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How to Prepare for a Data Scientist Interview?

Appearing for any sort of interviews could increase your adrenaline level. Cracking interviews need massive amounts of preparation and research. More so in the given scenario of appearing for a data scientists position, as only appropriate preparation and practice will get you cracking and performing well on the big day. If you are an aspiring data scientist, you are expected to have a working knowledge, or understanding, or the capability to perform over multiple firms, with a bag full of skills.

Continue reading to understand a quick step-by-step approach on specific areas of Aptitude, Technical know-how, and skill sets required to not only clear the interview but to also excel in the field of Big Data and Machine Learning.

The thing about data science is that its application, and hence expectation across industries varies to a large degree. The role is interpreted differently across companies, some might call a PhD Statistician as a data scientist, to others, it means proficiency in excel, while to some it may mean a generalist in Artificial intelligence and Machine Learning.

Step #1 read the Job Profile, specifically for Skills, Tools and Techniques. If the job description is not self-explanatory or in detail, then some research on the company is non-negotiable. Be clear as to what type of a data scientist position you are applying for.

The interview is usually a combination of an Aptitude Analysis, Technical Knowledge, Attitude Analysis.

The most organisation in recent times test the applicant on fundamental topics to gauge their fit in the company, attributes like Language Comprehension, Analytical Reasoning, Quantitative Aptitude etc…, can be easily cleared by reading up on the same to brush your skills.

Also Read : 5 Phrases to Avoid During An Interview

Step #2 Brush up on important and relevant concepts like these before the interview.

To test your technical understanding on the subject, most probably there will either be a technical round or an assessment, case study, which will essentially gauge your knowledge in statistics, programming, machine learning etc…, ensure you are fluent in relevant languages like R, Python, SQL, Scala and Tableau.

Step #3 will be to brush up on elementary topics like….

  • Probability – Random variables, Bayes Theorem, the Probability distribution
  • Statistical Models – Algorithms, Linear Regression, Non- Parametric Models, Time Series 
  • Machine Learning, Neural Networks.

So here, essentially you will be tested by the medium of a case study or discussion, on your problem-solving capabilities. It will help if you are able to define the problem for them on the presented scenario, and link the same to the suggested solution and its impact on business. While doing so, cite examples of case studies, or research papers for supporting the suggested solution.

Step #4, while you may come with the required skill sets and qualities, ensure through-out the interview you show the willingness to learn and flexibility in adapting to the current organisation, as Data Science and its applications are unique.

Step #5 to have a tight resume and pre-empt on ways you will link your experience with the given position during the course of the interview.

Step #6 is to carry out data science projects specifically if you are a fresher, there are many public domains available for the same. In addition, it is also advisable to take up MOOCs – Massive Open Online Courses to gain exposure to different as well as focused applications.

Remember, in recent times the role of a data scientist is viewed as someone who can bridge the gap between multiple features of a business. So it is not expected or required of you to be a specialist in all the aspects, but you should be able to link the features, ideate and provide solutions across domains. To stand apart in an interview you should not only show your individual strength and domain expertise but come across as a person with enough management skills, along with good communication and technical skills who can blend and get to the crux of a problem.

Related Article : Importance of Body Language during Interviews

  • March, 19th, 2018
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What are the career opportunities in the Fintech sector in India?

Emerging industries, which are famously known as sunrise industries in today’s time, are basically those industries that have emerged very recently and shown the potential of being the most lucrative industries for the society as well as the economy. Fintech or financial technology is one such sunrise industry, which has actually paved a novel way, away from the age-old financial services. The field is basically aiming towards disruption of banking processes, the way they are carried out in the present times and mainly want to provide digitally advanced services to the customers.

This field has showcased a huge number of profits as well as growth opportunities for those aspirants wanting to enter this industry. For instance, in the recent times, we saw a lot of high profile hires by many companies working in the digital field. PayTM hired Shinjini Kumar, to work as the Chief Executive of their payments banks which is supposed to be launched really soon. Flipkart, in order to boost its fintech business, made two high profile hires quite recently. PayTM even hired professionals who were working at powerful positions in global banks to head its leadership and management teams to help them get people on board of digital banking.

