Data cleaning consists of normalizing them according to a predetermined format. It includes managing missing data, correcting errors, and deleting outliers. Some examples of data cleansing are:
• Change all date values to a common standard format.
• Correct misspellings or extra spaces.
• Correct mathematical inaccuracies or remove commas from large numbers.

Is a preliminary analysis of data used to plan other strategies for modelling. Data scientists gain an initial understanding of data through descriptive statistics and data visualization tools. They then explore the data to identify interesting patterns that can be studied or used.

Software and algorithms are used to gain deeper insights, predict outcomes, and prescribe the best action. The techniques of regression analysis, multivariate analysis, econometric models, and machine learning, as well as association, classification, and grouping, are applied to the training dataset. The model could be tested with predetermined test data to assess the accuracy of the results. The data model can be adjusted many times to improve outcomes.

Regression analysis is a statistical method that allows examining the relationship between two or more variables and identifying which are the ones that have the most significant impact on a topic of interest.

refers to different methods that study and examine the simultaneous effect of multiple variables. Multivariate statistical methods analyze the collective behaviour of more than one random variable.

These are defined as those models that contain the set of hypotheses necessary for their empirical application; they constitute, in short, the instrument that allows one to connect and confront theory and reality.

Data scientists work alongside analysts and businesses to turn data insights into action. They make diagrams, graphs, and tables to represent trends and predictions. Data synthesis helps stakeholders understand and effectively apply the results.

Economic analysis is crucial to a company's planning, evaluation, and control. This diagnosis always offers a global vision of the organization’s structure concerning its profitability, solvency, and risks. With the data obtained, decisions to be made can be better oriented.

Promote knowledge of financial and entrepreneurship issues in people willing to create new companies.
The Economic Advisory makes available to clients’ consultation services in matters such as financing for projects and companies, economic-financial studies and modelling and financing and refinancing strategies.
Administrative Advice is to support clients in the timely decision-making and proper management of their company, including analysis at the level of the organizational structure considering the distribution of functions for each of the company's jobs causing efficient and effective development.

Coding, in simpler terms, is the language used by computers to understand our commands and, therefore, process our requests. Programming is a list of codes arranged in a sequence that results in the completion of work. Statistical coding is the form of classification that is most familiar to researchers. Coding is the task of taking data and assigning it to categories. This allows us to turn usually qualitative data into quantitative or numerical data.

Statistical Programming refers to computation techniques that help in data analysis. Making sense of data using statistical concepts/methodology is usually achieved by writing code, and the programming language used to perform this task is called statistical programming. This concept is widely used in industries like Pharma, telecom, banking & finance, and weather forecasts.

Some languages come with statistical programming packages/libraries that offer various statistical and graphical techniques to explore large data sets and create graphical displays for better and quick understanding.

These packages support statistical techniques like linear and nonlinear modelling, classification, clustering, and time-series analysis.