PGP BABI provided me an extra edge in the fiercely competitive market- Neeraj Khare, Wipro Technologies

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With the ever changing market demands, there is a need to upskill your knowledge and be able to meet these demands as and when required. Neeraj Khare was able to achieve this and successfully reach greater heights in his career with the help of our PGP BABI course. He extends his gratitude and appreciation towards the team. 

How did PGP BABI helped you achieve career transition? 

I would like to thank the Great Learning team and the entire team of PGP BABI as I have been successful in jumping up the ladder in corporate solely because of this course. It provided me with an extra edge in the fiercely competitive market. I got into Wipro Technologies with a hike of around 50 percent. This was possible because the course helped show-case my ability to learn new technologies and acquire the hot skill of Data Analytics. The recruiter was very impressed with the course projects and the interview, as it revolved around analytics, much like the new set of work that consulting companies are doing today. Hence, I received an opportunity to sail through, all thanks to the PGP BABI course. 

 Whom do you give credit for your success?

I am particularly grateful to Ms. Devansha Sehgal who has been a great Program Manager. She is extremely good at Program Management as well as People Management and has shown constant support. Since this course is for working professionals and is not easy to complete without help from the course faculty and Program Manager, it would not have been possible without her support. Devansha has outstanding abilities to handle the program. She has constantly pitched in and used to follow-up on my program completion status. She is really helping the working professionals and I appreciate her work. I would like to give the credit of my success to her.

 Upskill with Great Learning’s PGP BABI Course and unlock your dream career. 

 

Your Weekly Guide to Data Science and Analytics – October Part III

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Data Science has a diverse set of applications and has emerged as one of the leading career paths in the recent times. The scope of data science has greatly increased and various new courses are now available in the market. Events focused on data science and analytics are taking place all over the globe and new features are being released as well. If you wish to keep up with the developments, here are some articles that will take you through recent advancements in data science and analytics. 

MB, OPM and agencies partner to create data scientist occupational series

At the ATC IAC’s Executive Leadership conference in Philadelphia, deputy federal CIO Margie Graves said that the Office of Management and Budget is working with a number of partners across the federal government to figure out how to hire more data scientists. She talks about how she envisions a government in which “every step in the executive chain” is data-literate. 

OmniSci Announces Version 5.0, Featuring New Capabilities for Accelerated Analytics and Data Science at Massive Scale

OmniSci platform is used in business and government to find insights in data that are beyond the limits of mainstream analytics tools. At Converge 2019, OmniSci announced version 5.0 which is a major step in making analytics instant, powerful and effortless. One of the key features of the new version includes an integrated Data Catalog which has the ability to import external public or partner data sets and visually join them in geospatial.

TOP 12 BIG DATA, ANALYTICS AND DATA SCIENCE INFLUENCERS OF 2019

The development in Data Science and Analytics influences different aspects like education, environment, transportation, etc. Data Science and Analytics experts are the ones who drive this development and keep the industry up-to-date. Here is a list of some of the influencers who have been highly recognized for their work. Kirk Borne, Bernard Marr, Marcus Borba are some names amongst the 12 greatest influencers of 2019. 

Second colloquium on analytics, data science, computing set to attract hundreds to MNSU’s Edina location

Minnesota State University is set to host a colloquium on analytics, data science and computing on 26 October, 2019. The event will feature keynote presentations by computer science author and consultant Chuck Easttom and Georgia Koutrike who is a Ph.D., computer scientist, software developer and inventor. The event is also said to feature industry faculty panels and peer reviewed papers on over 25 topics. The colloquium is not free to the public, but industry professionals can attend by paying a fee. 

Data Science Course will provide a major boost to tackle the shortage of Data Scientists in India

Indian Institute of Technology Madras is planning to double the seats for Interdisciplinary Dual Degree Data Science due to its high demand in the industry. It will provide students with a strong foundation for their parent disciplines as well as additional benefit of learning Data Science skills. The goal of the program is to provide a basic understanding of data science and its applications so they have ample opportunities in the future. 

Data scientists will lead the digital age

A study published by McKinsey Analytics in January 2018, titled Analytics Comes of Age, found that nearly half of the respondents believed that analytics and big data have fundamentally changed business practices. Glassdoor and LinkedIn have named “Data Scientist” as the best job in 2019, with a base salary of USD 108,000. This is just the beginning of the data science era.

