Before I explain you all the concept of predictive modeling Let me introduce to you all the concept of business analytics. What is business analytics business analytics are techniques that we are applying on data to generate different reports and draw meaningful information and interpretations from it. It helps to mine an organization's data and discover meaningful insights from it. It helps to evaluate an entire company it helps an organization to measure performance. So business analytics are performed in order to identify weaknesses in existing processes and highlight meaningful data that will help an organization to prepare for future growth and challenges. It helps organization to face the future growth and to prepare for future growth and To face the challenges, what is data for business analytics?

These are the three terms that are associated with data for business analytics. First is what is data data is collected facts and figures. database is collection of computer files containing data and information is whatever we get after analyzing data. So these are the three terminologies associated with the data for business analytics. Now what are the differences between business intelligence and business analytics? Business Intelligence allows people at all levels of an organization to access interact with and analyze data to manage the business, improve performance, discover opportunities, and operate efficiently so business intelligence is the process comprising of technologies and strategies incorporated by the enterprise industries to analyze the existing business data, which provides past current and predictive events of the business operations.

Business Analytics is the process of technologies and strategies used to continuously exploring and to extract the insights and performance from the past business information to drive the successful future business planning business intelligence uses past and present available data to drive the present business successfully. Business Intelligence maintains, operates streamlines and increases the productivity of the ongoing businesses. Business Analytics uses past data to drive current business planning successfully. Business Analytics gathers and analyzes the data by using predictive analytics methods and provides rich visual reports to the viewers about the current business operations and its operations efficiency. Here are tabulated the differences between business analytics and business intelligence. Business Analytics analyzes past data to drive current Business, Business Intelligence analyzes past and present data to drive current business needs business analytics helps to change business operations and improve productivity.

That is it improves the productivity of the business operations helps to change the business operations and it improves the productivity business intelligence helps to run current business operations. Business Analytics are useful for future business operations. Business Intelligence are useful for current business operations. Business Analytics are applicable to companies where future growth and productivity are as good business intelligence are applicable to all large scale companies to run current business operations, business semantics contents, data warehouse Information Management etc. Business Intelligence is a part of business analytics it comes under business Netflix. Now what is data warehouse data warehouse is a storage house containing lots of data now what are the different business analytics applications first This management of customer relationships, how to manage customer relationships This can be done by estimating customer behavior by predicting the customer satisfaction using different predictive modeling techniques with different predictor variables next, financial and marketing activities under financial activity the most important activity that is done is credit risk analytics.

When we estimate whether a customer is a loan defaulter or not under marketing activities, we can do different sorts of frequency analysis where we can estimate that which of the products are bought by which of the customers which of the products are frequently bought by which of the customers like for example, which of the products are bought by high income groups customers, which are the products are bought by low income groups customers, which of the products are bought by medium income groups, customers and accordingly we can do different marketing activities next to supply chain management. Supply Chain Management and pricing decisions these both are very much linked they are part of retail analytics. So, in retail analytics that is in supply chain management in pricing decisions through the business analytics techniques we can decide which of the products are associated to each other which of the products should be kept together in a particular retail store?

What will be the placement strategies of those particular products? How do we maintain the different inventories? How do we maintain different stock different stocks of products in a particular retail store? What are the different trends of prices of products and using those trends we can also forecast the future prices and accordingly we can decide one optimum price or we can say an optimal price which is a market price. So, all these comes under retail analytics and it falls under supply chain management and pricing decisions. Next is human resource planning.

This is a part of HR analytics where we measure the attrition rate we measure the probability of retention of a particular employee and company that is whether the particular employee will retain in that company or not, what is the probability that it will retain in that particular company. All this comes under HR analytics. Next sports team game strategies. We also call it as sports analytics. That is a very important technique that we do for sports analytics that is called cluster analysis. We cluster different players based on their performance indicators.

And then we select the best cluster of players and then we use those players to play in a game or defend those players to play a particular game. So that is sports analytics. What is the importance of business analytics there is a strong relationship of business antics with profitability of businesses. revenue of businesses shareholder return business analytics enhances understanding of data. Business Analytics is vital for businesses to remain competitive. Business Analytics enables creation of informative report So, what are the different properties of measurement there are four properties of measurement first is identity, next magnitude, next equal intervals and next absolute zero.