Also Read: Introduction to Fintech

The managing director of Manpower India, when quizzed about this field of fintech said, “Finance Technology is a booming segment in India with the opening of numerous mobile wallet companies, non-banking finance companies and now payment banks as well. All of these are running on robust digital platforms.” Thus it is quite evident that this field is all set to create a lot of new jobs which will be centred around mobile phones, generating a better user experience and also for the field of financial analysis.

The reason why there would be many career opportunities available at various positions in the field of fintech has its solution in numbers. Around 170 million Indians are active as well as passive users of smartphone and close to 160 million have an active access to the internet. Thus it is safe to say that India is getting on the digital platform with rapid strokes of interest. This, on the other hand, is encouraging more and more companies to come ahead and provide such digital services and products which not just help the customers but also make their experience a smooth one.

There are career opportunities available today in companies like Mobikwik, Capital Float, MSwipe, Citrus Pay, Ezetap and many other digital payment platforms. Many other e-wallet and e-commerce companies are being developed which will be providing similar kind of career opportunities for those interested in the field of financial technology. This is why more and more youngsters today are opting out for this kind of jobs as opposed to jobs where the traditional banking systems are followed. There are quite a few institutes today which help candidates get into this field like Imarticus Learning which is increasingly becoming popular.

Related Article: What are the Advantages of Learning Fintech

  • March, 16th, 2018
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Everything You Need To Know About Machine Learning and Deep Learning

Artificial Intelligence (AI), Machine learning (ML) and Deep Learning (DL), can be imagined as the three bears from Goldilocks staying together in a house, where each member has a specific use but yet conceptually they are interconnected. Artificial Intelligence is the big umbrella under which resides the Machine Learning concepts, and Deep Learning can be referred to as a sub-set of Machine Learning. So while Deep Learning and subsequently Machine learning comprises of Artificial Intelligence, the other way around is not necessarily true.

The field of data science is buzzing with these terminologies, and in all the noise it is very easily misinterpreted, and often Machine Learning and Deep Learning are used interchangeably for one another. One thing is certain that Deep Learning is a technique for implementing Machine Learning.

Also Read: Future of Machine Learning in India

Let us understand this by breaking down the puzzle….

Artificial Intelligence orchestrates the capacity of a machine to comprehend complex human tasks like, decision making, understanding spoken language, detecting fraud, in short, it enables a machine to imitate intelligent human behaviour.

Machine Learning is surely a part of AI, where it enables a computer to act in a specific way without the need for explicit programming. This is imperative as the volume of data is ever increasing and to keep up, the machine should have the capability of implementing effective algorithms which can effectively and efficiently make predictions by recognising patterns. To perform the same, data scientists have a number of existing ML methods or Algorithms which can be easily applied to any data problem, at the same time it can be applied to a number of real-life use cases, for example, recommendation engines, or applying Natural Language Processing (NLP) in chat logs.

Deep Learning is a subset of ML and when data scientist refers to the term deep learning they most often mean Deep Artificial Neural Networks or alternatively Deep Reinforcement Learning.

Deep Artificial Neural Networks are essentially a set of Algorithms which are popular in recent times, for setting new records in accuracy while dealing with complex problems like, Image Recognition, Sound Recognition, Recommendations Systems, etc…, To add on, one can easily define DL in a similar manner to ML, so it can be safely said that DL also enables a computer to act in a specific manner without the need of explicit programming, with the addition that DL ensures it produces results with higher accuracy.

DL is often more complex as compared to ML, the prerequisites to DL would be a high-performance computer and huge volumes of Labelled data to give reliable results.