For more digests on Data Science, watch this space

 

 

 

AWS solution to build Real-time Data processing Application using Kinesis, Lambda, DynamoDB, S3

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A Capstone Project by Amit Bajaj and Sathya Guruprasad

Introduction

Cloud Computing has become very popular due to the multiple benefits it provides and is being adopted by businesses worldwide. Flexibility to scale up or down as per the business needs, faster and efficient disaster recovery, subscription-based models which reduce the high cost of hardware, and flexible working for employees are some of the benefits of cloud that attracts businesses. Similar to cloud, Data Analytics is another crucial area which businesses are exploring for their growth. With the exponential rise in the amount of data available on the internet is a result of the boom in the usage of social media, mobile apps, IoT devices, sensors and so on. It has become imperative for the organisations to analyse this data to get insights into their businesses and take appropriate action.

AWS provides a reliable platform for solving complex problems where cost-effective infrastructure can be built with great ease at low cost. AWS provides a wide range of managed services, including computing, storage, networking, database, analytics, application services and many more. 

Problem Statement:

We have analysed multiple software solutions which perform analysis on data collected from the market and provide information as well as suggestions and provide better customer experience. This includes trade application providing stock price, taxi companies providing locations of nearby taxis, journey plan applications providing live updates on the different transport media and many more.

We have considered a “server-less” platform / “Server-less Computing Execution Model” to build the real-time data-processing app. Architecture is based on managed services provided by AWS.

What is “Server-less”?

A cloud-based execution model in which the cloud provider dynamically allocates and runs the server. This is a consumption-based model where pricing is directly proportional to consumer use. AWS takes complete ownership of operational responsibilities eliminating infrastructure management and availability with higher uptime. 

Services Consumed:

  1. Kinesis – Kinesis Data Stream- Kinesis Data Analytics- Kinesis Firehose
  2. Athena
  3. Lambda
  4. Dynamo DB
  5. Amazon S3
  6. AWS CLI

Architecture:

AWS solution to build Real-time Data processing Application - cloud computing

Without building a sizable infrastructure, how to receive data from different sources for cloud-based infrastructure?

Kinesis, a managed service by AWS, Amazon Kinesis makes it easy to collect, process, and analyse real-time, streaming data so you can get timely insights and react quickly to new information. Kinesis Datastream allows user to receive data from data generation source. We have created amazon kinesis data stream using AWS CLI commands which is expected to consume data from the data source.

Technical + Functional Flow 

Create Kinesis data streams: 

      1. Create a stream in Kinesis using AWS Console or AWS CLI Commands; one to receive data from Data generator and another to write post processing. Data generator will produce the data which will be read and written to input/source data stream. Kinesis Analytics App will process and write data to Output/destination stream.
      2. We have created a program to generate data, and with the help of AWS SDKs and AWS CLI commands transmitted to Kinesis Data Streams. Data can be generated in various fashion:
        1. Using IoT devices
        2. Live trackers
        3. GPS trackers
        4. API
        5. Data generator tools (in case of Analysis)

Create a Kinesis Analytics App to Aggregate data

      1. Build a Kinesis Data Analytics application to read from the input/source data stream and write to output/destination data stream in formatted fashion in a specified time interval.
      2. It is very important to stop the application when not in use to save unwanted cost.

Data Storage and Processing:

      1. Lambda, another managed service by AWS processes data from trigger data stream and write to dynamo DB
      2. Lambda function works on trigger basis and cost model is strictly driven by consumption. No cost is incurred from user when function is not running. Data is stored in Dynamo DB and can be accessed in standard fashion.

Kinesis Firehose, S3 and Athena:

    1. Kinesis Firehose acts as mediator between Kinesis Datastream and S3 where Data received from Kinesis Datastream will be predefined S3 bucket in specified format
    2. Amazon Athena is server-less interactive query service which enables user to glorify data stored in S3 Bucket for analysis. 

Amazon CLI, AWS Cloud formation and AWS IAM also plays a very important role in building Cloud based infrastructure and ensure secure connectivity within and outside AWS cloud world. 

