Data and Analytics Weekly Round-up: July 9, 2019

Here are a few Data and Analytics updates from last week to keep you informed.

4 Challenges with Leveraging Analytics — and How to Overcome Them

To fully capitalize on the potential of modern analytics, enterprises must balance a complex mix of technical, organizational and cultural requirements. With this complexity come possible roadblocks that can hinder efforts to gain competitive advantage and also dilute returns on investments. Read along how to combat them.

Revenues from Big Data and Business Analytics to Hit $260 bn in 2022: IDC

Worldwide revenues for Big Data and Business Analytics (BDA) solutions will reach $260 billion in 2022 with a compound annual growth rate (CAGR) of 11.9 percent over the 2017-2022 period, according to a new forecast from International Data Corporation (IDC)…. [Read More]

What Matters Most in Business Intelligence, 2019

Improving revenues using BI is now the most popular objective enterprises are pursuing in 2019. Reporting, dashboards, data integration, advanced visualization, and end-user self-service are the most strategic BI initiatives underway in enterprises today…. [Read More]

The Coolest Business Analytics Companies of the 2019 Big Data 100

As part of the 2019 Big Data 100, CRN has put together a list of business analytics software companies offering everything from simple-to-use reporting and visualization tools to highly sophisticated software for tackling the most complex data analysis problems…. [Read More]

Top Five Business Analytics Intelligence Trends for 2019

From explainable AI to natural language humanizing data analytics, James Eiloart from Tableau gives his take on the top trends in business analytics intelligence as we head into 2019…. [Read More]

 

Happy Reading!

 

With Career support, I got to interview with many companies – Sai Ramya Machavarapu, Data Analyst at Mercedes Benz.

A career transition can be a daunting experience for many. But given the right direction, learning, and support, it is more like a cakewalk. That’s why here at Great Learning, we strive to provide the right learning, practical exposure, and complete career support. 

What has your professional journey been like?

I completed my graduation in Electronics and Communications Engineering from Amrita College, Bangalore. Then I moved to the USA to pursue my Masters in Electrical Engineering from the University of Missouri, Kansas-City in the year 2014. I got placed in Reliable Software Resources as a QA Tester and worked until May 2017. I will be joining Mercedes Benz very soon as a Data Analyst.

How did you develop an interest in Data Science? Why did you choose GL to pursue it?

Previously, I was working as a manual tester for a Consulting firm. The job profile involved manual testing for a project of Banking. The role was very limited and monotonous, so I decided not to go deeper into testing. I left my job and moved back to India. As I was from a non-programming background, I was very sceptical to get into coding and related fields. I was looking into various technologies and was suggested by a friend to consider Data Science as an option. I attended many seminars and workshops on Data Science organized by various companies. I developed an interest in this field and was looking for a classroom course. On the recommendation of the same friend, I joined Great learning to pursue PGP-DSE.

Coming from a non-programming background, was it difficult for you to understand the subjects?

Not at all. As most of the students in the batch were from the non-IT background, the course is designed keeping them in mind. The faculties ensured that the basics were covered. I understood that the course is based on Logics, so I slowly developed pace and contrary to my presumptions, I didn’t find it difficult. The faculty put in a lot of time and attention towards us and even repeated the sessions whenever required.

How was your experience of the academic and career support given by GL?

The team was always available, especially Akhila as she helped us thoroughly in preparing for the interviews and gave regular suggestions and feedback for us to improve at the same. Whenever we had any issues, Akhila and the team resolved them at priority.

With Career support, I got to interview with many companies like CTS, Mercedes, etc. Based on my experience, I realized that the curriculum is self-sufficient to crack any interview. The entire course is designed in a way to help us understand the concepts, crack interviews, and guide during the projects. 

What did you like the most in the program?

We were assigned mini projects on the completion of every topic. This gave a lot of hands-on experience of every topic in terms of understanding and its practical application. This hands-on experience on mini projects gave me a lot of confidence and helped me in exams as it gave a recap of all that we had learned in the course. After the completion of the course, during the capstone project, there were many remedial sessions to clear doubts. 

Share your experience of the interview with Mercedes.

The interview was organized by GL at Mercedes’s Bangalore office. The interview included a total of 3 rounds; 2-Technical and 1-HR. The first round included questions based on whatever I had mentioned in my resume and basic questions over Coding, ML, SQL, etc. 2nd round involved questions related to the Business aspect. The final round was an HR round, where they gave me a confirmation after the interview.

Any advice to aspirants who wish to take this course?

