Explore Business Analytics Course
What is Business Analytics?
Business analytics (BA) refers to the skills, technologies, practices that are applied on past data and/or processes to derive insights that can be used for future business planning. It is a field that is now applied across all domains and industries. With more and more data being generated, the requirement for data scientists is estimated to be 4.4 million by the end of 2015. (Source: Gartner)
Applications of Business Analytics:
- Analytical Customer Relationship Management (CRM): BA can be applied to analyze a customer’s behavior across the customer lifecycle i.e. (acquisition, relationship growth, retention, and win-back). A lot of business analytics applications such as Direct Marketing, Cross-Sell, Customer Churn and Customer Retention are components of a well-managed Analytical CRM. Predictive analytics forms the backbone of this CRM and is applied to customer data to create a holistic interpretation of the customer after collating information across all departments and locations.
- Fraud Detection:Fraud is now a pervasive problem and can come in various forms: intentionally inaccurate credit applications, fraudulent transactions (both offline and online), identity thefts and false insurance claims, to name a few. These problems hence affect credit card issuers, insurance companies, retail merchants, manufacturers, business-to-business suppliers and even services providers. A predictive model can help an analyst distinguish specious data/transactions from other similar data and reduce exposure to fraud. For instance, the Internal Revenue Service (IRS) of the United States uses predictive analytics to mine tax returns and identify tax fraud.
- Forecasting and Inventory Management : Retailers are typically interested in predicting store-level or sector-level demand for inventory management purposes. Similarly a manufacturing firm may be interested in predicting GDP figures to analyze demand and hence level of production. Both Forecasting and Machine Learning approaches can be used to find patterns that have predictive power.
- Underwriting : Insurance providers need to accurately determine the premium charge for all assets ranging from automobiles and machinery to people. Similarly, Banks need to assess a borrower's capability to pay before agreeing to a loan. Business Analytics can analyze past data, to predict how expensive an applicant or an asset is likely to be in the future.
- Human Resource Department: Business Analytics is used by human resources (HR) departments to create a profile of their most successful employees. Details – such as universities attended or previous work experience of successful employees – can help HR focus recruiting efforts accordingly.
- Market Basket Analysis: Market Basket Analysis finds association rules within transaction-based data. It has been used to identify the purchase patterns of the High - Volume Consumer. Analyzing the data collected on this type of customer has allowed companies to predict future buying trends and forecast supply demands.
- Numerous Other Applications: Credit – Scoring Analytical Models reduced the amount of time it takes for loan approvals to a few hours rather than days or even weeks. Pricing Models can lead to optimum pricing decisions, which can help mitigate risk of default. Analytics specifically, Pattern Mining and Subject Based Data Mining has even been used to counter Terrorism.
Course Outline
| Statistical Techniques | Different types of data, Data summerization, Frequency table, Frequency Distributions,Histogram, Measures of central tendency and dispersion, Skewnesss and kurtosis, Basic Probability, Conditional Probability, Normal Distribution, Sampling methods, Point and Interval estimation, Central Limit Theorem, Nul and alternative hypothessis, Level of significance, P value, Types of errors, Hypothesis Testing |
| Predictive Analytics: Linear and Multilinear Regression | Simple and Multiple Linear Regression, R2 and Adj R2, ANOVA, Interpretation of coefficients, Dummy Variables, Residual Analysis, Outliers, Logistic Regression, Assumptions, Logistic Function, Chi-Square, Hosmer Lemeshow test, Kolmogorov-Smirnov statistic and chart, Classification Table, Interpreting Coefficients, Dependent Variable Prediction |
| Predictive Analytics: Forecasting (Time Series) | Principles of Forecasting, Time Series, Causal models, Types of Forecasting Methods and their characteristics, Moving Average, Exponential Smoothing, Trend, Seasonality, Cyclicity, Holt Winter's forecasting method. |
| Data Mining Techniques: Market Basket Analysis | Basic concepts, Frequent Itemset Mining Methods, Apriori, FPGrowth, Pattern Evaluation Methods: Lift, Chi –Square, |
| Data Mining Techniques: Classification | Classification, Decision Tree Induction, Bayes Methods, Rule-Based Classification, Model Evaluation and Selection, Ensemble Approaches |