Conclusion:

Using AWS services, we were able to create a real-time data processing application based on serverless architecture which is capable of accepting data through Kinesis data streams, processing through Kinesis Data Analytics, triggering Lambda Function and storing in DynamoDB. The architecture can be reused for multiple data types from various data sources and formats with minor modifications. We have used all the managed services provided by AWS which led to zero infrastructure management efforts. 

Capstone project has helped us in building practical expertise on AWS services like Kinesis, Lambda, Dynamo DB, Athena, S3, Identity and Access Management, Serverless Architecture and Managed Services. We have also learnt the Go programming language to build pseudo data producer programs. AWS CLI has helped us to connect on-premise infrastructure with cloud services.  

This project is a part of Great Learning’s post graduate program in Cloud Computing. 

Authors
Amit Bajaj – Project Manager at Cognizant
Sathya Guruprasad – Infrastructure Specialist at IBM Pvt Ltd

Your weekly Guide to Data Science and Analytics – September Part I- GL

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Data Science and Analytics are being applied across industries, varying in their scope and magnitude based on the purpose of the application. Even as we witness these technologies solving bigger problems, there are still some challenges faced while building these solutions. We explore some of those challenges in this week’s digest.  

SEBI Bets on Data Analytics, New Generation Tech to Address Market Challenges

Continuing its efforts to bolster supervision and identify non-compliance, regulator Sebi plans to deploy data analytics and new generation technologies to deal with various challenges in the market. Technology solutions are being built to achieve the objective of identifying non-compliance and assisting in investigations.

Figleaves Deploys AVORA Augmented Analytics for Granular Insights and Reporting

AVORA provides an end-to-end augmented analytics platform, utilising Machine Learning with smart altering to deliver easy to use, in-depth data analysis. By eliminating the limitations of existing analytics, reducing data preparation and discovery time by 50-80%, and accelerating time to insight to just a matter of seconds rather than days, AVORA creates game-changing organizational intelligence.

New Tools of Data Science Used to Capture Single Molecules in Action

Single-molecule fluorescence techniques have revolutionized our understanding of the dynamics of many critical molecular processes, but signals are inherently noisy and experiments require long acquisition times. This work leverages new tools from data science in order to make every photon detected count and refine our picture of molecular motion.

Challenges in Analytics Sector: The Industry Perspective

Analytics industry has witnessed significant growth over the years but is still prone to a lot of challenges in terms of talent, reaching the right consumers, cumulating data points, among others. 3 Key Challenges That Analytics Industry Still Faces Today are: 

Translating data to business impact | Multiple sources of data | Data quality

To read more about Data Science, Analytics, and their career prospects, check this space. Upskill in Data Science domain with Great Learning’s PG program in Data Science and Engineering.

Keep Calm and Let the Business Analyst Handle it

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A Day in the Life of a Business Analyst

Business Analytics has emerged as a much sought after skill set. Professionals with business analytics expertise can work in different analytical profiles in companies to help them grow – but what exactly do they do? This article breaks down the essentials of a BA profile by looking into a typical day in the life of a business analyst. 

Equipped with strong analytical skills and a sound knowledge of the market, business analysts take care of a range of tasks to help companies meet their business goals. While collecting and interpreting data is core to a business analytics profile, stakeholder communication, meeting management and report collating are equally important. Aspiring business analytics professionals can refer to this detailed account of a day in an analyst’s life to understand the requirements and set their expectations. 

For a business analyst, a typical day starts by pinning up tasks on a storyboard to plan and prioritise them. As with most other roles, business analysts also have team meetings to discuss pain-points, pending tasks, obstacles and priorities. After having the tasks planned out, the workflow looks somewhat like this:

Prioritization & Business Context: Analysts typically like to plan their day and week meticulously in advance. Iteration planning meetings (IPM) are an excellent way to interact with the whole team and stay updated on all the ongoing projects. This iterative method ensures that objectives and plans are clearly explained. IPM also helps the team to understand the business context of any particular project and prioritize accordingly.  

Investigate Goals and Issues: An important part of an analysts job is to identify the problem. Research, interviews, analytical observations are few of the ways in which analysts investigate the situation to recognise the issues. Analysts look at past data, and try to make projections based on inferences.

