Gain skills you need to succeed as a data analyst.
Description
Data analysis is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.
A data analyst collects, organises and studies data to provide business insight.
Data analyst applies various tools and techniques for data analysis and data visualisation (including the use of business information tools) to identify, collect and migrate data to and from a range of systems manage, clean, abstract and aggregate data alongside a range of analytical studies on that data manipulate and link different data sets summarise and present data and conclusions in the most appropriate format for users.
R is a programming language. R is often used for statistical computing and graphical presentation to analyse and visualize data. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible.
SQL (Structured Query Language) is a programming language designed for managing data in a relational database. It’s been around since the 1970s and is the most common method of accessing data in databases today. SQL has a variety of functions that allow its users to read, manipulate, and change data.
Python is a popular programming language. Python can be used on a server to create web applications and also for data analysis and visualization. Analysing data with Python is an essential skill for Data Scientists and Data Analysts .
Power BI is a cloud-based business analytics service from Microsoft that enables anyone to visualize and analyse data, with better speed and efficiency. It is a powerful as well as a flexible tool for connecting with and analysing a wide variety of data. Power BI also has a desktop version that can be used for data analysis and visualization.
Gain skills you need to succeed as a data analyst! No prior coding experience required.
Who this course is for:
- Beginner Data Analyst
- Beginner Data Scientist