| Data Mining Techniques: Clustering | Partitioning Methods, Hierarchical Methods, Density-Based Methods, Grid-Based Methods, Evaluation of Clustering, Kmeans Method. |
| Excel Proficiency | Formatting of Excel Sheets, Use of Excel Formula Function , Advanced Modeling Techniques, Data Filter and Sort , Charts and Graphs, Table formula and Scenario building, lookups, pivot tables |
| Application of concepts using R and SAS | Reading and writing data in R, Vectors, Frames and Subsets, Code Writing and R code Debugger, Managing and Manipulating Data in SAS, Creating Charts in SAS, Simple Linear Regression in SAS, Multiple Linear Regression in SAS, Data Mining in SAS |
| Orientation on Big Data and Hadoop | Awareness of Big Data and Hadoop, Why is it relevant? The four V’s, Is Big Data = Hadoop?, Big Data and Cloud Computing, Generators of Big Data, Applications of Big Data |
| Web Analytics and Mobile BI | Exposure to Web and Mobile Analytics with focus on: Text Analytics, Sentiment Analytics, Click Analytics, Google Analytics, Difference between Web and Mobile Analytics |
| Case Studies | Population census, Marketing, Banking, Retail, Industrial and Telecom domain case studies- Cleaning data, Mining patterns, Making models, Model selection and validation. |
| Business Analytics - NSE India (NCFM) Certification Exam | After completion of above topics students have to take the Business Analytics Certification Exam. After clearing the exam, Proschool will provide additional training (Online or Live Virtual Classroom) without any additional charges on the below topics (Maximum 3) depending upon the job requirements. |
Base SAS | • Overview, SAS statements, Comments, Data types, Data steps & Proc steps • Importing and exporting data, Data transformation and manipulation, • Formats and Informats, • Advanced data manipulation, Conversion of variables, • SAS Macro, SAS SQL, Basic SAS procedures, • Statistical analysis in SAS – Regression, Time series, Clustering and Market Basket Analysis. |
Tableau – (Data Visualization tool) | • Extracting data into Tableau, • Data Preparation, Dimensions, • Transformation of variables, • Creating Views, • Working with charts, • Exporting visualizations, • Project Work |
| Text Analytics (Application) | • Difference between Structured & Unstructured Data, • Typical use cases of Text Analytics, Sentiment analysis, • Scrapping some data from the web, • Working with a static dump of Movie review data, • Cleaning the data, Handling the NA's and Stop words, • Using the sentiment package in r, • Error handling, • Classify sentiments, Classify polarity, • Using gplot for visualization, • Building the word cloud |
| SQL | Introduction to Databases • Terminologies - Records, Fields, Tables • Introduction to database normalisation • Primary Key • How data is accessed Introduction to SQL • SQL Syntax • SQL data Types • SQL Operators • Table creation in SQL : Create, Insert, Drop , delete and updating Introduction to SQL - Table access & Manipulation • Select with Where Clause (In between, logical operators, wild cards, order, group by) • SQL constraints • Concepts of Join - Inner, Outer Case study |
| Capstone Project | Benefits of Capstone Project: • At the end of this Capstone Project, you'll be able to make sense of the given data and gain insights on how to use Analytical techniques effectively to address the business challenge. • Once you've completed the project, you'll be better able to apply analytical techniques on a business case and accordingly prepare a detailed report. • In case you don't have any relevant experience in Analytics, this project will enable you to showcase your expertise in a job interview. |
Eligibility
- On successful completion of training and assessment on SAS Base, Tableau, Text Analytics, SQL and Capstone Project, candidates will get Certificates from IMS Proschool.
- Additional Certificates & training for only those candidates who have completed the NCFM (NSE India) Certification within 6 months of Enrolment date.
About IMS Proschool
- IMS Proschool along with its Parent organization has trained more than 3 lakh candidates for different competitive exams and professional courses such as CFA, CFP, CIMA, CPA etc
- Proschool has trained more than 16,000 employees of different financial organizations such as ICICI Group, State Bank of India, Citibank, Kotak Group, etc. on Financial Analysis, Wealth Management, Financial Planning, Equity Research etc.
- IMS Proschool offers certification & training programs in Financial Modeling, Chartered Financial Analyst, Certified Financial PlannerCM, Chartered Institute of Management Accountants, Financial Services, and of course, Foundation & Business Analytics
About Proschool Training Program
- Our techniques (Regressions, Time Series, Classification, Clustering, Market Basket Analysis) cover 90% of the techniques used within the industry
- Our tools (MS – Excel, R and SAS) cover 83% of the tools used within the industry.