Analysing Information:  It is after collecting data points concerning the issue at hand, that analysts finally get down to the analysing part. Data sets are thoroughly examined for recurring patterns and anomalies. Analytic reports are then shared internally for teams to understand the problem areas. These reports break down series of data sets into comprehensible explanations so that they are easily interpreted by the leadership team to help them arrive at business decisions unanimously.

Documenting Information: It is important to record all the analytical findings since they can act as future reference points. Analysts spend a considerable part of their day collecting and documenting all the analytical results, inferences and new developments. Considering documentation techniques are specific for each report, analysts also spend time looking into different documentation methods to choose the best option for any given report. 

Backlog Grooming:  This is an ongoing task for analysts- analysing and distributing the backlog. Resource optimization is crucial for any business and analysts aid that by efficient backlog management. Analysts go through the task lists and plan resource allocation according to priority.

Meetings and Communication: A major part of an analyst’s day is spent in active communication- internally with the team or externally with stakeholders. Business communication is not limited to just speaking, but it also means non-verbal communication in the form of emails and presentations to make sure that information is properly relayed, agreed to and acted upon.

Client Interaction: Client feedback is an integral part of any business plan. The best way to ensure that you are proceeding in the right direct and your business goals are met is by getting direct feedback from the clients. Feedback sessions can be used to evaluate the progress of the projects and analyse its success. Incorporating feedback in the project proceedings will lead to more satisfactory results and improve project success rates.

Business analysts act as a bridge between problems and solutions, trying to understand the former and planing the latter. However, a business analyst needs to work closely with the development teams, operations teams and the service teams to make any business project successful. A typical day in a business analyst’s life involves different kinds of tasks like extensive communication, reporting and documentation. While knowledge of analytical tools is an absolute necessity for an analyst, interpersonal communication skills coupled with strong business acumen is also required to deliver results.

Developing industry-relevant skills through Experiential Learning

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At Great Learning, we believe in imparting a holistic education experience through exposure to real-world problems, and a mentor-driven approach to solving them. We strive to provide a great learning experience to build capabilities that are driven by an efficient mix of theoretical sessions and practical ‘learn by doing’ approach. 

As a testimony to our philosophy of education, the ‘Cricket World Cup Challenge’, and ‘Hack of All Trades’ are an integral part of our learning journey, organized for Great Learners across programs. Here’s how these initiatives help our learners achieve career success:

The Cricket World-Cup Challenge

Overview:

The Great Learners were required to form a team of 2 with someone who is not a Great Learning program participant. The teams had to predict outcomes of each match, based on which they were assigned scores. Finally, using machine learning models, they had to predict the finals and submit a report on the same. 

Here’s a snapshot of the event in numbers:

Engagement statistics for the Cricket World Cup Challenge

 

Based on the match outcome predictions, a leader board was posted on Social Media each Monday.

Cricket World Cup Challenge Experiential Learning

Special sessions were conducted with Mr Gaurav Sundaraman, Data Scientist at ESPNCricinfo, on Cricket Analytics

After 50 days of altering leaderboard dynamics, we finally got our winners:

Cricket World Cup Challenge Experiential Learning

Here’s what the participants had to say about this initiative:

– Thanks for the innovative exercise. It created a lot of interest in the games as well as finding stats to predict the winner.

– It was a thrilling competition.

– Congratulations on the event being a success, and thanks for organizing.

– I would like to see more such competition based on some social impact data. That would help us understand our social environment. Thanks.

– All the instructions and scoring system were very transparent. Keep rocking team very good job. Looking forward to more such initiatives.

– This gave us a lot of learning and exposure.

 

Hack of all Trades 

The initiative was run exclusively for the online batches of the Business Analytics and Business Intelligence PG program, for both Indian and International participants. It was a 3-day online Hackathon where the participants had to predict the annual turnover of the restaurants across India based on the restaurant details, aggregated rating from social media, and customer survey data.

A state of the art Hackathon platform was devised with integrated leaderboard, customized view for each user with login credentials, FAQs and rewards on the same page.

hack of all trades experiential learning

 

There were 4 different rewards to raise the fun quotient of the experience

Hack of all Trades - Experiential Learning

Here’s what the participants had to say about this initiative:

– Thank you for the opportunity to showcase our talent to the world!

