Data Analytics
for Business Analytics

In today’s data-driven world, the most valuable professionals are those who make smart decisions backed by evidence. This course equips students with the skills to turn raw data into clear, actionable insights.

Students will learn to collect, clean, and analyze data to spot trends, uncover patterns, and support better business, product, and research decisions.

Data Analytics for Business Application is perfect for ...

The course will be useful for anyone interested in business analytics: seeking to master a new profession or deepen their knowledge in the field of business analysis in the IT industry.

For beginners, non-IT specialists

who want to gain knowledge in a new, in-demand field and are ready to learn from scratch.

Business analysts

who want to move into the IT field and gain the necessary knowledge to develop their career in a new direction.

For IT company owners

who want to master business analysis tools and save company resources.

For IT professionals

who want to expand their knowledge and change their direction in IT.

After completing the Data Analyst course, you will be able to:

Possess key analytics tools:

learn to work with programs and languages such as Tableau, SQL, Python, and other tools for data analysis.

Create clear data visualizations:

use tools like Tableau or Power BI to create intuitive visualizations and dashboards.

Effectively process and analyze data:

use tools and techniques to collect, clean and analyze data, revealing useful insights.

Perform statistical analysis:

apply statistical methods to interpret data and conclusions.

Make predictions based on data:

use forecasting techniques to analyze trends and predict future events.

Make informed decisions based on data:

use analytical findings to support strategic business decisions.

Engage with business users and stakeholders:

translate technical insights into business-friendly recommendations.

Improve business processes:

use data analytics to identify opportunities for optimization and efficiency in business operations.

Possess key analytics tools:

learn to work with programs and languages such as Tableau, SQL, Python, and other tools for data analysis.

Create clear data visualizations:

use tools like Tableau or Power BI to create intuitive visualizations and dashboards.

Effectively process and analyze data:

use tools and techniques to collect, clean and analyze data, revealing useful insights.

Perform statistical analysis:

apply statistical methods to interpret data and conclusions.

Make predictions based on data:

use forecasting techniques to analyze trends and predict future events.

Make informed decisions based on data:

use analytical findings to support strategic business decisions.

Engage with business users and stakeholders:

translate technical insights into business-friendly recommendations.

Improve business processes:

use data analytics to identify opportunities for optimization and efficiency in business operations.

A wide range of industries for employment:

Data Analysts are in demand in a variety of industries, from finance and marketing to healthcare and technology.

High demand on the labor market:

As the volume of data increases, the demand for skilled data analysts continues to grow.

Competitive salary:

The profession usually offers high salaries, especially with the development of experience and specialization.

Variety of tasks and projects:

Working with different types of data and in different industries provides interesting and varied tasks.

Influence on decision-making:

Data Analysts often play an important role in formulating strategies and making decisions based on data analysis.

Ability to work remotely:

Many aspects of the work can be done remotely, which provides flexibility in the choice of work environment.

Beginners:

specialists in Ukraine earn money at the start of their careers

from $500 to $970

month

Average:

with 1-5 years of experience, the salary level can be

from $800 to $2188

month

Experienced specialists:

with a high level of expertise, specialists can earn

from $2000 - $5000

month

Freelance and consulting:

analysts working as freelancers or as independent consultants may have different rates depending on the project and their experience.

Specialization and additional skills:

having additional skills, such as machine learning or big data, can increase salary levels.

This course will form a comprehensive view of the data analyst profession.

Data Base Theory and SQL

Introduction to database theory. History, models, relational model, Codd's rules, overview of MS SQL Server.
Basics of interacting with MS SQL Server. Creating and modifying tables, data types, indexes.
SELECT, INSERT, UPDATE , DELETE queries. Operators, using transactions.
Multi-table databases. Normalization, foreign keys, types of relationships.
JOINs and combines query results. Different types of JOIN, UNION.
Aggregate functions, subqueries, window functions. Grouping, filtering groups.
Views, triggers, stored procedures, and functions. Using CTE.
Exam. Assessment of knowledge and skills acquired during the course.

