Difference Between Data Science & Business Analytics

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Data Science vs Business Analytics, often used interchangeably, are very different domains. A layman would probably be least bothered with this interchangeability, but professionals need to use these terms correctly as the impact on the business is large and direct. In this article, we will elaborate on the difference between the two.  

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Overview

Data Science and Business Analytics are unique fields, with the biggest difference being the scope of the problems addressed. Simply put, The science of data that uses algorithms, statistics, and technology is known as Data Science. It provides actionable insights on a range of structured and unstructured data solving a broader perspective such as customer behaviour. 

Difference between Data Science and Business Analytics

On the other hand, the statistical study of mostly structured business data is known as Business Analytics. It provides solutions to specific business problems and roadblocks. 

These two terms are interchangeably used in either of the above scenarios, i.e., a business analytics problem could be wrongly addressed to be solved with the help of Data Science. The implications of carelessly using the term ‘Data Science’ in this context could be adverse because the tools and techniques used in Business Analytics are different than Data Science and using wrong tools to assess a data set will yield imperfect and undesirable results. 

Data Science is an umbrella term for all things dedicated to mining large data sets. An intersection of programming, statistics, and data analytics, Data Science is not limited to only statistical or algorithmic aspects. Business Analytics is the end-product of data science. It includes two broad categories, that are Statistical Analysis and Business Intelligence. 

Difference between Data Science and Business Analytics

Business Intelligence

Another term often confused with Data Science is Business Intelligence. It is also an umbrella term that portrays ideas and strategies to improve decision making by utilizing fact-based support systems. Modern Business Intelligence is much beyond just business reporting. It is a mature framework that encompasses intuitive dashboards, mobile analytics, what-if planning, etc. It additionally incorporates enormous back-end machinery for maintaining control around reporting.

Although it sounds similar to Data Science, it is not. The principal difference lies in the type of problems that they address. Business Intelligence deduces the new unknown values of previously known elements using a formula that is already available. On the other hand, Data Science works with unknown scenarios without any formula or algorithm in hand, to solve data queries that nobody has ever answered in the past. Data Science problems are solved by exploring data, finding the best method, building a model around it, and finally operationalizing the model. 

Conclusion

Business Intelligence is well established with deep roots in a typical corporate landscape. Corporate professionals are familiar, comfortable, and confident with the BI concepts and framework. As BI projects work on known unknowns, the projects can be planned well in advance and timelines could be efficiently followed. Also, there is minimal trial and error with several successful BI projects in a company’s kitty, who would have developed good project expertise over the years. 

There is a massive career scope in the fields of Business Intelligence and Business Analytics. Professionals who are genuinely thinking of making a shift in the BA and Data Science roles can consider upskilling with the right course. Great Learning’s PG program in Data Science & Business Analytics and helps working professionals make a smooth and successful transition. The course offers the choice of online or classroom-based learning with Dual Certificate from University of Texas at Austin, McCombs School of Business (world rank #2 in Analytics), and Great Lakes (India rank #1 in Analytics). It helps you with hands-on practical learning with case studies and projects, without the need of quitting your job. The course is also tailor-made keeping in mind the professionals from the non-IT background. With our career guidance and support, you can easily land your dream job in Business Intelligence and Business Analytics.  

The course offered an exhaustive curriculum – Dipankar Neogi, Sr. Data Analyst at Indegene.

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There are times when professionals in a specific domain reach saturation and do not enjoy working in their domain. At such times, one can either succumb to the monotony or rise up to look out for opportunities in other domains, sometimes drastically different from their current role. This is what Dipankar Neogi did when his marketing career reached its saturation point. Read how he transitioned to a data analyst role from being a marketing professional.  

What is your professional background?

I had completed my post-graduation as an MBA from Ramaiah Institute of Management Science in 2010 and worked for 7 years in Marketing with a firm in Bangalore. In order to upskill and upscale my career, I took a course in Business Analytics and Business Intelligence at Great Learning. Presently, I am working with Indegene as Senior Data Analyst.

Why did you choose Business analytics for upskilling and why did you choose GL?

I was not happy with the role I was working in previously. There were no growth opportunities and the remuneration not satisfactory. I had two options; one was to take up a full-time technical course and the other was to pursue an Executive MBA or get through GMAT to ISB or IIM. There was a lot of buzz for Analytics and Data Science and some of my friends suggested some courses. I did research and came across the GL’s BABI course. Since it was more business-related than a tech-driven program, I took this course as it suited me the best.

How was your overall experience with GL?

The course offered an exhaustive curriculum. Now since I am working in an Analyst role, I see how well-versed the course is. It provided detailed learning in Statistics, Regression, Conjoint analysis, etc., all of which I am using in my current role. The classroom experience made me realise the dream of being from a reputed firm. Working with peers and coming together on weekend classes or for projects, is what I recall as the most memorable time at GL.

