Data analytics is prominent today, especially because of large amounts of data being generated today. However, to qualify as a data analyst, you need different skills for handling tasks. Therefore, it is essential to understand the things you need and the skills you should acquire to enter this field.
The skillset needed to handle the responsibilities of a data analyst includes:
- Data visualization tools
- A good understanding of machine learning algorithms and statistics
- Deep knowledge of tools used in data analysis
- Programming knowledge
- Domain expertise and a degree
Things covered in analytics
Analyzing means scrutinizing something to derive some useful information. Data analytics involves drawing insights from raw data. The insights include market trends, product innovations, and business information.
We can compare data analytics to a puzzle. The first thing to do when handling a puzzle is to ensure all the pieces are gathered. Then, these pieces must be fitted correctly to give the final picture. In data analytics, data collected needs to be analyzed and cleaned. Then, the same data must be converted to information we can interpret.
Data can be unstructured, semi-structured, or structured. We can also visually represent the final result in charts and graphs, which give the results precisely. There are different frameworks and tools used in the process of analysis. Today, the demand for professionals capable of converting raw data into a meaningful form is high. Information aids with business growth.
Data analysts
Data analysts are responsible for collecting and processing data. They perform analysis tasks on data sets. Every business generates data through marketing research, logistics, accounts, and feedback, regardless of size.
A data analyst collects, processes, and performs analysis of large datasets. Every business, small or big, generates and collects data. A data analyst’s responsibility is to take data and figure out different measures that can be applied to benefit the business. In addition, analysts have to deal with reporting, data modeling, and data handling.
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Roles of a data analyst
Data analysts have a wide range of responsibilities and roles they need to satisfy in their areas of expertise. Before getting started, you need to understand the responsibilities you must handle. Some of the responsibilities include:
Understanding goals
A data analyst needs to identify the different goals of an organization. Next, they need to assess all resources that are available and comprehend all problems of a business. Finally, they need to collect the correct data.
Querying
Data analysts need to use SQL queries as well as scripts to help them gather, manipulate, store, and retrieve information from all sorts of databases like MySQL, Oracle DB, and MS SQL servers.
Data mining
We can mine data from so many sources today. This data can then be organized to get some new details from it. This facilitates the creation of data models to make the systems even more efficient.
Data cleansing
Cleaning and wrangling data is a duty that data analysts have to master. The data gathered is usually very messy and may have little value at a glance. However, this kind of data needs to be cleaned to ensure it is ready to be analyzed.
Data examining
Data analysts must use statistical and analytical tools, including programming languages, to conduct the most logical data examination.
Interpreting trends
Data analysts can use different libraries and packages to spot patterns and trends from various datasets. This helps them to discover some business insights that would have been otherwise invisible.
Summary reports preparation
Data analysts need to handle summary reports using data visualization tools. The reports are a good option because they guide the team to make the best decisions at the right time.
Team collaboration
Analysts must interact with data scientists, development teams, and management teams to implement business requirements correctly. It also helps to find the best way to improve all the available opportunities.
Having a clear understanding of the above information helps you appreciate how important the work of a data analyst is. Knowing their responsibilities and roles should motivate you to know how you can become one. While some skill sets are learned while working, you need to study different subjects and master them.
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The subjects in data analytics
The course syllabus in data analytics is not always uniform or identical. The syllabus can differ from one course to the next. However, there are some common subjects you can expect to cover in data analytics. They include:
- Data structures and algorithms
- Data collection
- Text analytics
- Business fundamentals
- Relational database management systems
- Probability and statistics
- Forecasting analytics
- Statistical analysis
- Data visualization
Subjects falling under big data
Data analysts need to handle big data and extract information from it. Therefore, training in big data is necessary to find correlations, predictions, market trends, and patterns. Under big data analytics, a data analyst can expect to cover the following subjects.
- Statistical methods
- Stochastic process and probability
- Foundations of data science
- Linear algebra and programming
- Machine learning
- Data science enabling technologies
- Computing for data sciences
- Non-relational and relational database management
- Elective course
- Value thinking
- Python Programming
- Machine learning
- Internship-based project work
- Elective courses
- Operations management modeling
- Data visualization using Tableau
Computer science combined with data analytics subjects
When you decide to pursue a computer science degree in data analytics, a syllabus is designed to offer you value, ensuring that all basics are covered, and you can delve even deeper. While electives offered can differ from one institution to the next, some of the common subjects to expect in such a course include:
- Language
- English
- Programming in C and C++
- Internet basics
- Data structures
- Linear algebra
- Discrete mathematics
- Environmental studies
- Value education
- Programming: Java, Python, R
- Data warehousing and mining
- Deep learning
- Data networks and communication
- Data visualization
- Capstone project work
- Big data analytics
- Linux and shell programming
- Machine learning
MBA data analytics subjects
Under this type of course, there are some subjects you can expect to be offered in different colleges in their curriculum. In addition, as with the other data analytics courses, electives can differ. Subjects include:
- Accounting for managers
- Applied statistics
- Applied operations research
- Data cleaning, data mining, and data normalization
- Econometrics
- Financial reporting and analysis
- Business Analytics
- Macroeconomics- global economy
- Project management
- Organizational behavior
- Spreadsheet modeling
- Research Methodology
- HR analytics
- Healthcare analytics
- Foundation in predictive and descriptive analysis
- Programming
- Legal and ethical aspects of analytics
- Social and web analytics
- Stochastic modeling
Conclusion
Data analytics is essential today, and many opportunities exist for those who take this field seriously. You could choose to take various courses to study data analytics. The subjects you cover depend on the course taken, level, and institution picked. It is also essential to handle projects and internships because a data analyst needs to practice with accurate data.
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