Fuentes de datos en el business analitycs

Summary

Business analytics involves transforming data into actionable insights to help organizations make informed decisions. The process includes data collection, storage, preparation, and exploration, followed by modeling or prediction to address business questions. Data can come from internal sources, such as website visits and customer databases, or external sources like social media APIs and government databases. Data engineers maintain databases that data scientists use to analyze and respond to business needs, enabling data-driven decision-making. Business analytics has a wide range of applications, limited only by imagination.

Takeaways

• 😀 Business analytics is the scientific process of transforming data into insights to improve decision-making.
• 😀 The process involves several steps: data collection, storage, preparation, exploration, visualization, modeling, communication, and decision-making.
• 😀 Data can come from both internal and external sources, including websites, customer databases, machinery sensors, and more.
• 😀 External data sources include open data provided by governments, APIs from social media, Google Maps, and other services.
• 😀 Data engineers are responsible for building and maintaining databases that store these diverse data sources.
• 😀 Data scientists use these data sources to answer specific business questions and support decision-making.
• 😀 Effective data analysis is key to enabling organizations to make data-driven decisions.
• 😀 The applications of business analytics are vast, with possibilities limited only by imagination.
• 😀 Visualization and exploration of data are essential steps to understand the context of the problem being addressed.
• 😀 Models and predictions play a crucial role in answering business questions and shaping outcomes.
• 😀 The end goal of business analytics is to help organizations improve their performance and decision-making processes through insights derived from data.

Q & A

What is the main purpose of business analytics?

The main purpose of business analytics is to transform data into conclusions to help organizations make better decisions.

What are some of the key activities involved in the business analytics process?

Key activities include data collection, data preparation (cleaning and transformation), exploration and visualization, modeling, experimentation, prediction, communication of results, and decision-making.

What is the role of data engineers in business analytics?

Data engineers are responsible for building and maintaining databases that are used by data scientists to answer relevant business questions.

Where do the data used in business analytics come from?

Data can come from both internal sources (such as website visits, customer databases, machine sensors, logistics data, etc.) and external sources (such as open data from governments and APIs for social media or mapping services).

What are open or public data sources?

Open or public data sources are datasets made available to the public, such as government-provided data or information accessible through APIs from services like social media or Google Maps.

How do data scientists use the data provided by engineers?

Data scientists use the data to model, experiment, and predict in order to answer business questions and support decision-making within the organization.

What is the significance of data in business analytics?

Data is essential for business analytics because it forms the foundation upon which decisions are made. Without accurate and relevant data, organizations cannot make informed decisions.

What types of data might be collected internally within an organization?

Internally, organizations may collect data from website traffic, customer databases, production machinery sensors, logistics, customer surveys, call center recordings, financial transactions, and more.

What are some examples of external data sources?

External data sources can include publicly available data from governments, social media data accessed via APIs, location data from services like Google Maps, and more.

What is the role of data visualization in the analytics process?

Data visualization is crucial for understanding the context of the data. It helps make complex data more accessible and interpretable, allowing stakeholders to better understand trends and patterns.