They should be confident in sharing what they know and admit to what they don’t know. Give your 100% to every interview thinking that this is the last opportunity as there is a huge competition in the market. There focus should be in developing a strong foundation of whatever they are learning. The interviews are based on basics and focus to test you in your understanding of the field. So, have a stronghold of basics and you will be good enough to crack through it.

 

Upskill with Great Learning’s PG program in Data Science Engineering and unlock your dream career.

 

The placement assistance was excellent – Debashis Gogoi, Data Analyst at Indegene.

There lies a big challenge among engineering students to pick the right field of specialization and build a successful career within the same. Once you understand the core area of interest, upskilling in the same with a relevant course could be a key to unlock your dream career. Here’s how Debashis did it. 

What is your professional background?

I completed my graduation in Civil Engineering from Royal School of Engineering & Technology. After graduation, I worked for 3 months in National Highway project and Gammon India Pvt. Ltd., Guwahati. Then, I moved to Bangalore to pursue the course in Data Science Engineering. Currently, I am working with Indegene as a Data Analyst.

How did you develop an interest in Data Science and How did you choose GL?

I wanted to pursue graduation in Computer Science Engineering but could not as there was no scope for IT in Assam. Based on the available opportunities, I took a course in Civil Engineering. While working during my internship, I realised that I have a passion for Analytics. So I moved from Assam to Bangalore and took some certification courses from Coursera. Meanwhile, I was looking for Data Science courses and got to know BABI is the No.1 course in India for Analytics. Since the only full-time course was of DSE and it was designed for Freshers like me, I took this course.

How was the overall experience with Great Learning?

It was a very nice experience. Before joining the course, I checked the curriculum and found it was very extensive. DSE is a 5-month program and I believe GL did justice in delivering the basics and in-depth understanding. The faculty members were industry experts and they spent a good amount of time with almost all topics. The management was very supportive and the placement assistance was excellent. From CV reviews to Mock interviews, everything made the students really comfortable and industry-ready.

How was your experience at the interview with Indegene?

I got to participate in the placement drives of 6 companies. I got to interview with 3 companies, namely, Kargil Solutions, Evive, and Indegene. With Indegene, there were 2 interview sessions; 1st was a Case Study and 2nd was a Technical Round where they tested me with my basic ML concepts. After the interviews, they offered me the role of Data Analyst. 

Coming from a non-programming background, how easy was it for you to understand the course?

The course is designed with the first week dedicated to Python. Initially, it was a bit tough but then eventually things got easier as we got acquainted with it. The course and the curriculum are very well designed keeping the diversity of the batch in mind.

Any advice for our future aspirants?

My father always quoted me with “Patience and Perseverance always pay”. Along with it, working hard, being focused, and believing in oneself will help anyone achieve the best out of the program. I will suggest them to practice more and participate in a lot of competitions.

 

Upskill with Great Learning’s PG program in Data Science Engineering and unlock your dream career.

GL helped me to kick-start my career – Yeknath Merwade, Associate Analyst at Ugam Solutions

One needs career support the most when they are a fresh graduate. The right direction and support at the right time help multifold in shaping a successful career. What kind of support did Yeknath get? Read on:

What has your professional background been?

I completed my Graduation in Electrical, Electronics & Communications Engineering in 2018 from Belagavi, Karnataka. I then took a course in Data Science at Great Learning, Bangalore and currently, I am working in Ugam Solutions as an Associate Analyst.

How did you develop an interest in Data Science?

I finished my graduation with 58% aggregate score. With this score, I was not eligible to attend interviews for any good role or company. I understood the need to upskill myself as my father suggested me to read about Data Science which has created a lot of buzz. After researching online, I developed an interest in it and got fascinated with what this field can do.

Why did you choose GL to pursue a course in Data Science Engineering?

After viewing the scope and growth opportunities, I immediately started to search for courses. But to choose the best out of them was a task in itself. All I wanted was to take a classroom program as for a fresher it was better compared to online training. I visited GL’s website for weeks and saw it was regularly updated with relevant data and testimonials. I checked the reviews on Google and LinkedIn as well. Finally, I looked at the faculty profiles on LinkedIn and saw their experience. I understood that GL is the best institute in India to study Data Science, so I took up the course here. 

What did you like the most in the program?

There were many things that I loved about the program.