Share your experience at the Interviews?

I got interviewed and shortlisted by many companies. I realised some patterns in the questions asked during the interviews. I figured out that the interviewer mainly focussed on my learning of the project that I had mentioned in my CV. In some interviews, I was given a real-life situation and was asked to give predictions for them. They judged me not only on my answers but also on my perception of the situation and the approach towards it.

Any advice to future aspirants?

Firstly, you need to focus more on projects. Apart from the Capstone project offered by GL, work end to end on some projects of your own. This will give you clarity and confidence with the subject matter. And secondly, focus on mastering one domain at a time. This will give you a stronghold in the domain.

Upskill with Great Learning’s PG program in Business Analytics and Business Intelligence and unlock your dream career.

The quality of faculty at GL is unmatched compared to other institutes – Venkatesh Radhakrishnan, Sr. Research Analyst at RRD

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From an amateur in Data Science to a Hackathon winner, Venkatesh has come a long way in his career. He was a newbie in this field since he’s from a commerce background, but he still didn’t lose confidence or direction throughout the course. Here’s how he did it: 

What is your professional background?

I completed my graduation with B.Com in Informations System Management from Ramakrishnan Mission Vivekananda College, Chennai by 2015. Then, I started as a Research Associate in RRD – Global outsourcing solutions, APAC. In 2017, I took a BABI course with GL. Currently, I am working as a senior research analyst at RRD.

How did you develop an interest in this course? Why did you choose Great Learning?

As soon as I started working in RRD as a research associate, I got aware of the Analytics field in terms of information & intelligence value. As a market researcher, I developed an immediate interest in this field and started looking for institutes that provided courses in this stream. I came across GL and it’s brand value. I got in touch with the team, got interviewed for the course and cracked admissions in BABI course at GL. 

How did you transition from a Research to a Data Science role?

During my time at GL, I spoke to my organization about my course and requested them to let me explore my skills in order to check applicable areas. After their approval, we started developing a proof of concept for clients; which turned pretty well. In the past 2 years, as a company, we have come a long way in terms of our practice and implementation of analytical tools. I feel privileged to be a part of an organization where through the help and support of management, I could transition to the Data Science field.

What did you think was the best thing about this program?

The best thing about this course is it provides flexibility in terms of learning things at one’s own pace. The course and curriculum are designed to promote learning and not spoon-feeding. There is an ample amount of time to learn, understand, practice and implement the concepts. The quality of faculty at GL is unmatched compared to other institutes.

What would be your advice to the future aspirants?

The advice would be to develop key skills in identifying areas where analytical tools can be applied to make things easy and profitable. One needs to study and research properly to understand the deployment of tools in favour of Business.

Upskill with Great Learning’s PG program in Business Analytics and Business Intelligence and unlock your dream career.

Your essential weekly guide to Data and Business Analytics 

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By 2020, 80% of organizations will initiate deliberate competency development in the field of data literacy, according to Gartner. The march of analytics into the collective consciousness of businesses around the world is unstoppable now, and the implications are far-reaching. From a glut of new skills that employees need to learn, to the shiny new applications of Analytics that’s changing the way humans live, there’s quite a lot of activity going on here. We try to make sense of all that news in our digest that encapsulates the Analytics landscape.

Here are some articles that will take you through recent advancements in the data and analytics domains. 

Businesses Face Three Biggest Challenges While Leveraging Big Data

According to a report from Dun & Bradstreet, the three biggest challenges businesses still face when it comes to leveraging big data are protecting data privacy, having accurate data, and Analysing/processing data. The global big data market was estimated at $23.56 billion in 2015 and now is expected to reach $118.52 billion by 2022.

Big Data & Business Analytics Market to Rear Excessive Growth During 2015 to 2021

Due to the tremendous increase in organizational data the adoption of big data and business analytics has been increased within organizations to better understand their customer and drive efficiencies. Read more to know about Drivers and Challenges of Big Data and Business analytics market. 

‘Jeopardy!’ Winner Used Analytics to ‘Beat the Game’

An aggressive strategy, mathematical finesse, a sharp mind, and a willingness to take risks were some of the factors that spurred ‘Jeopardy!’ game-show contestant James Holzhauer to win 32 consecutive games and rake in more than $2.4 million. Read more to know how this happened. 

The Age of Analytics: Sequencing’s New Frontier is Clinical Interpretation

Today, genomic data is being generated faster than ever before. And those on the frontier of this field are trying to make sure that data is as useful as possible. While the surge in sequencing has benefited many patients, the genomic data avalanche has caused its own problems. Read more about the challenges and proposed solutions to manage and analyze the volumes of genomic data. 

