely. To do this, you must have data warehousing capabilities.