This is a tutorial about Business Analytics Foundation With R Tools offered by Simplilearn. The tutorial is part of the Data Science with R Language Certification Training course and will help understand the basics of data science and business analytics with types and learn its importance.
This business analytics foundation tutorial comprises of four lessons. After completing the business Analytics Foundation With R Tools tutorial, you will be able to:
Understand what analytics is, where it is applied, its types, the tools and the process involved in it.
Get an overview of the various topics that will be covered in different lessons.
Describe the Career Path of a business analyst.
In the next section, we will look at what analytics is.
Analytics is a journey that involves a combination of potential skills, advanced technologies, applications, and processes used by a firm to gain business insights from data and statistics. This is done to perform business planning.
In the analytics process, data is collected from various external sources and is stored in a data warehouse. After this data collection, the process of analytics begins. Here, a more in-depth learning of the data is done to derive possible insights from data. In addition to this, all advanced data-driven capabilities are developed, which in turn provides additional value to the business.
In the next section, we will look at the places where analytics is applied.
Some of the common fields where analytics is implemented are as follows,
In this field, analytics is used for credit scoring, fraud detection, pricing and claims analysis.
In Retail, it is used for promotions, replenishment, demand forecasting, and merchandising optimization.
In Healthcare, it is used for drug interaction, preliminary diagnosis and disease management.
Customer retention, capacity planning, and network optimization are the primary applications in the field of Communications.
Trading, supply, demand forecasting, and compliance are the areas of application in Energy.
In Manufacturing, it is used for inventory replenishment, product customization, and supply chain optimization.
The use of Analytics has evolved over time and the advent of Big Data has made analytics one of the most sought-after skills in the industry across domains. This tutorial will help you take the first step toward understanding analytics and the way it interfaces with the industry.
The tutorial will also help you to start thinking like a business analyst. Career-wise, you can aspire to be a data manager, data miner, or a business manager. The work of data manager involves:
Data preparation
Deployment services
Report administration
The work of a data miner involves:
Exploratory analysis
Descriptive segmentation
Predictive modeling
The work of a business manager involves:
Campaign management
Domain expertise
Process and ROI evaluation
In the next section, we will look at the topics that are covered in the first and second lessons.
There are four lessons covered in r tutorial. The lesson names and their brief descriptions are listed below.
Lesson no. |
Chapter name |
What you will learn |
Lesson 1 |
Introduction to Analytics. |
|
Lesson 2 |
Statistical Concepts And Their Application In Business Tutorial. |
|
Lesson 3 |
Basic Analytic Techniques - Using R Tutorial. |
|
Lesson 4
|
Predictive modelling techniques |
|
In the next section, we will look at the career path of a business analyst.
With this, we come to an end about the Business Analytics foundation with R tool tutorial. In the next chapter, we will discuss the Introduction to Analytics.
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