Times Techies: Upskilling is Key to Meeting Demand For Analytics

An exhaustive Nasscom-Zinnov report released last year flags a huge talent demand-supply gap in the artificial intelligence (AI) and big data analytics (BDA) family of jobs. By 2021, the total AI and BDA job openings in India is estimated to go up by 2,30,000. But the fresh employable talent or university talent available will be just 90,000, leaving a huge gap of 1,40,000. 

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

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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.

Is Design Thinking PepsiCo’s Secret to Market Dominance?

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Pepsico CEO Indra Nooyi took up the reins of the company when it was facing considerable drop in sales. As a way to address this, she revised her business strategy to make it more inclusive for consumers. She famously went after Mauro Porcini and sought his expert advice to redesign PepsiCo’s user experience. Eventually, her team resolved the problems by relying on an iterative process of understanding users and providing instinctive solutions.

Under the leadership of Indra Nooyi, PepsiCo prioritised user-specific solutions, designed products that were more human-centric and earned the company record-breaking revenues apart from accolades. User experience was not a part of PepsiCo’s business strategy until the early 2010s. Whether it was their product packaging, form or function, that human element was missing in the design. Once they focused on customer experience and made design a priority, customers responded by engaging with the brand more. From designing touch-screen fountain machines (Pepsi Spire) to launching a special line of women’s snacks, PepsiCo reconditioned the way consumers interact with products. Mauro Porcini successfully introduced a more consumer-centric PepsiCo to the world with design thinking being the key driver behind all these changes.

The company leveraged design to drive innovation and create relevant brand experience for their customers. Design thinking helped them change their brand’s visual identity and improve the product itself. Following an iterative prototyping process, Pepsico was able to align the company goals around the product, helping transform obscure ideas and overcome plausible blockers in production process.

What really helped PepsiCo’s journey towards success was a deep understanding of consumer needs – the idea that the product had to communicate with the consumer in a way in which was unheard of before. Getting a perception of what consumers wanted from each of the products- vending machines, fountains or consumables and crafting the experience accordingly helped the company reclaim the market. 

The Pepsi spire (a series of fountains and vending machines) is the most loved and the first in the design enhanced line of products. Pepsi Spire allows customers to customize their drinks by communicating with a highly responsive touch-screen fountain. Now, if you are wondering if design thinking is just about enhancing product packaging, it’s not quite so. Pepsi Spire is a classic example of how design thinking can impact all phases of product-customer experience. The spire is basically a futuristic machine that speaks to customers and invites them to interact with it. Its intelligent interface reminds customers of the order history and suggests new options based on the customer profile. They can also experience the infusion digitally by watching the whole process of adding their favourite elements in the drink on the screen in real time- right when they select it. This approach extends the enhanced customer experience to the post-product phase and makes it holistic. Pepsi Spire has now become iconic and inspired a series of intelligent vending machines. 

Other Companies taking Cue from PepsiCo

Using design thinking to drive business means designing solutions with customers in mind – not only will that lead to more customer satisfaction but also establish businesses as distinguishable brands. What company wouldn’t want that? Global leaders are already using design thinking to align their customer’s goals and step into the future. Let’s take a look at the top companies who have already benefited from this model. 

Apple:  Apple is undeniably a classic example of how reconstructing user experience through innovation can lead to revolutionary success. At its core, Apple remains a company that has always championed innovation and delivered unique customer-driven experiences – all thanks to design thinking. Apple products ranging from iPhone, MacBook to ios not just bring you exquisite usability but also optimised functionality. From providing a holistic user experience to predicting customer needs, Apple has successfully shown the rest of the world how it’s done.

Nike: Nike has been a pioneer in merging sports with fashion. A brand which primarily targeted athletes and helped them enhance performance has now become quite a fashion trailblazer. “Move forward” (their pet phrase) not only dictates their designs but also aptly captures their user imagination. All along, design thinking has been instrumental in shaping their advanced products and services.

Google: Needless to say, Google has been acing the game and how! Whether it is Google map or Google Pixel’s image software, Google products are glaring examples of enhanced designs. Google teams are constantly thinking ahead of time and designing products and services that answer futuristic customer needs. Google’s constant endeavour to design products with a focus on user experience has established the brand as a world leader in design thinking.

Design Thinking has been around for longer than we think and its focus towards building enhanced user experiences has made it a much coveted strategy for brand building today. To put it in Porcini’s own words,

“People don’t buy, actually, products anymore, they buy experiences that are meaningful to them, they buy solutions that are realistic, that transcend the product, that go beyond the product, and mostly they buy stories that need to be authentic.”

PepsiCo’s success has since then inspired many other companies to rethink their business strategy and hire design thinking experts. If you are an enthusiast, learn more about it here.

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

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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]

 

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