About this course
Simplilearn’s Data Analytics online course for beginners will give you insights into how to apply data and analytics principles in your business. Learning analytics, data visualization, and data science methodologies through this course will make you capable of driving better business decisions and ROI.
This Data Analytics course provides fundamental concepts of data analytics through real-world case studies and examples. You’ll learn about project life cycles, the difference between data analytics, data science, and machine learning; building an analytics framework, and using analytics tools to draw business insights.
What is Data Analytics?
Data analytics is the science of analyzing raw data in order to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.
The next essential part of data analytics is advanced analytics. The collection of big data sets is instrumental in enabling these techniques. Descriptive analytics aims to answer the question “what happened?” This often involves measuring traditional indicators such as return on investment (ROI).
The availability of machine learning techniques, massive data sets, and cheap computing power has enabled the use of these techniques in many industries. This is the process of describing historical trends in data. This part of data science takes advantage of advanced tools to extract data, make predictions, and discover trends.
What is the Role of a Data Analyst?
The primary goal of a data analyst is to increase efficiency and improve performance by discovering patterns in data. They combine these fields in order to help businesses and organizations succeed. Data analysts exist at the intersection of information technology, statistics, and business.
The work of a data analyst involves working with data throughout the data analysis pipeline. This means working with data in various ways. The primary steps in the data analytics process are data mining, data management, statistical analysis, and data presentation. The importance and balance of these steps depend on the data being used and the goal of the analysis.
The final step in most data analytics processes is data presentation. This is an essential and mandatory step that allows insights.
What you will learn from this course
- Types of data analytics
- Frequency distribution plots
- Swarm plots
- Data visualization
- Data Science methodologies
- Analytics adoption frameworks
- Trends in data analytics
Benefits from this data analytics online course
The global data analytics market is expected to expand at a CAGR of 30 percent from 2017-2023 and reach the market valuation of $77.64 billion by the end of 2023. Skilled professionals will be eligible for more than 90,000 available jobs in data analytics globally.
The Data Analytics online course contains about 7 lessons in its curriculum as follows:
Lesson 01 – Data Analytics Overview
- Data Analytics: Importance
- Digital Analytics: Impact on Accounting
- Data Analytics Overview
- Types of Data Analytics Descriptive, Analytics Diagnostic Analytics Predictive Analytics Prescriptive Analytics
- Data Analytics Benefits: Decision-making,
- Data Analytics Benefits: Cost Reduction and Data Analytics: Other Benefits
Lesson 02 – Dealing with Different Types of Data
- Terminologies in Data Analytics – Part One
- Terminologies in Data Analytics – Part Two
- Types of Data- Qualitative and Quantitative Data
- Data Levels of Measurement
- Normal Distribution of Data
- Statistical Parameters
Lesson 03 – Data Visualization for Decision making
- Understanding Data Visualization
- Commonly Used Visualizations
- Frequency Distribution Plot
- Swarm Plot
- Importance of Data Visualization
- Data Visualization Tools – Part One and Part Two
- Languages and Libraries in Data Visualization
- Dashboard Based Visualization
- BI and Visualization Trends
Lesson 04 – Data Science, Data Analytics and Machine Learning
- The Data Science Domain, Data Science, Data Analytics, and Machine Learning – Overlaps
- Data Science Demystified
Lesson 05 – Data Science Methodology
- Introduction to Data Science Methodology from Business Understanding to Analytic Approach, Requirements to Collection, Understanding to Preparation, Modeling to Evaluation and From Deployment.
Lesson 06 – Data Analytics in Different Sectors
- Introduction to Analytics for Products and Services
- You will have eyes on How tech giant industries are using Data Analytics
Lesson 07 – Analytics Framework and Latest trends
- Case Study: EY Customer Analytics Framework, Data Understanding, Data Preparation, Modeling, Model Monitoring, Latest Trends in Data Analytics, Graph Analytics, Automated Machine Learning, Open Source AI
Pre-requisites for Data Analytics online course
This Data Analytics online course for beginners has been designed for all levels, regardless of prior knowledge of analytics, statistics, or coding. Familiarity with mathematics is helpful for this course.
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- Online Course
- Less Than 24 Hours
- Paid Course (Paid certificate)
- Data Analysis Data Science Machine learning