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Introduction to Analytics

Learn Analytics from basics in this free online training. Free Digital marketing course is taught hands-on by experts. Learn Spectrum of Analytics, Descriptive Analytics, Diagnostic, Predictive and Prescriptive Analytics in detail

Instructor:

Mr. Rounak Dholakia
4.51
average rating

Ratings

Beginner

Level

1.5 Hrs

Learning hours

48.2K+
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Learners

Skills you’ll Learn

About this Free Certificate Course

This introduction to analytics course covers the fundamentals of analytics, including Business Analytics. Business Analytics is the practice of analyzing data to make data-driven decisions in a business context. One example of this is Amazon Recommendation, where data is used to recommend products to customers. The spectrum of analytics is divided into four categories: descriptive, diagnostic, predictive, and prescriptive analytics. Descriptive analytics describes what happened in the past, while diagnostic analytics helps to identify why it happened. Predictive analytics uses data to predict what might happen in the future, and prescriptive analytics recommends actions to achieve a specific outcome.

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Course Outline

What is Business Analytics
Examples
What Constitutes Analytics
Amazon Recommendation
Spectrum of Analytics
Descriptive Analytics
Diagnostic , Predictive and Prescriptive Analytics
Data Science Vs Data Analytics

Our course instructor

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Mr. Rounak Dholakia

Academic Operations Head (PGP DSBA)

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71.8K+ Learners
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3 Courses
He currently heads the academic operations for PGP DSBA. Mr Rounak is a seasoned analytics practitioner with 10+ years of experience in providing analytical solutions to Fortune 500 clients across different industry vertical – banking, retail, CPG and pharmacy retail.

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4.51
Course Rating
69%
22%
6%
1%
2%

What our learners enjoyed the most

Ratings & Reviews of this Course

Reviewer Profile

5.0

I have been searching for courses that give insight into data analytics because I'm trying to decide what career is best for me
I found this platform after doing some research, and I can say that I will be taking more courses here to expand my knowledge. The course was easy to follow, and the instructor explained the concepts in the most basic form, which for me shows the depth of knowledge the instructor has. I'm happy I took the course and I look forward to more learning opportunities.
Reviewer Profile

5.0

Feedback about Data Analytics Course
The Data Analytics course provided an excellent overview of key data analysis concepts and techniques. It was structured in a way that catered to both beginners and those with some experience, gradually building on concepts from the basics to more advanced analytics methods. The combination of theoretical lessons with practical case studies and hands-on exercises made the course engaging and highly valuable. Strengths: Comprehensive Curriculum: The course covered a wide range of topics, from data cleaning, analysis, and interpretation to more advanced statistical methods and machine learning basics. This ensured a well-rounded understanding of data analytics. Hands-On Approach: The use of real-world datasets for projects and exercises allowed for practical application of the concepts taught. This not only helped in solidifying the theoretical knowledge but also in developing problem-solving skills. Step-by-Step Progression: The course was structured in a way that each module built on the previous one, making the learning curve manageable for students at all levels. This progression made complex topics more digestible. Variety of Tools: The course introduced various tools commonly used in the industry, such as Python, Excel, SQL, and sometimes even visualization tools like Power BI or Tableau. This exposure to multiple tools made the learning experience versatile. Supportive Learning Environment: The availability of forums, group discussions, and instructor support added to the value of the course. The feedback on assignments was constructive and helpful in improving one’s skills.
Reviewer Profile

5.0

Easy to Follow Course Module
The lessons were easy to follow, and the subject of data analytics was presented in a way I could understand.
Comprehensive and Well-Structured Course
I was able to actively follow and understand the course. The use of multimedia content made it easier to comprehend.
The Best Learning Experience I Have Ever Had
The way the materials were presented and the structure of the content were excellent.
Reviewer Profile

5.0

It is a Wonderful Experience in the Analytics World
The way the curriculum is designed is perfect. The instructor gives very clear explanations that make you understand the concepts better, which motivates the learner. The questions are well set to help understand all the learned concepts.
Reviewer Profile

5.0

An Engaging and Well-Structured Learning Experience
I thoroughly enjoyed the course as it offered a comprehensive and structured approach to analytics. The curriculum was well-designed, covering all essential topics in depth. The quizzes and assignments were challenging yet engaging, allowing me to test my understanding. The instructors explained complex concepts in a simplified manner, making the course easy to follow. Overall, it was an excellent experience that enhanced my analytical skills.
Reviewer Profile

5.0

Engaging and Comprehensive Learning Experience
I thoroughly enjoyed the course, especially the well-structured curriculum and in-depth topic coverage. The instructor was clear, and the quizzes and assignments reinforced my learning effectively. The combination of practical tools and theoretical knowledge made the content easy to follow and apply. Overall, a great learning journey!
Reviewer Profile

5.0

Clear Understanding Between Data Analyst and Data Scientist
It was easy to follow and understand. The descriptive videos really helped in better understanding.
Reviewer Profile

5.0

Engaging Learning Experience is Good
I found the curriculum to be well-structured and informative, covering the topic in depth. The instructor's explanations were clear and engaging, making the content easy to follow. I also appreciated the quizzes and assignments, which helped reinforce my understanding of the material.

Introduction to Analytics

1.5 Learning Hours . Beginner

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Introduction to Analytics

Analytics is the practice of using data to derive insights and make decisions that drive business outcomes. It can be applied to various areas of business, including marketing, operations, finance, and human resources. In this article, we will discuss different types of analytics, tools and technologies used in analytics, and the benefits of using analytics.

Analytics can be divided into several categories, including descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics. Descriptive analytics provides insights into what happened in the past, while diagnostic analytics helps identify why something happened. Predictive analytics uses historical data to predict future outcomes, and prescriptive analytics provides recommendations on what actions should be taken to achieve a particular outcome.

To perform analytics, specialized tools and technologies are needed to collect, store, analyze, and visualize data. Data management tools are used to collect, store, and manage data, while business intelligence (BI) tools are used to analyze and visualize data. Statistical analysis tools are used to analyze data using statistical methods, while machine learning tools are used to build predictive models using machine learning algorithms.

Using analytics provides several benefits to businesses. It helps improve decision-making by providing insights into business operations, increasing efficiency and productivity by identifying inefficiencies and suggesting improvements, improving customer experience by better understanding customer needs and preferences, and increasing competitiveness by providing insights into market trends and identifying areas for improvement.

In conclusion, analytics has become essential to the success of businesses in today's digital world. It allows organizations to make data-driven decisions that improve business outcomes across various areas of business. Specialized tools and technologies are required to perform analytics, and the benefits of using analytics include improved decision-making, increased efficiency and productivity, improved customer experience, and increased competitiveness.

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