Frequently Asked Questions

The idea behind data analytics is to see numbers as information and dissect business and policy relevant insights in the most precise and comprehensive manner. Data Analytics is more about informed decision-making than merely designing or running scientific programs. A number of statistical tools and software are available to perform analytics but the nature of data and the problem which needs to be solved guides the choice of statistical tools and techniques. Domain knowledge and expertise are also very important to interpret and apply the results obtained from analytics. Lastly, in our experience, the best data analysts are those who have the ability to dig into the data but can also layer common sense and domain knowledge into their recommendations.

Data has seeped into every facet of our professional and personal life. Data Analytics is fast becoming an integral part of businesses to understand their customers in fundamentally new ways. It is well understood that the policymakers as well as the corporations will lose their edge in the market if they don’t rely on data backed insights. Hence, the relevance of data analytics has grown immensely which has translated into greater demand of analysts who can play with data and construct relevant discernment for business and policy development.  Statistics from Indeed.com shows, there has been a 256 percent increase in data-driven jobs since 2013, which suggests companies recognize the worth of data-intelligent workers and want to add them to their teams. Interestingly, LinkedIn recently picked data-driven positions as its most promising career of 2019 with a career advancement score of 9 out of 10. This is the potential data analytics hold in shaping and escalating your career graph!

According to the International Institute for Analytics (IIA), the world will create 180 zettabytes of data (or 180 trillion gigabytes) in 2025, up from less than 10 zettabytes in 2015. This momentous growth of data is ushering in a Fourth Industrial Revolution – Digital Business Transformation. No surprises then that the big data analytics market is expected to surpass $200 billion, with worldwide revenues to grow from $130.1 billion in 2016 to more than $203 billion in 2020, at a compound annual growth rate (CAGR) of 11.7%.

Is this upswing here to stay? There are definitely no doubts about that. Hence, the business and policy think tanks are increasing relying on the power of data and intelligent analytics for designing realistic goals and achieving it in both India as well as the rest of the world. Randstad reports that the annual salary hikes for Data Analytics professionals in India is 50% more than other IT professionals which within itself shows the worth of analytical skills. The data science sector has been reeling with massive shortage of skilled talent in the country. In 2019, close to 97,000 positions related to analytics and data were vacant owing to dearth of qualified talent. Similar shortages of skilled analysts have been reported from other foreign countries as well, namely, The US and the UK. Higher skills and less supply entail higher salaries, hence, data analytics is the buzz word in the changing world of work. While there has been an increase in the number of professionals up-skilling in this domain, the job growth has outpaced this number, leading to lucrative career opportunities.

• BI is intended for analyzing specific data using specific strategies and technologies to offer past, present, and predictive views of a business’s daily operations. 
• BI uses structured information, and it falls more under this solidly in the domain of analytics, and it uses a lot of visualization tools and dashboard reports that are built on more standard statistics. It analyzes current information to pinpoint trends. 
• If you look at data science, it uses both scripted and unstructured data and is based more on science and mathematics, using various forms of sophisticated statistical and predictive analysis. You can think about machine learning or AI, of course, which combines both past and current data to arrive at these future predictions.

• Analytics is indispensable in any profession – whether you choose market research, academia, operations, logistics, sales, or any other field, analytics is the key to make better business/policy decisions and find solutions by accessing the data of the past to discern patterns for the future.
• To draw inferences, it is imperative to understand how to manage the dumb data and then employ techniques for decisive outputs that enable storytelling and forecasting which are intrinsic features of data analytics.
• Loads of data is being collected each day from each realm, which has become increasingly difficult for the companies to manage. According to the 2018 Data Security Confidence Index from Gemalto, 65 percent of the businesses polled said they couldn’t analyze or categorize all the data they had stored. As a data analyst, you can help companies make progress with the data they gather, making it pay off for them both quickly and over time.
• Data analytics makes you internationally competitive!

Any degree or diploma helps you in developing perspective about issues and matters that concerns you. A lot many times your college degrees are restricted to emancipate your understanding of theories that govern the domain and fail to make you understand how it affects or explains the real-time problems. If the foundational degree programs that are offered by Universities are complemented with courses in analytics, then it opens up a wide range of career opportunities, ranging from coveted positions in think tanks, government policy making institutions, banking sector, international development and MNCs. Not only you fetch a better role and a handsome salary package but you also achieve these relatively early vis-à-vis your peers. It is also expected to make you a stand-out candidate in your campus placements.