What is identity? each value on the measurement scale has a unique mean that is the identity property of measurement. Next is magnitude. values on the measurement scale are in ordered relationship to one another that is some values are larger and some values are small, like we can say one is less than two, then two is less than three. So, this is the concept of magnitude. Next is equal intervals.

Scale units along the scale are equal to one another. This means for example, the difference between one and two should be equal to the difference between 19 and 20 and next is absolute skew to zero. The scale has a true zero point that is no values should exist below zero. What are the different scales of measurement first is nominal scale the nominal scale of measurement only satisfies the identity property of measurement values assigned to various able to represent a descriptive category, but have no inherent numeric value with respect to magnitude. So, gender is an example of variable that is measured on a nominal scale. So, nominal still generally deals with categorical variables where each value is showing some descriptive category that is, it is denoting some description here I have given an example of a gender gender has got any two types of values and the male or female male denotes male descriptive category, female denotes female descriptive category.

So this is the concept of nominal scale. Next, what is ordinal scale? The ordinal scale has the property of both identity and magnitude. each value of the ordinal scale has a unique meaning, and it has an ordered relationship to every other value of the scale. An example of an ordinal scale in action would be the result of a horse race like we can calculate the amount of time that is taken by each horse to complete a race and the horse which has taken minimum amount of time. to complete a particular race will be declared as ranked first and the horse which has taken maximum amount of time to complete a particular race will be ranked as last.

So in this way, we can say that who has won the race and who has lost the race. So that is a concept of audience scale where we can rank here we are ranking the results of a horse race, and we are ranking the horses based on the amount of time that they have taken to complete a particular race. So this is measured on audience scale. Next is interval scale, the interval scale of measurement has the properties of identity magnitude and equal intervals. A perfect example of an interval scale is the Fahrenheit scale to measure temperature, the scale is made up of equal temperature units, so that the difference between 40 and 50 degrees Fahrenheit is equal to the difference between 50 and 60 degrees Fahrenheit with an interval scale, you know, not only whether different values are bigger or smaller and smaller. You also know how Much bigger or smaller there.

So, basically the units on an interval scale are placed at equal intervals, the gaps are always equal. So, that is the concept of intervals scale. And it fulfills the three properties of measurement as I said, it is identity magnitude and equal intervals. Next to the ratio scale, the ratio scale of measurement satisfies all four properties of measurement, that is identity magnitude equal intervals and an absolute zero. The weight of an object would be an example of ratio scale. Each value on the weight scale has a unique meaning weights can be rank ordered units along the weight scale are equal to one another.

And there is absolute zero is the property of the weight scale because objects at rest can be weightless, but they cannot have negative P. Next, let me introduce to you all the different terms that are associated with business analytics first Go to them and go to them is a map that is used to analyze data in general a procedure for calculations. A list of instructions to calculate a function. In software the actual implementation of such a procedure is a programming language. Next is analytics, a set of analytics tools and computational power used to query and process platform data. Next is what is batch batch it is a job or process that runs in the background without human interaction. Next, what is big data?

Big Data is data that goes beyond the traditional limits of data along three dimensions that is valuing variety and velocity. The combination of these three dimensions needed the data more complex to ingest process and visualize then what is cloud cloud is used to refer to any computing resources software, hardware or service that is delivered as a service over a network. Then what is the data mining? data mining is the process of discovering patterns, trends and relationships from data using different Data Mining techniques or analytics techniques. So what is data mining data mining it is a process of discovering patterns, trends and relationships from data. So in this video we'll be doing till here.

Before I move to the next video, let me recap the concepts that we have covered in this video we have covered what is business analytics, what is data for business analytics, the differences between business intelligence and business analytics. What are the different business analytics applications? What are the importance of business analytics, the different properties of measurement that is identity magnitude equal intervals and absolute zero? What are the different scales of measurement, ordinal scale nominal scale, interval scale and ratio scale and we have also introduced the different terms of seeded with business analytics. In my next video I will be doing what are the main categories of business analytics for now. Goodbye, thank you see you all in the next video.