Data Science

Types of Analytics Overview Data analysts solve various problems for businesses of different types depending on what the business needs. Some of the most common types of analytical analysis are: Descriptive Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics Generally speaking, it is harder to gain insights on future and it is also harder to understand how or why those events would happen. For that reason, the types of analytics are ordered from the easiest to the hardest based on the type of insights the analysis type is trying to find....

Key Skills: Data Analysis Phases of the Data Analytics Lifecycle Analytical Tools Master various analytical tools for data gathering, cleaning and visualization Analytical Methods Identify and implement data analysis methods Data Analytics Lifecycle: Business Understanding (Discovery) Data Acquisition (Collection) Data Cleaning (Preparation) Data Exploration (Exploratory Data Analysis) Predictive Modeling (Data Modeling) Data Mining (Machine Learning) Data Reporting & Visualization (Representation & Communication) Tools: Python R SQL Tableau Methods: Machine learning algorithms Statistical analysis techniques

This will be a deeper dive into the different phases of the data analytics lifecycle and serves as a continuation for the Data Analytics Lifecycle Overview. Data Analytics Lifecycle Overview Stages of the Data Analytics Lifecycle Business Understanding (Discovery) Data Acquisition (Collection) Data Cleaning (Preparation) Data Exploration (Exploratory Data Analysis) Predictive Modeling (Data Modeling) Data Mining (Machine Learning) Data Reporting & Visualization (Representation & Communication) Business Understanding This phases involves gaining a business understanding of the problem or mission objective....

Data Analytics Lifecycle The data analytics lifecycle consist of the entire process from understanding the business problem and objectives to the communication and visualization of the data and analysis. Upon gaining a business understanding of the objective after collaborating with stakeholders, data analyst will then begin collecting and gathering data from various sources that will undergo cleaning and preprocessing steps to address errors, inconsistencies, and missing values ensuring the data is of great quality....