What is a data analyst?

The data analyst. Turning data into decisions.

In the information age, data has become one of the most valuable assets for companies. However, merely collecting data is not enough; it is crucial to analyze it and transform it into useful information that can guide strategic decisions. This is where the Data Analyst comes into play, a key professional in the digital transformation of organizations.

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At Ubiqum we offer three programs adapted to people with more or less technical background:

.- Business Analytics and Power BI. For those with less technical background and business experience.

.- Data Analytics and Machine Learning. For people with a good technical background who want to start in this field.

.- Data Science and Deep Learning. For people with a very good technical background who want to professionalize in the most technical part of data science.

Below, we explain in detail what a data analyst is, his or her role in different functional areas and how he or she interacts with executive roles.

What a Data Analyst does.

A data analyst is a professional tasked with examining and analyzing data sets to draw conclusions that can be used to make informed decisions. They use statistical and software tools to clean, process and model data, and ultimately communicate their findings clearly and effectively to stakeholders.

Main Functions of a Data Analyst

Data Collection and Cleaning
- Collection: They collect data from various sources, either internal (such as company databases) or external (such as surveys and market research).
- Cleaning: Ensures that data is clean and error-free, including removing duplicates, correcting errors and addressing missing values.
Preliminary Data Analysis
- EDA (Exploratory data Analysis): Analyze data in a preliminary way to discover patterns, trends and anomalies.
- Statistician. FE (Feature Engineering) They use advanced statistical techniques to identify significant relationships between different variables.
Data Modeling
- Prediction: Develop predictive models that can anticipate future behavior or results based on historical data.
- Optimization: They create models that help optimize processes and resources within the company.
Data Visualization
- Graphics and Dashboards: Use visualization tools to create interactive graphics and dashboards that facilitate the understanding of data.
- Reports: Prepare detailed reports that present your findings in a clear and concise manner.
Communication of Results
- Presentations: They present their analysis and recommendations to executives and other company stakeholders.
- Advice: They act as internal consultants, providing data-driven advice to support decision making.

What to study to become a data analyst.

To become a data analyst, a combination of technical and analytical skills is required. At Ubiqum Code Academy, we offer data analytics courses designed to equip students with the tools and knowledge necessary to succeed in this field. Our hands-on methodology, flexibility and customization ensure that each student can learn at their own pace and receive the support needed to achieve their career goals.

Programming Languages: Knowledge in languages such as Python, R, SQL, among others.
Statistics: Descriptive statistics and calculation of probabilities. For advanced students it also applies linear algebra and calculus.
Analysis Tools: Familiarity with data analysis tools and software such as Excel, Tableau, Power BI, etc.
Critical Thinking: Ability to create models, evaluate their quality, interpret the results and draw meaningful conclusions.
Data Presentation: Ability to communicate findings clearly and effectively to non-technical audiences.
Collaboration: Ability to work as part of a team and collaborate with different departments.

What to learn to become a data analyst

At Ubiqum we offer three programs focused on three different student profiles. In each of them the student gets a solid foundation in Python programming and in the use of the libraries mentioned above.

Data Analysis and Machine Learning Courses

Some tasks performed by a data analyst.

- Market Segmentation: Identify and define specific market segments for marketing campaigns.
- Campaign Analysis: Evaluate the effectiveness of marketing campaigns and propose adjustments based on performance data.
- Sales Forecasting: Using predictive models (time series analysis) to anticipate sales trends and prepare appropriate strategies.
- Price Optimization: Analyzing sales and pricing data to identify optimal pricing strategies.
- Process Efficiency: Analyzing operational data to identify bottlenecks and areas for improvement in production processes.
- Inventory Management: Using data to optimize inventory levels and reduce storage costs.
- Talent Analysis: Helping to identify patterns in employee turnover and propose strategies to retain talent.
- Staff Productivity: Analyzing performance data to improve staff productivity and job satisfaction.

The executive role of a data analyst.

A data analyst can opt for a technical career or an executive career.

The technical career, now that it is a relatively new field and there are few people trained, is suitable for junior and middle management profiles.

The executive career is the natural path if you are really interested in Senior Management. In 5 years most likely, but in 10 years for sure, every top executive of a company should have solid and deep knowledge in this field.

Data analysis is the most direct path to the C-Suite.