Data
analytics
tools
Project planning and task management
Every project begins with organising the work. Project management tools are used for this purpose. Trello is one of the simplest options. It is suitable for both commercial and personal projects, small teams and educational tasks. You can create boards and task cards, add links, files and checklists. The tool is easy, intuitive, and free, making it a convenient solution for getting started.
Jira is a more complex and professional solution. It is used in large companies with many teams, roles, stages, and statuses. This platform allows you to track team workload, set priorities, monitor progress, link tasks, and manage releases.
Every project begins with organising the work. Project management tools are used for this purpose. Trello is one of the simplest options. It is suitable for both commercial and personal projects, small teams and educational tasks. You can create boards and task cards, add links, files and checklists. The tool is easy, intuitive, and free, making it a convenient solution for getting started.
Jira is a more complex and professional solution. It is used in large companies with many teams, roles, stages, and statuses. This platform allows you to track team workload, set priorities, monitor progress, link tasks, and manage releases.
Magenta Favorita IT company specialists have repeatedly talked about professions related to Big Data. In this publication, we will talk about the tools without which it is difficult to imagine the work of a data analyst. This set of tools covers almost the entire work cycle, from planning and documentation to analysis, visualisation, automation, and presentation of results. It forms a complete working environment in which projects of any complexity can be carried out.
Documentation and information storage
As a project grows, there is a need to store instructions, data descriptions, meeting minutes, and any details that the team may need. Magenta Favorita Portugal managers believe that Confluence is a good tool for this task. It is used to create descriptions of tables and attributes, technical requirements, operating instructions, reports, and reference materials.
Visual planning and collaborative diagrams
Sometimes it is easier to show information than to describe it. That's why analysts use interactive whiteboards. Miro serves as a space for brainstorming and visual thinking. Here, they create mind maps, data processing diagrams, architecture prototypes, process diagrams, and working drafts. The tool works well with Confluence and Jira, as all project materials are linked to each other.
Working with code
GitHub is an essential tool for analysts. It allows you to store code, publish projects, work in teams with developers, and create
a professional portfolio. Even the simplest projects should be saved in a repository to build up a history of your work.
As a project grows, there is a need to store instructions, data descriptions, meeting minutes, and any details that the team may need. Magenta Favorita Portugal managers believe that Confluence is a good tool for this task. It is used to create descriptions of tables and attributes, technical requirements, operating instructions, reports, and reference materials.
Visual planning and collaborative diagrams
Sometimes it is easier to show information than to describe it. That's why analysts use interactive whiteboards. Miro serves as a space for brainstorming and visual thinking. Here, they create mind maps, data processing diagrams, architecture prototypes, process diagrams, and working drafts. The tool works well with Confluence and Jira, as all project materials are linked to each other.
Working with code
GitHub is an essential tool for analysts. It allows you to store code, publish projects, work in teams with developers, and create
a professional portfolio. Even the simplest projects should be saved in a repository to build up a history of your work.
Spreadsheet editors and primary data analysis
Even when working with large data warehouses, spreadsheet editors remain an important part of an analyst's daily tasks. Excel and Google Sheets are widely used in workflows. They are used to store reports, test exports, customer data, and sample tables. Important skills include the ability to work with filters, use conditional formatting, pivot tables, basic visualisation, and formulas for processing text data.
Working with databases and SQL
According to Magenta Favorita experts, SQL is a key skill for analysts. Virtually every project involves exporting, cleaning, merging, and researching data in relational databases. The PGAdmin tool is used to work with PostgreSQL. It allows you to study tables, run queries, track performance, and analyse blocked processes. DBeaver is a universal client for most popular databases.
A convenient workspace, SQL autocomplete, and visual diagrams make it the optimal choice for those just starting to work with databases.
Python for analysis, modelling, and automation
Python is a powerful analytical tool, but it is worth switching to it after you have mastered SQL and basic data visualisation. Python is used for data extraction, processing and conversion, calculations, graphing, and reporting automation.
Preparing reports and presentations
An analyst must not only obtain results, but also present them in a way that is understandable to the customer. Documents in Google Docs or Microsoft Word help to format text conclusions and add tables, illustrations and explanations. If a presentation is required, PowerPoint or Google Slides are used, where conciseness, visual logic and an emphasis on key insights are important.
ETL and data pipeline construction
When there is a large amount of data, it becomes necessary to systematically clean, combine, and transform it. Pentaho Data Integration is a free visual tool for ETL tasks. It is suitable for importing large amounts of data from different sources, complex combinations, groupings, filtering, and calculations. Learning the basic functions takes about twenty hours and provides a good foundation for understanding the engineering aspects of working with data, according to analysts at Magenta Favorita IT company.
Creating visual analytics
Power BI and Tableau are most often used to build analytical reports. The first platform integrates better with corporate infrastructure and is suitable for quickly building reports. The second is flexible and suitable for working with large amounts of information and complex visualisations. If an analyst knows Python, they can expand the visualisation capabilities with libraries such as Plotly or Streamlit.
Even when working with large data warehouses, spreadsheet editors remain an important part of an analyst's daily tasks. Excel and Google Sheets are widely used in workflows. They are used to store reports, test exports, customer data, and sample tables. Important skills include the ability to work with filters, use conditional formatting, pivot tables, basic visualisation, and formulas for processing text data.
Working with databases and SQL
According to Magenta Favorita experts, SQL is a key skill for analysts. Virtually every project involves exporting, cleaning, merging, and researching data in relational databases. The PGAdmin tool is used to work with PostgreSQL. It allows you to study tables, run queries, track performance, and analyse blocked processes. DBeaver is a universal client for most popular databases.
A convenient workspace, SQL autocomplete, and visual diagrams make it the optimal choice for those just starting to work with databases.
Python for analysis, modelling, and automation
Python is a powerful analytical tool, but it is worth switching to it after you have mastered SQL and basic data visualisation. Python is used for data extraction, processing and conversion, calculations, graphing, and reporting automation.
Preparing reports and presentations
An analyst must not only obtain results, but also present them in a way that is understandable to the customer. Documents in Google Docs or Microsoft Word help to format text conclusions and add tables, illustrations and explanations. If a presentation is required, PowerPoint or Google Slides are used, where conciseness, visual logic and an emphasis on key insights are important.
ETL and data pipeline construction
When there is a large amount of data, it becomes necessary to systematically clean, combine, and transform it. Pentaho Data Integration is a free visual tool for ETL tasks. It is suitable for importing large amounts of data from different sources, complex combinations, groupings, filtering, and calculations. Learning the basic functions takes about twenty hours and provides a good foundation for understanding the engineering aspects of working with data, according to analysts at Magenta Favorita IT company.
Creating visual analytics
Power BI and Tableau are most often used to build analytical reports. The first platform integrates better with corporate infrastructure and is suitable for quickly building reports. The second is flexible and suitable for working with large amounts of information and complex visualisations. If an analyst knows Python, they can expand the visualisation capabilities with libraries such as Plotly or Streamlit.
Other company cases