In today’s technologically-driven society, terabytes of data are being generated every day. Businesses have information about their customers, suppliers, products, subscribers and everyone else they have interaction with. Traditionally, business intelligence has been helping firms analyze their historical data. However, tables turned when Data Analytics gave the power to predict events and suggest actions. What to do with that information, and how to mine it for trends, insights and predictors of future behavior, has increasingly become a key driver for a successful business.
Due to its potential, the past few years have witnessed a phenomenal growth in the reach of data analytics. Big data analytics is basically looking for two types of people – those who can channelize large amount of information and those who can translate business problems to analytical problems, while the ability to communicate remains intrinsic to both roles.
According to a report on Big Data from research firm McKinsey & Company, it is estimated that there will be a shortfall of approximately 200,000 analysts who have the in-depth skills necessary to interpret Big Data by 2018. Data Analytics professionals are needed across - in domains like marketing, sales, customer relationship management, operations and in all sectors research, government organizations, healthcare, services, manufacturing, airlines, ecommerce, Banking and financial services, technology or even sports
As more and more businesses and government organizations across the world are going to put their faith in data-driven decisions, a plethora of roles are emerging in this – such as Internet of Things (IoT) architect, marketing technologist, technology broker and chief data officer apart from the in demand roles like Data Scientists, Data Engineers, Big Data analysts, Data Strategist, Data Architect, Data Visualization analyst, Data quality Manager etc.
The domain of analytics is thus going to be immensely lucrative for young professionals with the right skills, aptitude and attitude. Recent Industry salary reports indicate that there is 32% increase in demand with people having Analytics qualifications over and above degrees in IT or business administration or even doctorates (2016) and data scientists earn more than CA’s & engineers. A well-trained business analyst is going to be a much sought-after professional in the foreseeable future.
Collaboration with Northwestern University & Rankings
Bridge School has an exclusive academic collaboration with Northwestern University School of Professional Studies (SPS), whose analytics program is ranked among the top five in the world by Predictiveanalyticstoday.com and Datanami.com.
The certificate program in Predictive Business Analytics has been specially created for India by academicians from Northwestern University and top industry experts. In 2015, the Predictive Business Analytics Program of BRIDGE (in collaboration with Northwestern University), has been ranked 6th nationally and 2nd in North India. (http://analyticsindiamag.com/top-10-analytics-courses-in-india-ranking-2015/)
The Bridge-Northwestern PBA program detailed below, is an enhanced version of the program that has been ranked in 2015. The improvements made have been in the area of additional courses in software packages (Advanced Excel, R, Hadoop®, SAS®) and a greater emphasis on the application of concepts in live projects. This is easily one of the most comprehensive programs in the Analytics domain in the country.
The Certificate in Predictive Business Analytics is a rigorous, part-time program. It aims to train students for a successful career in the Analytics domain, and will involve a high degree of academic rigour along with a lot of emphasis on practical application of theory and concepts
- The total program duration is 40 weeks (around 10 months), with an optional additional specialization of 8 weeks duration. This includes 36 weeks of study/participation and 4 weeks of breaks (a week’s break after each module).
- Business Communication and Soft Skills is a course that runs alongside the analytics modules. This is a compulsory course, since it prepares the student in the interpersonal and allied domains, preparing them for a successful career.
- The mode of delivery of the program is Flipped classrooms (Blended format).
- Flipped classes refers to the online + face-to-face model, where students have to study and prepare online before coming in for the weekend class.
- Face-to-face classes are held on either Saturday or Sunday.
- Assignments are part of weekly learning modules.
- A critical component of the program will be numerous workshops on Business Communications and Soft skills. This helps develop the students’ personality and groom them holistically for a corporate career, beyond just gaining technical skills.
- All courses and workshops are compulsory. They have been designed keeping in mind the requirements from a Business Analyst.