– Thrilling!

– It was a fantastic event and will look forward to more.

– Good initiative to check one’s skillset.

– Good practical experience.

 

Hack of all trades experiential learning* Social Media Mentions

 

When we talk about active engagement and learning through digging solutions to practical real-life challenges, this is just the tip of an ice-berg. At Great Learning, we put immense thought and effort in pushing such initiatives across programs and derive meaningful learning outcomes through them.

Such projects and hackathons have been the core of the teaching methodology at Great Learning and will continue to be so. The purpose is to nurture students to become job-ready professionals who are capable of acing interviews in their respective domains and areas of interest. These methods are replicated across courses to give a similar experience to students and professionals enrolling for any given program.

 

 

Best Data Science and Business Analytics courses for Professionals

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The term analytics and data science have garnered a lofty prominence in the past decade mostly used interchangeably. As it stands strong today, business analytics is finding applications across functions ranging from marketing, customer relationship management, financial management, supply chain management, pricing and sales, and human resource management among others. It has also made a place for itself across industries, spanning its wings even to the most traditional ones such as Manufacturing and Pharma. 

A bachelor’s degree with a minimum of 2-3 years of work experience is mandatory to enrol for almost all business analytics or data science programs out there. It holds a great career scope for graduates in the field of engineering, business management, marketing, computer science and information technology, finance, economics, and statistics among others. 

All things said and done, there are certain challenges that professionals might face while looking out for the perfect business analytics or data science course to steer their career on the growth path:

– Lack of time and issues with balancing work and course schedules

– Financial Barriers

– Inflexibility in the course structure

– Obsolete curriculum or irrelevant modules

– Inaccessibility to the course

An institution or a course that focuses on combating these challenges and provide a comfortable, valuable, and manageable learning experience is the ideal course for professionals. At Great Learning, we strive to focus on these issues and design courses to suit the needs and resources of the aspirants.

Here is a comparative study of various Data Science and Business analytics program with Great Learning’s PG program in Business Analytics and Business Intelligence:

What are the best Data Science and Business Analytics Courses for working professionals in India?

Great Learning has been changing the lives of professionals across domains for over 5 years now. Having imparted more than 5 million hours of learning, we have touched professionals in 17 different countries, and are working towards reaching more geographies to transform careers of professionals across the globe. 

The post-graduate program in Business Analytics and Business Intelligence was the first program to be launched by Great Learning in the year 2014. Since then, there have been more than 50 batches with 5000+ professionals enrolled and successfully completed the course. The program has been ranked #1 Analytics program in India for 4 years in a row by Analytics India Magazine and has involved 300+ Industry Experts and 25+ India’s Best Data Science Faculty to impart quality skills and practical learning. Having propelled more than 2,500 career transitions, the success of the program can also be gauged by the fact that 90% of our alumni refer the course to other professionals. 

Best business analytics and business intelligence course for professionals

Our alumni have been placed with some of the top Analytics firms and reputed MNCs such as IBM, Accenture, HSBC, KPMG, LatentView, Myntra, Rakuten, RBS, Shell, Tiger Analytics, UST Global, and many more, with an average salary hike of 48%. This alone speaks a lot about the value and industry relevance of the program. Know more about Great Learning’s PG program in Business Analytics and Business Intelligence here. 

Here are a few testimonials by our PGP BABI Alumni. Read-Along:

GL puts a lot of effort to make the curriculum up to date matching world-standards Sowmya Vivek, Independent Consultant – Data Science, ML, NLP

The best part of GL is its experienced faculty – Sriram Ramanathan, Associate Director for Data Products at Scientific Games

The best takeaway is the approach with which I now perceive business problems – Pratik Anjay, Data Scientist at Walmart

The course aided my old desire to pursue finance as a career – Sahil Mattoo, Data Scientist, DXC Technologies

The guidance from the GL faculty is an important driver of my success – Priyadarshini, Analyst at LatentView

 

Book a call with us at +91 84480 92400 and our learning consultants will guide you through the program details and the specific queries that you might have.

10 Most Common Business Analyst Interview Questions

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Preparing for a Business Analyst Job Interview? Here are a few tips and the most useful and common business analyst interview questions that you might face. 

