Week 1 - Understanding the data ecosystem

How data informs better decision

1. Data-driven decision making

An airline collects, observes, and analyzes its customers' online behaviors. Then, it uses the insights gained para elegir what new products and services to offer. What negocio process does this describe?

Data-driven decision-making

Data + business knowledge = mystery solved

A lot of times, it will depend on the goals of your analysis. That is why analysts often ask, "How do I define success for this pro

Project-based data analytics life cycle

A project-based data analytics life cycle has five simple steps: Identifying the problem Designing data requirements Pre-processing data Performing data analysis Visualizing data This data analytics project life cycle was developed by Vignesh Prajapati. It doesn't include the sixth phase, or what we have been referring to as the Act phase.

Which of the following terms refers to the collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making?

Data analysis

In data analytics, what is the term for elements that interact with one another in order to produce, manage, store, organize, analyze, and share data

Data ecosystem

Which of the following statements best defines data?

Data is a collection of facts.

What is the differnece between Data Scientist to Data Analyist

Data science - Creates a new ways of modeling and understanding the unknown by using raw data. Data scientists create new questions using data, while analysts find answers to existing questions by creating insights from data sources.

Fill in the blank: In data analytics, the data ecosystem refers to the various elements that interact with one another to produce, manage, store, _____, analyze, and share data.

orgainze

SAS's iterative life cycle

An iterative life cycle was created by a company called SAS, a leading data analytics solutions provider. It can be used to produce repeatable, reliable, and predictive results: Ask Prepare Explore Model Implement Act Evaluate The SAS model emphasizes the cyclical nature of their model by visualizing it as an infinity symbol. Their life cycle has seven steps, many of which we have seen in the other models, like Ask, Prepare, Model, and Act. But this life cycle is also a little different; it includes a step after the act phase designed to help analysts evaluate their solutions and potentially return to the ask phase again.

Example- Agricultural companies

Information including geological patterns in weather movements. Data analysts can use this data to help farmers predict crop yields.

Identify the real-world examples of how a company might make data-driven decisions.

Scheduling a certain number of restaurant employees to work based on the average number of lunch-goers per day Choosing e-commerce solutions based on customer shopping preferences

Where is the data ecosystem stores important information and a MUST HAVE as anaylist

The Cloud

Data-driven decision making

The process of using facts to guide business strategy

asking yourself these questions about a project to help find the perfect balance:

What kind of results are needed? Who will be informed? Am I answering the question being asked? How quickly does a decision need to be made

Analysts use data-driven decision-making and follow a step-by-step process.

You have learned that there are six steps to this process: Ask questions and define the problem. Prepare data by collecting and storing the information. Process data by cleaning and checking the information. Analyze data to find patterns, relationships, and trends. Share data with your audience. Act on the data and use the analysis resul

Example -Store Retail database

which is an ecosystem filled with customer names, addresses, previous purchases, and customer reviews. As a data analyst, you could use this information to predict what these customers will buy in the future, and make sure the store has the products and stock when they're needed