ML can be used with a small volume data set and has a shorter training time, while DL will be effective with large volume data set and often requires a longer training time. In ML you can use your own features, so for example, if you need a computer to be trained on recognising an image of a cat, you will first need to key in all the relevant features of a cat into it. In DL you will need to feed the computer with large volumes of data with cat images, and the system will choose the features on itself which characterises a cat. Hence the training time is longer, while the chances of accurate information are higher due to the complexity of reaching the conclusion, in some cases, it is more accurate than humans.

Driverless Cars, Movie Recommendations and preventive health care are all possibilities enabled by Deep Learning. DL in the future could be responsible for machine assistance in possibly all aspects of life. Deep Learning has the promise of taking the application of AI from fantasy to reality.

Related Article: Skills Required to Learn Machine Learning

  • March, 15th, 2018
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What Are the Advantages of Blockchain Certification?

Today we are experiencing a new string in the revolution of information technology, which is of the Blockchain technology. Right now we are at a very nascent stage when it comes to accepting this technology, similar to the 1980s when the human civilization had just begun to understand the complex advantages of the World Wide Web.

It would be right to say that it was during those years when our digital economy received an absolute overhaul. Mainly leading to the emergence of companies like Yahoo, Google and Amazon, which made sure that the world never was what it used to be.

Also Read : Future of Blockchain Technology

How It Works

It was actually the virtual, secret currency or as we all know it, cryptocurrency which gave rise to the concept of Blockchain technology. This technology was more so developed as the nerve system of the whole field of cryptocurrencies like Bitcoin, which had emerged in the aftermath of the global economic crisis of 2008.

Although designed to only work in the financial arena, this technology has the potential too and at sometimes even taken over other industries, proving to be an absolute game changer.

Currently, we have about two blockchain technologies which are of immense importance in terms of the global scenario. They are;

  1. The Bitcoin blockchain: It has been devised in order to provide transparent accounting and easy transfer of money, especially in terms of the transactions that take place using the bitcoin.
  2. Ethereum blockchain: This blockchain does not just overlook the activities of transactions and accounts, but also deals with programming logic.

Also Read : Importance of Blockchain in Big Data

Potential Benefits of Blockchain to the Supply Chain

Considering the fact that this technology ticks all the boxes of being the technology of the future, there are more than enough reasons to learn it and get certified in it. Some of the reasons which also act as an advantage of getting certified in blockchain are;

  1. Blockchain technology does not need varied and different kinds of infrastructure. Rather, with the distributed ledger technology, both of these technologies have a universal infrastructure, which is more advanced than the others but at the same time integrates with the other processes as well. Thus this technology is changing the way data is shared among all.
  2. For many firms, investments in this field may be quite lukewarm in terms of returns right now, but at the same time, they are getting a perfect platform to create futuristic growth. Adopting this technology would lead to more flexibility, new capabilities and also lucrative enough to leverage it in the market in the future.
  3. The blockchain is also known as disrupting technology. This is mainly because of the fact that it would be readily encouraging transactions to take place between two parties, without the hassle of including an intermediary. Thus leading to a lot of players in the market to update their game.
  4. The blockchain is only confined to the field of finance right now, but there are quite a lot of possibilities for it to branch out into various other fields soon enough as well. Although it may take a few years, it is certainly going to ensure the change in the game.

We’re sure that these advantages that only a trained expert in blockchain technology would get, are more than enough a reason to get certified in it.

  • March, 13th, 2018
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What are the Advantages of Learning Fintech

In any market, when a certain industrial product or service is launched, there are a variety of reasons why it may work or may not work for the industry. This holds especially true in terms of any of the new technologies entering the market. The growth of such technological industries determines the influx of new players, some of whom may come in with a silver spoon in their mouths, basically turning everything they touch into gold, great turnovers, fabulous mergers and acquisitions and so on. At the same time, there are also a number of failures and flounders in the industry.

The fintech industry is not a very new one and has been through its fair share of ups and downs. In spite of a little while of a slump in the middle, there are many ways in which the fintech industry has strived and turned its trade positive in order to come to be thriving in the present times. One of the main reason why this industry has seen more ups is that it catered not just to the big guns but also to the small business owners which included all the disadvantaged sections of the society, women, minorities and immigrants.