Before attending an interview for a business analyst position, one should be through about their previous experience in the projects handled and results achieved. The types of questions asked generally revolve around situational and behavioural acumen. The interviewer would judge both knowledge and listening skills from the answers one presents. 

The most common business analyst interview questions are:

 

1. How do you categorize a requirement to be a good requirement?

A good requirement is the one that clears the SMART criteria, i.e., 

Specific – A perfect description of the requirement, specific enough to be easily understandable

Measurable – The requirement’s success is measurable using a set of parameters

Attainable – Resources are present to achieve requirement success

Relevant – States the results that are realistic and achievable

Timely – The requirement should be revealed in time 

business analyst interview questions

 

2. List out the documents used by a Business Analyst in a project?

The various documents used by a Business Analyst are:

a. FSD – Functional Specification Document

b. Technical Specification Document

c. Business Requirement Document 

d. Use Case Diagram

e. Requirement Traceability Matrix, etc.

 

3. What is the difference between BRD and SRS?

SRS (Software Requirements Specifications) – is an exhaustive description of a system that needs to be developed and describes the software – user interactions. While a BRD (Business Requirements Document) is a formal agreement for a product between the organization and the client. 

The difference between the two are:

business analyst interview questions

 

4. Name and briefly explain the various diagrams used by a Business Analyst.

Activity Diagram – It is a flow diagram representing the transition from one activity to another. Here activity is referred to the specific operation of the system.

Data Flow Diagram – It is a graphical representation of the data flowing in and out of the system. The diagram depicts how data is shared between organizations

Use Case Diagram – Also known as Behavioural diagram, the use case diagram depicts the set of actions performed by the system with one or more actors (users).

Class Diagram – This diagram depicts the structure of the system by highlighting classes, objects, methods, operations, attributes, etc. It is the building block for detailed modelling used for programming the software.

Entity Relationship Diagram – It is a data modelling technique and a graphical representation of the entities and their relationships. 

Sequence Diagram – It describes the interaction between the objects. 

Collaboration Diagram – It represents the communication flow between objects by displaying the message flow among them.

 

5. Name different actors in a use case diagram?

Broadly, there are two types of actors in a use-case:

a. Primary Actors – Start the process

b. Secondary Actors – assist the primary actor

They can further be categorized as:

i. Human

ii. System

iii. Hardware

iv. Timer

 

6. Describe ‘INVEST’.

The full form of INVEST is Independent, Negotiable, Valuable, Estimable, Sized Appropriately, Testable. With this process, the technical teams and project managers to deliver quality products or services.

 

7. What is Pareto Analysis

Also known as the 80/20 rule, Pareto Analysis is an effective decision-making technique for quality control. As per this analysis, it is inferred that 80% effects in a system are a result of 20% causes, hence the name 80/20 rule.

 

8. Describe the Gap Analysis.

It is utilized to analyze gaps between the existing system and its functionalities against the targeted system. The gap is inferred to the number of changes and tasks that need to be brought in to attain the targeted system. It compares performance between the present and the targeted functionalities.

 

9. Name different types of gaps that could be encountered while Gap Analysis

There are mainly four types of gaps:

a. Performance Gap – Gap between expected and actual performance

b. Product/ Market Gap – Gap between budgeted and actual sales numbers

c. Profit Gap – Variance between targeted and actual profit

d. Manpower Gap – Gap between required and actual strength and quality of the workforce in the organization

 

10. What are the various techniques used in requirement prioritization?

Requirement prioritization, as the name suggests, is a process of assigning priorities to the requirements based on business urgency in different schedules, phases, and cost among others.

The techniques for requirement prioritization are:

a. Requirements Ranking Method

b. Kano Analysis

c. 100 Dollar Method

d. MoSCoW Technique

e. Five Whys

 

Stay tuned to this page for more such information on interview questions and career assistance. If you are not confident enough yet and want to prepare more to grab your dream job as a Business Analyst, upskill with Great Learning’s PG program in Business Analytics and Business Intelligence, and learn all about Business Analytics along with great career support.