Yes! You can easily fetch an entry level data analyst position even without a degree in statistics or mathematics. Someone who has no specialization in data analysis, but opts for an apt market-relevant and well-structured hands-on-training can easily find a place in the data-driven job market. Most entry level data analyst jobs at least require a bachelor’s degree. Some of the entry level position titles includes research assistant, business support analyst, operations analyst. Most of these positions further hone your skills by providing valuable on-the-job experience.

Becoming an analyst is purely a matter of choice! But we will not debunk that it is also the need of the hour to have a satisfying career in these dynamic times. To be able to become an impeccable analyst, you need to have a solid inferential foundation. This you may have acquired during your live-projects or dissertation writing during an undergraduate or a postgraduate course & if not, then you may have to choose a course that introduces you to the nitty-gritties. It is important to understand that merely learning software may not make you a good analyst; you need to draw powerful inferences to remain in the market. A well-structured course with abundance of practice can provide you with the right mix of training in handling data, software and drawing meaningful inferences.  You may not necessarily go for a degree or a diploma course for the same which are costlier and take relatively long to complete.

Very basic ones!

• Understanding of High school mathematics.
• Access to MS Excel and MS Office
• You should be ready to ‘think out of the box’!

Absolutely Yes! We have a team of experts who are truly outstanding in teaching analytics. We have been training research scholars and corporate clients in data analytics with absolutely no technical knowledge of statistics, economics or econometrics. We have been a first-hand witness to their learning graph and performance. All that we expect from you is your time, patience, and practice. Our courses expect you to do regular hands-on training and assignments which will smoothly land you in the data industry. Hence, the key to analytics not a foundation in economics or statistics but practice!

Tableau is a storytelling tool and it’s hard to think of a professional industry that doesn’t benefit from a tool that makes your data easily understandable. Tableau offers practical, real-life applications that are undeniable. And, since visualization is so prolific, it’s also one of the most useful professional skills to develop. The better you can convey your points visually, whether in a dashboard or a slide deck, the better you can leverage that information. While traditional education typically draws a distinct line between creative storytelling and technical analysis, the modern professional world also values those who can cross between the two: data visualization sits right in the middle of analysis and visual storytelling. This is why Tableau is a massively loved tool in the corporate world.

Each software brings something extra to your skill-set. For instance, working with Tableau makes you a pro in data visualization while working with Stata makes you an expert in statistical analysis. Now, this is not to say, we cannot draw charts and graphs in Stata but certainly the ease of doing the same is much higher in Tableau with better and more aesthetic look. Also, the world of analytics is evolutionary and dynamic, hence, learning and sticking to one tool may not ensure your survival in the long-run. Different industries and work domains have different technical requirements, so, learning more than one tool will undoubtedly provide you with a distinct comparative advantage and open up wider professional opportunities for you.

Although choice of each program or courses offered in this domain are purely driven by the interest and requirements of the learners. However, we can assist you in this. all you need to do is to register yourself for a free consultation with our in-house experts! We have a team of champions who have excelled in the field of data and belong to diverse academic and professional backgrounds. They take cognizance of your interests and academic profile and can be your best mentors for selecting courses in general and career in particular. Meanwhile, some of our blogs may help you too!

At Outlier, we offer you the best match of an analytical course given your interest, knowledge and requirements. This will enable you to fend better internships for academic scholars who are still pursuing an academic degree, will enable lecturers to design and carve out better research papers and for working professionals it may imply a career jump altogether. We not only teach you how to be a pro in managing complex datasets using statistical and visualization tools but also train you in formulating policy relevant data-backed inferences.

We provide live interactive lectures; we focus on student learning capacity and adjust our teaching methods accordingly.

• We strive for developing statistical foundations and inferential capacity of learners unlike many other training institutions which focus on providing codes and explaining you how to run them.
• Data analytics require human intervention rather than pre-recorded lectures in robotic voice.
• Learners make numerous errors while practicing. Hence our trainers are there to answer all you question during training.
• We focus on theoretical aspects of techniques as well and teach in-depth the implications of various techniques. In short, we don’t just teach tools but techniques in details.
• We work with real-time data sets and go beyond the course to keep their learners updated about what works in the job market and what doesn’t.
• Our trainers counsel and help learners preparing for analytical positions. That’s why we hire all-rounders and well-experienced trainers who can understand and guide young minds in achieving their academic and professional pursuits.