Also Read: Introduction to Fintech

This industry is going to grow on and be stronger, which is why there are many experts who believe it is advantageous to get certified and get into this industry.

Here are a few reasons why we believe there are great advantages in learning Fintech;

  1. Financial technology has been criticised in the sense that it would not see a large number of growth and developments in the future. But the majority thinks otherwise. The reason that fintech is actually going to be there in the industry for a much longer time is the very fact that banks are getting digitalized and they are doing so at an alarmingly fast rate. The industry is no longer at the innovator stage and is more at an adoption stage. Thus getting certified to work in this industry will prove extremely advantageous.
  2. Fintech companies or those organizations that are involved in this industry don’t really have the rules of capitalism apply to them. This is mainly because of the fact that, in capitalism, there is the chance of companies getting explosive dividends and later on also going bust. But in case of fintech whenever a void is created, there would be a number of alternative lenders to jump in to fill it up. This is the reason why the field of fintech which does not follow a ‘growth at all costs’ mentality will definitely flourish both in terms of growth and job opportunities.
  3. The world is getting digitalized on a massive scale and today no one really has any time for actually getting their transactions done from slower, larger financial corporations anymore. Technology has touched every single sphere of life including the sphere of banking. This is why learning the various nuances of fintech would be most definitely an advantage for candidates entering into this new world of technology.

The above reasons are why learning fintech is a great option for candidates looking to get into the Industry today.

Also Read: Is a Career in Fintech Your Future?

  • March, 12th, 2018
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Introduction to Fintech

Fintech is the popular abbreviation for the terms, financial technology, which is currently considered as one of the trendiest fields to work for in today’s digital age. This is mainly because of the fact that financial technology has the potential to revolutionize and bring in massive changes in the lifestyles of people as well as in the ways that they conduct business.

Those companies which work in the arena of fintech are usually involved in the offering of products and services, which are usually offered by financial institutions. But they are doing so by offering these very services by leveraging technology and thereby making them much more innovative as well as affordable.

The main reason for the field of fintech to emerge was the colossal amounts of cash that was being pumped into the economy in the past few decades. The purchasing power of people and disposable cash at their hands was growing manifold, which was what made venture funding and capital investments increase so very much at the same time.

Related Article : Is a Career in Fintech Your Future?

Fintech is basically referred to as a broad term which is mainly used to describe those companies that usually apply cloud-based tools, open source software and other various kinds of technologies in order to improve the field of banking and finance. This field is considered to enough potential to bring in a revival of the current financial system. Which is why many regulators have been working to strike a proper balance between protection and innovation.

This technology basically is aimed at as a competition to the traditional methods of finance and financial services. Various electronic devices like smartphones and technologies like mobile banking, investing services, cryptocurrency is such services which usually end up under the ambit of financial technology. It also involves a number of start-ups as well as various companies which are involved with finance and technology companies all of which are trying to enhance the quality of services delivered in the present times.

The definition of fintech is, “it is a new financial industry that applies technology to improve financial activities.” The main medium of work here is the internet, where all the services produced and marketed are supposedly functional through the same. The various areas in which you would find here in would be insurance trading and risk management. There has been an increased investment for both the development as well as the expansion of this field in the recent times.

The various startups that happen to be working in this field are Lufax from China, Square, Stripe, Zenefits, Social Finance, and Credit Karma in the USA and POWA Technologies in UK, Adyen in Netherlands, Klarna in Sweden, One97 Communications in India and Coupa Software in America and Funding Circle in United Kingdom again. These are just a few of the many start-ups striving in this field. This diversity of start-ups is one of the main reasons why there are so many professionals seeking to get trained in this field and get certified for the same.

Related Article : How to Start a Career in FinTech?

