Skip to main content

BUSINESS ANALYTICS AND ITS APPLICATIONS

WHAT IS BUSINESS ANALYTICS? 
Business analytics is the combination of computer science programming, data analytics, and data science. Business analytics is based on data science technology. Business analytics is a technique that is used for making effective business strategies. This technique is being used in every sector of the industry nowadays. The companies determine the hidden patterns and useful information from a huge quantity of data. It is pronounced by the Interactive Data Corporation that, the generation of the data is expected to reach 163 Zettabytes till the year 2025.
PROCESS OF BUSINESS ANALYTICS 
Here is a brief discussion of the process of the business analytics technique. The implementation of this technique by the companies is discussed below. 
  1. Framing of the business problem 
Framing the problem is the most important part of our strategy. It is not only important in business analytics, but in every field as well. You should be aware about your problem which you are looking for a solution so that the companies determine which problem they are facing in this stage.
  1. Framing analytics problem
In this part, the companies think about how the problem can be solved with the help of data analytics. A discussion about the type of analysis is held to solve the problem. This stage is known as the success model of the strategy.
  1. Data 
The next step is dealing with data. After the companies decided how to solve the problem, they collect or select the data which would be suitable for the data analysis. In this step, the data is collected, cleaned, etc. The data is completely got ready for the analysis.
  1. Model building and methodology selection 
Once the data is ready for the analysis, then the companies go for applying the methods. In business analytics, different methods are used for the analysis. They decide about the methodology according to their data. Moreover, the models are also examined and based on the type of analysis as well as the data type collected by the company.
  1. Deployment 
The company deploys its product in the final stage. The outcome is controlled to see if the product is in desired mode or not. Once the product is verified, then it is deployed over the company's system.
TYPES OF ANALYTICS 
The following types of analyses are performed on the data by the business analytics techniques. They are listed below.
  • Predictive analysis
  • Prescriptive analysis
  • Descriptive analysis
APPLICATIONS OF BUSINESS ANALYTICS 
Here are the different applications of the business analytics technique in different sectors of the industry. From these applications, you can understand how useful the business analytics technique is at the present time. They are listed below. 
  • Gaming 
  • Fraud detection 
  • Speech recognition 
  • Image recognition 
  • Recommender system 
  • Price comparison 
CONCLUSION 
The applications of business analytics take place in everywhere in the industry. This shows that this technique is becoming important in the industry. Students can choose this field as their career option. Interested students can join different courses in business analytics.

To know more info on business analytics course

To know more info on data analytics courses

To know more info on data science interview questions

To know more info on data science course in Mumbai

For more info :

ExcelR - Data Science, Data Analytics, Business Analytics Course Training in Mumbai

304, 3rd Floor, Pratibha Building. Three Petrol pump, Opposite Manas Tower, LBS Rd, Pakhdi, Thane West, Thane, Maharashtra 400602
09108238354 

Comments

  1. Data analytics advances and procedures are generally utilized in business ventures to empower associations to settle on progressively. Thank you for sharing such an informative blog with us. I would like to suggest,
    to check the website best data science course from best data science institute in bangalore, Learnbay.co. Check Learnbay.co website.

    ReplyDelete

Post a Comment

Popular posts from this blog

Understanding Logistic Regression using R

  1. What is Logistic Regression? Logistic Regression is one of the machine learning algorithms used for solving classification problems. It is used to estimate probability whether an instance belongs to a class or not. If the estimated probability is greater than threshold, then the model predicts that the instance belongs to that class, or else it predicts that it does not belong to the class as shown in fig 1. This makes it a binary classifier. Logistic regression is used where the value of the dependent variable is 0/1, true/false or yes/no. Example 1 Suppose we are interested to know whether a candidate will pass the entrance exam. The result of the candidate depends upon his attendance in the class, teacher-student ratio, knowledge of the teacher and interest of the student in the subject are all independent variables and result is dependent variable. The value of the result will be yes or no. So, it is a binary classification problem. Practical Implementation of Logistic Regres

Data science: A Blend of These Data Components

Data Science Course ExcelR offers Data Science course, the most comprehensive Data Science course in the market, covering the complete Data Science lifecycle concepts from Data Collection, Data Extraction, Data Cleansing, Data Exploration, Data Transformation, Feature Engineering, Data Integration, Data Mining, building Prediction models, Data Visualization and deploying the solution to the customer. Skills and tools ranging from  Statistical Analysis , Text Mining, Regression Modelling, Hypothesis Testing, Predictive Analytics,  Machine Learning ,   Deep Learning, Neural Networks, Natural Language Processing, Predictive Modelling, R Studio, XLMiner,  Tableau , Spark, Hadoop, Minitab, programming languages like R programming ,  Python are covered extensively as part of this Data Science training. ExcelR is considered as the best Data Science training institute which offers services from training to placement as part of the Data Science training program with over 400+ participant

Knowledge Science, Enterprise Analytics Programs

Increase your analytics career with highly effective new Microsoft® Excel abilities by taking this Business Analytics with Excel course, which includes Energy BI coaching. Information Science is a area which is consistently evolving and constantly making manner for brand new technologies to be picked up. Many firms and professionals are mastered to stay ahead within the competition. Course Content (Score 4.5): The core course contains Statistics and likelihood, R and Python for Information Science, Hadoop, big information with Apache Spark, machine studying for information science, IBM Watson analytics, enterprise use instances of big information and data science and much more. College students had been enlightened by his profound information and business experience on Digital Advertising. This Big Information provides problem in term of storage and further analysis in rest of in real time. Information science is a combination of statistics, mathematics, computers, algorithms and a