This is a presentation related to the data science and business analytics.

1. Business Analytics and Data Science
“BADS”
BY-
DR. VISHAL KUMAR SINGH
Dr. Vishal Kumar Singh

2. UNIT 1
Dr. Vishal Kumar Singh

3. Data Science: Meaning
Dr. Vishal Kumar Singh

4. Data Science: Meaning
• Data Science is a combination of multiple disciplines that uses statistics,
data analysis, and machine learning to analyse data and to extract
knowledge and insights from it.
• Data Science is about data gathering, analysis and decision-making. Data
Science is about finding patterns in data, through analysis, and make future
predictions. By using Data Science, companies are able to make:
 Better decisions (should we choose A or B)
 Predictive analysis (what will happen next?)
 Pattern discoveries (find pattern, or maybe hidden information in the data)
Dr. Vishal Kumar Singh

5. Data Science: Significance
 In the healthcare industry, physicians use Data Science to analyse data from wearable
trackers to ensure their patients’ well-being and make vital decisions. Data Science also
enables hospital managers to reduce waiting time and enhance care.
 Retailers use Data Science to enhance customer experience and retention.
 Data Science is widely used in the banking and finance sectors for fraud detection and
personalized financial advice.
 Transportation providers use Data Science to enhance the transportation journeys of their
customers. For instance, Transport for specific location, city maps helps customer
journeys by offering personalized transportation details, and manages unexpected
circumstances using statistical data.
 Construction companies use Data Science for better decision making by tracking
activities, including average time for completing tasks, materials-based expenses, and
more.
Dr. Vishal Kumar Singh

6. Data Science: Application
Dr. Vishal Kumar Singh

7. Data Science: Application
 For route planning: To discover the best routes to ship
 To foresee delays for flight/ship/train etc. (through predictive analysis)
 To create promotional offers
 To find the best suited time to deliver goods
 To forecast the next years revenue for a company
 To analyse health benefit of training
 To predict who will win elections
Dr. Vishal Kumar Singh

8. Data Science: Application
Data Science can be applied in nearly every part of a business where data is
available. Examples are:
 Consumer goods
 Stock markets
 Industry
 Politics
 Logistic companies
 E-commerce
Dr. Vishal Kumar Singh

9. Data Science: Evolution
• In 1962, John Tukey wrote about the convergence of Statistics and computers to devise measurable
outputs in hours.
• In 1974, Peter Naur mentioned the term ‘Data Science’ multiple times in his review, Concise
Survey of Computer Methods.
• In 1977, the International Association for Statistical Computing (IASC) was formed to link modern
computer technology, traditional statistical methodology, and domain expertise to convert data into
knowledge. In the same year, Tukey composed a paper, Exploratory Data Analysis, that briefed the
importance of using data.
• By 1994, organizations had started gathering tremendous individual data for new showcasing
efforts.
• In 1999, Jacob Zahavi stressed the need for new devices to deal with the gigantic chunk of
organizational data.
Dr. Vishal Kumar Singh

10. Data Science: Evolution
• In 2001, William S. Cleveland presented an activity plan depicting how to create a
specialized understanding and scope of Data Scientists and indicated six regions of
studies for offices and colleges.
• In 2002, the International Council for Science published the Data Science Journal
focusing on Data Science issues like data systems explanation, application, and more.
• In 2003, Columbia University published the Data Science Journal to set a platform for
data teams.
• In the year 2005, the National Science Board published an existing collection of digital
data.
• In 2013, IBM revealed that 90% of the global data had been created in the past two years.
By this time, organizations realized the importance of Data Science to convert huge data
clusters into usable information to gain crucial insights.
Dr. Vishal Kumar Singh

11. Dr. Vishal Kumar Singh

12. Business Analytics VS Data Scientist
Dr. Vishal Kumar Singh

13. Data Science Vs Machine Learning
Dr. Vishal Kumar Singh

14. Challenges in Data driven Decision Making
Dr. Vishal Kumar Singh

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