- Foundation in Statistics
Appropriate use of statistical techniques and correct interpretation of statistical findings in business analytics are vital in order to help businesses make sense of data. This course will help students in developing basic understanding of statistics and drawing inferences based on data. Specifically, students are made familiar with numerical and visual summarization of data, introductory probability, common probability distributions, sampling distribution and basic concepts of statistical inference. Discussion questions are provided with the goal of facilitating logical thinking and taking a quantitative approach towards solving business problems.
This course will also prepare the pathway for students to delve into big data and predictive analytics in the next modules of the course.
Month 2 & 3
- Introduction to Business Analytics
This course focuses on building the programming and analytics skills necessary to build analytics solutions to business problems. The course begins with a general introduction to the subject of business analytics: what it is, how does it add value in an organization and what are the characteristics of organizations which successfully use analytics to drive operations. Using that as a foundation for later thought and action, the course moves into the fundamentals of programming using the mathematical and analytics language R.
The course wraps up with application of the analytics skills to reading and understanding business cases and a review of how hypothesis testing can be applied in business situations to promote better operations and results.
Month 4 & 5
- Modeling Methods
This course serves as an introduction to statistical analysis as used in predictive modelling to support business decision making. Students will learn basic techniques in the formulation, parameterization, and selection of the right model for the right business problem. This course covers different types of analytics and a variety of statistical topics, including multiple linear regression, logistic regression, correlations and goodness of fit. Through the use of practical examples with hands-on training, discussion of the major decisions focused on making sense of data, integration of fact-based predictions into everyday decision making, the student will be exposed to a comprehensive, managerial and practical approach to predictive modelling techniques.
Month 6 & 7
- Advanced Modelling Methods
This course builds on the previous introductory material to provide a more in-depth review of modeling techniques as applied to different use cases. Emphasis will be on modeling techniques to gain insights into hidden data patterns and the ways to best represent behavior of the data for predictive analysis. Topics covered include Cluster Analysis, Neural Networks, Time Series, and various Classification Algorithms.
Month 8 & 9
- Analytics Communication and Management
This course looks at how to make business analytics an integral part of an organization’s decision-making to create a competitive edge and generate value. Topics covered include promoting analytical thinking, building consensus, and adopting smart metrics for project development, implementation, evaluation, and monitoring. Emphasis will be placed on the visual display of data and how to effectively communicate analytical, and sometimes complex, results to a mixed audience including clients, staff, non-technical leaders, and senior management. Students will have the opportunity to work with examples depicting real scenarios from different industries such as finance, healthcare, retail, government, marketing and sales. To gain experience, students will present their analysis, actionable insights, added value for the business, and gained competitive edge, all in front of an audience.
Month 10 & 11
- Advanced Specialization (Three options)
- Marketing Analytics
This course provides a comprehensive review of predictive analytics as it relates to marketing management and business strategy. The course gives students an opportunity to work with data relating to customer demographics, marketing communication and purchasing behavior. Conjoint analysis and choice studies are introduced as tools for consumer preference measurement, product design, and pricing research. The course also reviews methods for product positioning and brand equity assessment. This is a case-study- and project-based course involving extensive data analysis.
A central part of e-commerce and social network applications, Web sites represent an important platform and data source for online marketing and customer relationship management. This course provides a comprehensive review of Web analytics. It shows how to use Web sites and information on the Web to understand Internet user behavior and to guide management decision-making.
- Risk Analytics
Building upon probability theory and inferential statistics, this course provides an introduction to risk analytics. Examples from economics and finance show how to incorporate risk within regression and time series models. Monte Carlo simulation is used to demonstrate how variability in data affects uncertainty about model parameters. Additional topics include subjectivity in risk analysis, causal modeling, stochastic optimization, portfolio analysis, and risk model evaluation
- Advanced SAS Analytics
The goal of this course is to teach students SAS software at an advanced level. Students will learn how to apply SAS procedures to solve analytics problems.
- A critical component of the Blended teaching mode is the regular assignments and participation in the online discussions through the week, both of which will be graded.
- There is no exam at the end of each module, but every week there will be deliverables for continuous assessment.