Python for Data Analytics

Introduction to Py thon. History, tools, installation.
Variables and data types. Working with the console, operators.
Data type conversion. Logical operators and conditions.
Loops and debugging.
Strings and lists. Methods, slicing, working with collections.
Functions. Definition, arguments, scope.
Exception handling.
Working with files. Read and write operations.
Basics of OOP. Encapsulation, inheritance, polymorphism.
Pandas for data analysis.
Numpy for scientific computing.
Visualization with Matplotlib.
Advanced visualization with Seaborn.
AI, Generative AI, LLM, and programmer efficiency.
Exam.

Using Power BI for Business Analytics and Data Visualization

Basics of Power BI. Definition, ob jectives, installation, creating the first report.
Working with data. Importing, transforming, cleaning data.
Data models. Development , defining relationships, creating measures and calculated columns.
Reports. Creation and visualization, customization, publication.
DA X. Basics, advanced features, practical application.
Dashboards. Creation, customization, roles.
Exam.

Download the program

Data Analytics for Business Application

Schedule

twice a week

Duration

9 months

Age

14-55 years old

Time:

4 hours per week

Payment in installments

PHP 6 905 month

For monthly payment

Full payment

PHP 6 214 month

Under terms of payment
entire course: PHP55 929

schedule-new__full-description_one PHP55 929

Book now

Study results

After the Data Analytics for Business Application course you will be able to:

work with data types, variables, loops, conditions, and debugging.

manipulate strings, lists, functions.

handle errors and apply OOP principles.

use Pandas and Numpy for data analysis.

create visualizations in Matplotlib and Seaborn.

understand the basics of Generative Al and Large Language Models, create prompts.

enhance productivity through ChatGPT, GitHub, Copilot, and other Al tools.

use the OpenAl API in applications.

upload, clean, and transform data.

create queries and analyze results.

design databases and normalize tables.

work with SQL : queries of any complexity, aggregation, subqueries, JOIN, CTE.

create procedures, triggers, functions.

modify database structure through DDL.

IT Step Academy collaborates with local and international companies. We regularly update and post job offers from our partners and provide students with employment possibilities.

Frequently Asked Questions

How do I know if the Data Analyst profession is right for me?

What does a data analyst do?

Processes and analyzes data using various analytical tools. Visualize data: Using tools like Tableau or Power BI to create intuitive visualizations and dashboards.

Who can study, and are there any age or knowledge restrictions?

Anyone over the age of 18 can study on the course, regardless of basic education. There is no need to take any entrance exams or tests.

What document/certificate will I receive after completing the Academy online?

IT Step Computer Academy diploma in two languages: Ukrainian and English.

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Data Analyticsfor Business Analytics

Data Analytics for Business Application is perfect for ...

After completing the Data Analyst course, you will be able to:

Possess key analytics tools:

Create clear data visualizations:

Effectively process and analyze data:

Perform statistical analysis:

Make predictions based on data:

Make informed decisions based on data:

Engage with business users and stakeholders:

Improve business processes:

Possess key analytics tools:

Create clear data visualizations:

Effectively process and analyze data:

Perform statistical analysis:

Make predictions based on data:

Make informed decisions based on data:

Engage with business users and stakeholders:

Improve business processes:

Advantages of the professionData Analyst

A wide range of industries for employment:

High demand on the labor market:

Competitive salary:

Variety of tasks and projects:

Influence on decision-making:

Ability to work remotely:

How much does Data Analyst earn?

Beginners:

Average:

Experienced specialists:

Freelance and consulting:

Specialization and additional skills:

Training program Data Analyst

Data Base Theory and SQL

Python for Data Analytics

Using Power BI for Business Analytics and Data Visualization

Choose your method of payment

Data Analytics for Business Application

Study results

Career Opportunities for a Data Analyst

Ready to start studying on a data analytics course?

Frequently Asked Questions

How do I know if the Data Analyst profession is right for me?

What does a data analyst do?

Who can study, and are there any age or knowledge restrictions?

What document/certificate will I receive after completing the Academy online?

Would you like to receive a set of demonstration lessons?

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Data Analytics
for Business Analytics

Advantages of the profession
Data Analyst

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of demonstration lessons?