  1. The Faculty: Since I looked at the LinkedIn profiles of almost all the teaching professionals, I got to know that they all were Industry experts and had a great experience in their respective fields. When I enrolled myself for the course, I was surprised to see how grounded and friendly they were. Also, they taught us everything from scratch. 
  2. Course-Curriculum: The course is well designed and well structured. The curriculum is exhaustive and gave me a good understanding of the domain. The course includes what is needed by the industry and everything is accommodated in the syllabus.
  3. Career Assistance: I got to sit on campus drive of 7 companies and got shortlisted in all of them. Apart from this, the CV reviews and Mock Interviews helped me develop confidence and crack interviews. Also, they organized Bootcamps for the students and helped us in all aspects. There were ample opportunities and it got us placed.

Overall it was a nice experience as I got good friends and faculty with whom I learned a lot and I am still in touch with them. I feel very grateful to GL, that helped me to kick start my career.

Being from a non-programming background, did you face any issues with the course or the transition?

Initially, it was very hard for me to adjust to the syllabus as I was not at all familiar with Coding or programming. The first week of the course started with Python, which was a new thing for me. Here, I would like to mention that the teaching faculty boosted my confidence by mentioning that “It is not rocket science and is easy to learn”. After the EDA session, I felt self-motivated and realised that irrespective of any branch, one can achieve success in their ventures. Slowly things started to fall in place. I was in regular sync with sessions, and the regular exams and quizzes kept us in constant touch of the topics. In the end, everything was good and great.

Share your experience of interviewing with Ugam?

I had 4 rounds of the interview; An SQL Test of 30 minutes duration, followed by a Case Study of 30 minutes duration again, a Technical round and finally an interview session with Vice President and HR. The technical round involved questions around my Project mentioned in the Resume and general technical questions to check my understanding of algorithms. With the VP, the interview was to check how my understanding can contribute to the Analytics team of Ugam and general questions from the HR. After the interview, I received a job confirmation from them. 

Any advice to our future aspirants of this course.

I would like to suggest to prepare well on Stats and SQL. The material is self-sufficient and includes in-depth content and curriculum. The placement assistance is superb and helps everyone in getting placed. So there is no need to panic for anything. Also, focus on your project as all my interview questions revolved around my Capstone Project.

 

Upskill with Great Learning’s PG program in Data Science Engineering and unlock your dream career.

I got to interview with 3 companies – Pushpendra Nathawat, Programmer Analyst at Cognizant

Finance has evolved to position itself as an important business function. Given the nature of this domain, it overlaps with analytics in many areas. Finance professionals and executives are finding new ways to leverage from this overlap and increase the value of this vertical in their organizations. 

What is your professional background?

I had completed my MBA from Tapmi School of Business in the year 2015. I then joined Vodafone and worked as a Relationship Manager for 10 months. I switched to HDFC and worked for over 1.75 yrs as an Assistant Manager. Currently, I am working with Cognizant as a Programmer Analyst.

Why did you think of upskilling? Why did you choose Great Learning?

I did an MBA with Finance as my specialization and while working with HDFC, I enrolled myself in Financial Risk Course with IIM Kashipur. Though I had good knowledge in Finance Domain, I had no understanding of Coding or Data Science. I felt the need to upskill and checked for the courses. While searching I found high recommendations for GL. So I left my job in Jaipur and moved to Bangalore to pursue a full-time program in Data Science Engineering with Great Learning.

What did you like most about the program?

The management, staff, and the faculty, everyone was very helpful. The faculty took a great deal of interest in teaching students and gave a good explanation of every topic. The management was very supportive in providing any assistance whenever the batch needed extra sessions or special classes for having a better understanding of the programming subjects. 

How was your overall experience at Great Learning?

Since I was from a non-programming background, initially it was a bit difficult to follow the specific modules. But later with the help of faculty, I could cope up with the subjects and it became easier to understand and manage. The faculty was very helpful in providing material and guidance, especially in my lacuna. They took extra effort in organizing classes over those areas during the weekends. Since I was very new to Data Science, I had to improvise a lot in terms of my CV & Interview performance. The Career assistance provided by GL helped me prepare an impressive CV & mock interviews prepped me to crack interviews.

Share your experience of Career fair organized by GL?

I got to interview with 3 companies; Kinara Capital, Credi India, and Cognizant. I cleared the interview with CTS which involved 3 rounds; 2 in Technical of 45 minutes duration each and 1 HR round of interview on the same day. The technical interviews involved testing my knowledge of Machine learning. I got the job confirmation on the same day.

 

Upskill with Great Learning’s PG program in Data Science Engineering and unlock your dream career.