  • March, 10th, 2018
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Future of Blockchain Technology

You must have heard about the new and emerging forms of currency in the economy today, which is more popularly known as a cryptocurrency. Bitcoin is one of the types of cryptocurrency which has become extremely famous among the rich and famous as well as those involved in the finance industry today.  This cryptocurrency has brought in a whirlwind of a revolution in the industry of finance mainly due to the fact that it has introduced a payment system which does not really need any firm or individual or bank to function as an intermediary.

This peer to peer payment system makes use of a technology called as blockchain technology, where the identity and transaction details of both the parties are effectively protected. It is believed that blockchain technology has a great future, especially in the financial industry owing to its mechanisms of storing legitimate information in such a way that it can be traced thoroughly. There are many experts in the industry who claim that bitcoin would soon do to the field of finance, the exact same thing that was done by email for communication around the globe.

Also Read: Importance of Blockchain in Big Data

Banks although are extremely apprehensive about dealing with blockchain as there aren’t many countries which have still not accepted bitcoin as a legal tender due to its many liabilities, but there are great chances of rapid adoption of this technology in the near future. This technology has immense potential especially when it comes to reducing the cyber risks by offering various types of identity authentication methods, which would be offered through a visible leger.

The future would definitely see blockchain technology being brought in to the mainstream all thanks to electronic ledgers, which would do the job of numbering, maintaining as well as indexing all of the records and communicating the information that is stored in all of them. Smart devices can also make great use of blockchain technology in the future. For instance, a refrigerator can do a lot more than just storing food. It could track its own warranty, call for its delivery of the various food items that are required by the household and so on.

Did you know that blockchain can do a lot more than just restricting itself to finance? There is a great application of blockchain in the sphere of crime, wherein its software can be so developed so as to enable the speedy catching of criminals and reducing the amount of money spent on catching them on a regular basis as well.

There is a huge potential in this technology to new opportunities for employment in the industry as well as increasing the ability of professionals to innovate a lot more. It has an immense potential to transform the world into a much smaller place as it goes on to increase the speed and the efficiency of the transactional activity. The future of blockchain encompasses even the governments of the countries worldwide.

Also Read: Blockchain Revolution: Prosperity in the Era of the Internet

  • March, 9th, 2018
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What is Big Data and Business Analytics?


Big Data has the potential to dramatically change the way organisations are making decisions, with the use of information and insights from it to enhance customer experience and build effective business models. No wonder then that Big Data is known as the most important technology trend of recent times. Does this mean that Big Data is this marvellous invention of today? Well not really. It is true that most organisations now understand the potential of capturing data that generally streams into their business, so that they can apply analytics and get significant value from it, but even as long ago as the 1950’s, way before the term big data was even whispered, its concepts were in use on a smaller scale. Businesses were using business analytics, in its basic form, over spreadsheets manually created, to uncover insights and trends.

So why is this buzz around big data now? Quite simply because of the speed and efficiency it offers. While years ago analytics could be done over the accumulated data, but the method would only allow making a future prediction for their business. Today business can identify insights for immediate consumption. It is the pure ability to work quickly and stay responsive, is what gives the organisations the competitive edge which was lacking before.

Big Data is not a single component, as accumulating information is easy in today’s time and technology. Big Data is a combination of Data Management Technologies that have evolved over time. When organisations talk about Big Data they mean, To Store, To Manage, and To Manipulate, humungous amounts of structured and unstructured data at the right speed and the right time to get the right insights.

And thus Business Analytics or Big Data Analytics gains importance. It is business analytics that makes it possible for the organisations to connect to their data, and use it effectively to identify new opportunities. Which further leads to a better business environment, where you can make informed decisions, create an efficient operations environment, gain higher profits, and acquire happy customers.

Companies using Big Data Analytics gain value by…….

Cost Reduction, Cloud-Based Analytics, Hadoop, and similar technologies can not only bring down the cost of storing large amounts of data but at the same time they can bring about more ways of doing business.

Quicker Decision making, with the availability of in-memory analytics, and to add to that the ability to analyse the new sources of data, businesses can analyse real-time data, and make immediate decisions based on what they have learnt.