- It is essential to clear each module’s requirements before moving on to the next, since each module builds upon concepts in the previous module.
The BRIDGE Edge
- Collaboration with Northwestern University, one of the top universities in the world, and their leading Analytics program. Curriculum has been designed jointly by Northwestern University faculty, using inputs from industry practitioners in the Analytics domain.
- The successful student receives a certificate jointly from Northwestern University and Bridge.
- The faculty teaching the courses comprises Analytics experts from leading organizations, bringing industry examples and perspective to the program, along with academics from both Northwestern University and Bridge School of Management.
- Comprehensive coverage of the underlying statistical concepts, modeling techniques and applicability to real-life scenarios, providing a very robust foundation for a career in Business Analytics
- Familiarity with commonly used software in Analytics such as R® and Tableau®
- Focus on building Business Communication and Soft skills, alongside the technical training, which is essential for effective working in the business world
Bridge School of Management is committed towards providing students with access to the best Analytics jobs in the country. Through its extensive ties with the industry, Bridge has an established network of organizations that it works with, all of which are exciting places for our PBA graduates to work in.
In the event that a student would like to go through the placement process at the end of the program, there are intensive interview support sessions held, to prepare the student for the job-interview process. Every attempt is made to understand a student’s aspirations and provide the student with suitable opportunities.
Bridge School gets you ready for your career transformation by providing comprehensive support like:-
- Individual career coaching
- Professional Resume Writing Team
- Business Culture training and workshops
- Interview Workshops
- Internship Preparation
- Identify the relevant opportunities/job descriptions
- Provide personal job consulting on specific opportunity
- Share employer-specific information & presentations
- Follow up & share feedback during interview cycle
* T&C Apply
The program will enable graduates of Predictive Business Analytics Program to -
- Strategically navigate business data and understand patterns therein
- Apply analytics techniques and tools to real-world business contexts for improved decision making
- Assess the strengths and limitations of analytics and predictive modeling techniques for different business applications and varying data conditions
- Acquire hands-on experience working with leading statistical tools and software packages (such as R® and SAS®) in predictive modeling and the visual analytics of results
- Effectively communicate the actionable insights stemming from analytical work to multiple stakeholders
A student will be awarded with a Certificate in Predictive Business Analytics, jointly from the Northwestern University and the Bridge School of Management. The certification will require a minimum level of academic performance and also cover areas such as attendance, discipline and adherence to school policies.
If the student chooses to also pursue a course in one of the 3 advanced specialisation courses, then he/she would also get a certificate for having successfully completed this course, in addition to the Certificate for completing the Program in Predictive Business Analytics.
Students applying for this program have to:
- Be a Graduate in any discipline, with an aptitude for numbers and quantitative techniques
- Is employed currently
There is an Entrance Exam, which assesses candidates on their quantitative and analytical aptitude. On the basis of their performance in this exam, as well as in the personal interview, students will be offered admission. Outstanding students will be offered scholarships.
Scholarship of up to Rs. 1,00,000 is available to meritorious students (selected basis performance in the selection process)
Gurgaon and Noida
Next Batch start date:
18th June 2016
Rs. 3,75,000 + applicable taxes
Weekdays: 9 AM – 5 PM
To know about the Industry faculty, Click here
1st Floor, Tower B Infinity Towers, DLF Cyber City
Gurgaon – 122001
Contact - 1800-102-4500
E-mail - Career.Advisor@bridgesom.com
B-1, Sector 2, Near Sec 15 Metro Station,
Noida – 201301
Contact - 1800-102-4500
E-mail - Career.Advisor@bridgesom.com
Students who perform well on the selection test and personal interview will qualify for scholarship.
The program has been approved by Credila (An HDFC Ltd Company) for 100% Higher Education loan assistance. Students can avail section 80-D tax benefits.
Avanse is a new age education finance company from DHFL Group which aims to provide hassle-free and 100% education finance to Indian students with customized solutions and flexible repayment plans