7 Domains Benefiting from Big Data and Machine Learning

The wonders of Big Data and Machine Learning are already dazzling the world. Whether it is driverless cars, quick-wit from robots, or Facebook chatbots that had to be shut down, it is safe to say that no aspect of our life stays untouched from AI and Machine Learning. Having said that, there are several fields that are making key progress in leveraging Big Data to revolutionize the way they function, conduct business, and more importantly the way they envision the future. Here is a glimpse of each:

Manufacturing For a long time, the manufacturing industry was associated with a slew of problems – health risks, worker unions, poor optimization methods, and what not! However, technology and Big Data Analytics (BDA) to be precise emerged as a game changer and is now taking the factories and production units to the next level. Big Data Analytics and Machine Learning are making factories smarter with computerization of manufacturing processes, optimizing quality checks, improving accuracy and quantity of production, and promoting 3D printer factories and MaaS (Manufacturing-as-a-Service) with better collaboration. Read more

Healthcare Apart from helping hospitals and companies to cut down on costs and increasing profits, analytics has been instrumental in improving the quality of life by helping to diagnose diseases, determining the most effective course of treatments, and decreasing the overall mortality rate. As Charles Doarn, director of the Telemedicine and e-Health Program at the University of Cincinnati puts it, “Our healthcare system is in desperate need of reform, and technology is one of the tools that can help. It can be a paradigm shift in how we practice medicine.” Read more

Government Initiatives Thanks to the Union budget 2018, the NITI Aayog will initiate a national program to direct efforts in Artificial Intelligence, and the Department of Science and Technology will launch a Mission on Cyber-Physical Systems to support the establishment of centers of excellence for research, training, and skilling in robotics, artificial intelligence, digital manufacturing, big data analysis, quantum communication, internet of things, etc. Find out how government initiatives will help the government revamp manufacturing and commerce, banking, healthcare, cybersecurity, and even town planning. Read more

Finance and Banking How do machine learning and artificial intelligence impact the financial industry? The financial industry in India or the Banking, Financial Services and Insurance (BFSI) sector in India is a fast-evolving one. How then, do banks and associated organizations save time, costs and yet add value to their operations for smooth functioning? In India, Artificial Intelligence (AI) has begun to play a major role in solving some of the most vital problems faced by both companies as well as customers. Not just banks, but nearly every company whether public or private in BFSI has started using AI for Robo-advisory, risk management and fraud detection, sophisticated high-end trading, and providing superlative customer experiences, etc. Read More

Delivery of Public Services The nation is on a massive-path digitalization. It is, currently, being realized through the Digital India mission. Today, more than 980 million Indians have AADHAR cards, 700 million own mobile phones, and more than 300 million have access to broadband internet connection. This transforms into a massive data set that has the potential to actively transform the public services delivery system. Find out the top 3 to-dos for the Indian government to transform its public delivery system.

Supply Chain Management Supply chain is a natural choice when it comes to Big Data finding its applications. From improving delivery times by synchronizing shipments to identifying better ways to reduce the communication gap between manufacturers and suppliers, today, Big Data Analytics is working as an evolutionary catalyst for the supply chain management to analyze consumer behaviors and habits, improve customer experience by personalizing it, streamlining e-commerce, and managing and distributing inventories exceptionally. Read more

E-Commerce While many industries are still at the nascent stages of figuring out what to do with the huge amount of data at their disposal, e-Commerce is one industry that is already reaping the rewards of their Big Data initiatives. Major players in this industry rely heavily on their team of data scientists to compete in this fiercely dynamic space. The key ways e-Commerce companies are deriving value from Big Data analytics are by personalizing offers, running promotions or big discount days, inventory management, and optimizing pricing by introducing real-time pricing. Read more

The only resolution you should be making in 2017

Every New Year brings with it the hope of a new beginning in our lives and along with it, come the myriad of resolutions we make to ourselves. Research indicates that most of the resolutions made by people are towards fitness and weight loss. As a result, January becomes a windfall month for most gymnasiums and fitness studios while most of us don’t become any leaner or fitter with passing years the one thing that we can definitely achieve is being a better version of ourselves. To achieve that you don’t have to make tall promises to yourself just Make Learning a Habit.

Learning new things is simple, achievable and one of the most profitable investments you can make each year.

 

1. Learning is like weight-loss

train

Let me make an uncanny analogy here: Aspiring to becoming leaner is very similar to wanting to learn something new. Ultimately, you have to change something that’s core in your behaviour to have the desired results. Both these goals need focus, determination and lots of discipline. And lastly, just as in weight loss as in education, there are no low-hanging fruits or express results. Both take time to fructify, but once you go the distance, there is no looking back.