- Our Domains (Finance, Retail ,Telecom, Marketing, Manufacturing, Government) cover more than 80% of the domains that use Business Analytics
- Course prepared with the inputs of professionals in the academic and consulting side of Business Analytics.
- 3 months program – our course is an ideal blend of basic foundation and advanced applications.
- Real – life case studies and numerous data sets. All concepts are elucidated hands-on with data.
- Additional Certification: On completion of NSE Certification, candidates will get additional certification and training (online) on SAS Base, Tableau, Text Analytics, SQL (Only 3).
Business Analytics FAQ'S
Our course has been devised with a lot of thought with respect to the number of hours required to comprehensively understand a particular tool or technique. At the same time, we have done extensive research on the most common tools and techniques that are applied in the industry to enable “Industry-Readiness” on course completion. The experiential approach of the course blends academic content with hands-on application to ensure that students are comfortable with both.
No, the course has been designed so that all participants can build their knowledge from basic concepts to advanced applications. For example, Linear Regression starts with the concept of mean and variation followed by correlation. Regression is then explained via Correlation followed by Interpretation of Regression results. Any knowledge of Math and Statistics will be helpful to the participants. Also comfort with data and its various formats will be an added bonus.
IT or programming deals with processes. Business Analytics deals with data. As a part of a programming team you will try and automate processes. A lot of these automated processes now generate huge amounts of data. This data is now the focus of Business Analytics. BA gains insights from these data to get an edge. A lot of IT processes such as Project Management are getting automated so demand in the sector is going to stagnate in the long run. At the same time, data is increasing exponentially, consider this: From the beginning of recorded time until 2003, the world had created 5 Exabytes of data. In 2011, the same amount was created in 2 days. In 2013, the world produced the same amount of data was created in just 10 minutes. Hence demand for BA professionals will continue to increase. An estimated 4.4 million BA professionals will be required by the end of 2015.
Most of Consulting involves Analysis of Data to drive future business
plans and strategy. Business Analytics will clearly give you an edge in
your analytical and data handling capabilities.
If you are pursuing an MBA and want to make a career in Analytics,
Consulting, Finance or Marketing then BA will be helpful to you. This
course will make you comfortable with data and data analysis along with
popular analytical tools such as MS-Excel, R and SAS. It will give you
the desired exposure to various domains thus creating a well-balanced
outlook on data usage. Lastly, it will also help you to improve your
profile vis-à-vis other candidates of your institute.
Typically engineers are already conversant with basic IT tools and data
structures. As an engineer you can exploit this advantage and bolster it
with techniques and domain knowledge from our course. If you are
interested in a career in Analytics or Market Research or Finance then
data analysis can only be handy.
A lot of IT professionals find BA more exciting. Along with this the
demand for BA professionals is growing whereas the demand for IT
professionals is stagnating. Business Analytics hence may be a good
career shift for you. Also familiarity with IT leads to a better
understanding of data leading to improved data analysis.
Certification Process
1. Join IMS Proschool for the Business Analytics Program
2. Complete training of the Business Analytics program through any mode viz Classroom/ Virtual Classroom/ Distance Learning
3. Complete internal quizzes and assignments.
4. Fill the exam form on the Proschool website with NCFM ID. If you don’t have an NCFM ID, you can visit www.nseindia.com : - Education : - Online Register/Enroll
5. Once you get a confirmation email from Proschool, select the exam date ( All days & venues in 85+ centers)
6. Take the exam at NSE India or NSEIT Centers.
About the NSE India Certification Exam
1. The Certification Examination will be conducted at 85 NSE Centers.
2. The exams are conducted on a daily basis.
3. The examination is a computer based test and will comprise multiple-choice questions.
4. Exam will be out of 100 marks (66 questions) and duration of the exam is 2 hrs.
5. The students will receive their scores immediately after the exam.
6. Exam Grades: 50% to 59%: C Grade, 60% to 74% B grade, 75% or above 75 % A Grade. No negative marking.
7. Those who fail the examination can reappear for the exam by paying the exam fee of Rs.1700 + GST. There is no limit on the number of attempts.
8. Certification from NSE India is valid for lifetime.
Business Analytics Video
Awesome video interview with an expert on Business Analytics.