How Supply Chain is Using Analytics to Solve Its Problems

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Supply Chain is a tricky business. One missing entity or a lack of synchronisation can break the entire chain and mean millions in losses for a company. However, the use of analytics in this domain is resolving several pain points in supply chain management at the strategic, operational, and tactical levels. According to Capgemini Analytics, “Supply Chain Analytics brings data-driven intelligence to your business, reducing the overall cost to serve and improving service levels.” For supply chain professionals, it can only mean one thing – to upskill to be able to use advanced analytics to improve operational efficiency and make data-driven decisions. Here are 5 case studies about the use of analytics in the supply chain that will motivate professionals in this domain to upskill:

  • Identify the most efficient shipping carriers through advanced analytics – One of the issues that a Fortune 100 CPG company faced was assessing each carrier and choosing the right carrier for shipment across the globe. Since there were various metrics available, the challenge was ranking carrier performance and choosing the right one for shipping. Understanding the carrier selection framework, the solution by Fractal Analysis followed a step-wise approach by identifying correlated attributes, ranking of carriers, and assessing alternate carriers via what-if analysis.
  • Pierian Digital delivered interface, forecasting, and visibility solution to oil & gas major – A Global EPC Service Provider was facing issues without a common user interface across applications to provide end-to-end visibility, visibility of global supply chain and logistics processes, and forecasting for cost and schedule. Pierian Digital’s solution provided Proactive Supply Chain Performance Management Analytics insights positively impacting the top and bottom-line business growth specifically through improvements across the whole supply chain. 

  • Gartner Analyzes Market for Supply Chain Management Solution – A Fortune 500 company knew its innovative solution for supply chain management had huge potential, however, management needed the validation of the market, the competitive landscape, and opportunities to secure funding. A Gartner engagement answered all their questions by conducting a full product assessment, sizing the market, and analysing competitive alternatives. 
  • Improved forecasting and inventory planning for a large retailer – Mu Sigma helped one of UK’s leading fashion retailer to build a customised demand forecasting and inventory planning solution for its online channel involving apparel and home furnishing products. They developed an analytical process to forecast demand and estimate launch quantities for new products during seasonal sales leading to an increase in product availability by 8%. 

How Big Data is transforming Supply Chain Management

Use predictive modelling to control critical process parameters – A Fortune 100 fertiliser manufacturing company produces fertilisers that must meet quality criteria for key natural elements like potassium, nitrogen, and phosphorus to be within a defined range of specification. The results of thorough data understanding and brainstorming determined that for water soluble fertilisers, in 98.4% of instances the prediction accuracy was greater than 95%. For other nutrient products, in 99.9% of instances, the prediction accuracy was greater than 95%. The client saw multi-million-dollar savings through these tools in fine-tuning the manufacturing process.

Analytics provides opportunities for people from a diverse set of professional backgrounds, and Parag Janrao is a shining example. As a management trainee, Parag was handling supply chain and finance projects. Here’s how PGP-BABI helped him advance his journey in this domain.

Why did you choose an online program?

I wasn’t looking for a full-time classroom or blended program because I know that it will be very hectic to go and attend the classes. Initially when the videos were shared, basics were understood and then during the live mentoring sessions, our doubts were clarified. It depends on personal interest. I was very much interested, so I’ve learned a lot.

What did you think about the fee structure?

I felt that it is a bit highly-priced when I compared with Jigsaw and others. That is when the inputs from alumni convinced me that this has more weight and value than other programs available in the market. When I had updated in my LinkedIn profile that I am doing this program, recruiters reached out to me asking about the program and they started reaching out me looking at my e-portfolio. 

How did you transition to Hasbro?

I have moved into my new role after 6-7 months of completing the course. I had no prior experience in analytics because I was working for the functional domain of planning, supply chain and logistics. That was a major issue for me because most of the recruiters look for candidates with hands-on experience in analytics. I had used forecasting and time-series in my previous role then. Hasbro selected me based on my background knowledge of supply chain and logistics because the work I am doing now is on data analytics reporting with a  focus on logistics & supply chain. We mainly work on Excel and other tools and PowerBI for visualization.

Any advice or tips to the aspirants?

There are 6 modules and candidates don’t have to be perfect in all the 6 modules. They should be perfect and thorough in at least one module that they like, and they can get a job in that. In my case, I was really interested in forecasting and time series and so I started working more on those skills. If you really work hard on getting the concepts clear, you should be able to make the transition easily.