 

2. Why ‘Learning’ in 2017?

Why we need to learn in 2017

The right question here should be ‘Why Not’. There has never been a better time to learn and frankly speaking, with the changing dynamics of businesses and technology disruption impacting us, if we don’t make learning a habit in 2017 and onwards, our professional credentials would be questionable at best and irrelevant at worst. Learning new skills and upgrading one’s professional capabilities is no longer a matter of choice but a necessity to have a fruitful career. In today’s time and age, the half-life of knowledgehalf-life of knowledge is forever decreasing which means that one needs to keep learning always to stay professionally relevant. The new reality is that what you learn at 25, will not take you till 35.

 

3. What should I learn?

What should you learn

This is like standing by an ocean and trying to find the perfect starting point for your swim. What you can learn is limited only by your intellectual bandwidth and interest. For the sake of brevity, let us focus on what the professional in you needs to learn. Depending upon the industry you are in or aspire to be in, you need to understand the trends that are driving growth. If you are unclear about it, you should talk to your seniors from the industry and pick their brains. Pick an area that is affecting most companies in your space and eventually will impact everyone and build your skill sets in that. Professional competencies such as analytics, big data engineering, product management, information security, intellectual property, digital marketing etc. are high growth areas where most companies are struggling for ‘good’ talent. Finding a sweet spot like this and making yourself competent in it will ensure your career benefits from this talent shortage.

 

4. Where should I learn?

e-learning

Learning in 2017 will be easier than ever before. From blogs to YouTube or TED, from companies offering online learning to mobile apps, ‘lack of access’ cannot be your excuse to not learning. But having said that, having a plethora of options makes it overwhelming and confusing.

I come across some candidates who know what the skills they need to acquire but are not sure if they will be able to learn. I usually advise them to first test the waters by accessing some free content online. YouTube is usually a good source for this. See if you like what you are learning and are able to grasp it.

 

5. Why do we fail to learn online?

why we fail to learn

If you are the kind that does not suffer from such starting troubles, you will usually find your learning options to be either completely online courses or blended courses (online + occasional weekend classroom sessions). Given this spread, how do you decide which format to go for?

Completely online courses provide convenience since you don’t need to attend any classroom sessions. But, online learning has been plagued by abysmally low rates of completion. The main reason for this is that for most of us, we learn better when we learn in a classroom setting with peers and faculty, who we can talk to in person.

The flexibility of attending class room sessions over few weekends in a month gives you the advantage of mixing the best of two worlds – the flexibility of online learning and the learning effectiveness of classroom learning. In our blended analytics program, we have seen hundreds of candidates do our program after having done one or multiple online courses. When asked, the most common response we get is because they feel that their learning in the online programs was incomplete. Also, when it comes to acquiring hard skills such as analytics, big data or machine learning, it is important to focus on programs that are more exhaustive and immersive and don’t take a superficial approach by promising to teach something in a matter of some hours.

 

6. What will it take?

learning in 2017

Learning is for everyone. Amongst the thousands of candidates who take our programs every year, we see about 30% of them to be with in the 15-30 year experience bracket. While there is no age to imbibe the habit of learning, just like with all good habits, the sooner you do it, the better you are. Having said that, learning is hard work. Depending upon when was the last time you were in a class, you would need discipline, focus and perseverance to go the whole distance. Usually, we have seen that the first two months are the hardest but once you settle into a routine within the first sixty days, you will go one to achieve the results you desire. The advice that we give to all our learners is to start small. Begin by dedicating an hour every day for the first 2 weeks, then about 8-10 hours a week for the next thirty days. Small changes in your habit will ultimately lead to big gains in your learning and professional success.

On that note, in 2017, make a promise to yourself. To learn something new and to challenge your professional status quo. Make Learning a habit and build the career you’ve always wanted. Oh and as for fitness, try playing a sport – 5 days a week. It is fun and just as effective (or ineffective) 🙂

5 Reasons why 250+ professionals have chosen Great Lakes Analytics Program          

Big data = Big opportunities.

Businesses today are flooded with massive information and data, but face a hard fight to make sense of it all. This burning concern to utilize the data strategically has led to a rising demand for data scientists and business analysts. Simultaneously, the skills gap for all such kind of jobs has been well documented. Identifying the growing need, institutes are developing data-oriented Masters Programs.

Great Lakes’ PGPBA program has an industry endorsed unique pedagogy that blends general management and analytics and makes you industry-ready. The candidates pursuing this program can expect to gain an overview of business foundation and a comprehensive knowledge of analytic techniques, with an applied industry orientation designed for professionals interested in a career in analytics.

Here are 5 best of reasons for why 500+ professionals have chosen Great Lakes Analytics Program:

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