Segmented Products and Services, the power of analytics is that it can gauge customer needs so that organisations can create product catering to specific needs of the said customers.

The only pitfall that organisations applying big data analytics initiatives need to be alert on, is the lack of internal analytics skills and the high cost of hiring experienced data scientist and data engineers to bridge the gap. If you are a fresher looking at career opportunities, with interest in data analytics, then getting yourself trained in techniques of Big Data Analytics, will be a fantastic career choice.

  • March, 8th, 2018
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What Is A CFA Course? | Benefits of CFA Courses

CFA or Chartered Financial Analyst is a credential that is offered as a part of the CFA program. Apart from being a program which is recognized globally, CFA provides its holders with a strong foundation of skills in investment analysis, portfolio management as well as the practical knowledge that a candidate would require in the present day investment industry. Being a CFA holder makes you a part of this worldwide network of professionals who believe in following professional and ethical standards of the highest degree. Clearing all three levels of this examination doesn’t just land you the certificate, but it is also a testament to your professional qualities.

There are a number of eligibility criteria, for all of those who wish to give this examination. The criteria are as follows;

  • An applicant applying for this exam must have a bachelor’s degree or a degree equivalent to that of the bachelor’s.
  • If a candidate doesn’t hold the bachelor’s degree, the candidate must be in the final year of their degree at the time of the registration.
  • Have at least four years of qualified professional work experience.
  • Have a combined experience both in terms of college activities or work, the total of which would be four years. Any summer, part-time or internships positions do not make the candidate qualified enough to apply for the exam.

Moving ahead, let’s discuss what exactly the syllabus for this exam includes, if we were to put it all in a nutshell, it would be;

  • Investment tools
  • Ethical and Professional Standards
  • Economics
  • Portfolio Management
  • Equity
  • Fixed Income
  • Derivatives
  • Alternative Investment

Now once you commence your journey of becoming a CFA holder, you could take two paths. You could either attempt to crack the exam on your own through self-study or you could opt for cracking the exam with the help of an institute. India has some of the most renowned institutes which offer comprehensive courses in CFA certifications like Imarticus Learning, which you could opt out for. The general course of study involves candidates having to study the Candidate Body of Language, the curriculum content, learning outcome standards and the topic area weights.

This course includes three varying levels of examination which a candidate is supposed to clear in order to become a Charter holder. This is how the three levels are divided;

  1. Level 1: This level is usually focussed on a basic knowledge of the ten topic areas that are provided as the syllabus as well as a very simple analysis done using the investment tools.
  2. Level 2: This level lays a major emphasis on the application of investment tools as well as the concepts with more of a focus on the valuation of all types of assets.
  3. Level 3: The last level usually is supposed to focus on the synthesis of all the concepts and the analytical methods which are used in various applications for an efficient portfolio management and wealth planning.

Once you pass this examination, the doors of global opportunity open up for you by providing you with an access to a global network of qualified professionals and lucrative job prospects.

  • March, 7th, 2018
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What is The Meaning of Business Analytics?


What is the meaning of business analytics? According to the definition of business analytics, it means, “The study of data through the statistical and operations analysis, the formation of optimization techniques and the communication of these results to customers, business partners, and college executives.”

In technical terms, business analytics is supposedly a quantifying mechanism, which works with big data and performs various functions of business modelling and decision making for furthering the business prospects of various companies. Big data basically refers to a huge volume of data, meaning information which could be both in a raw format or a proper structured format. This is also known as unstructured data and structured data in the business analytics jargon.

This information that is available on such a massive scale to companies, is usually used by them by the method of analysing of the same. When firms analyse this information, they are basically making use of business analytics to do so. This way once the process of analysis is done, the companies are able to get the proper insights that are required for them in order to take more effective business decisions and strategize in terms of their future endeavours.

More and more companies have begun to make use of business analytics, in order to make data-driven decisions these days. As the process of business analytics is actually able to mine this data, process it and derive the proper kind of insights, which then help the companies in achieving the much sought after competitive edge over their contemporaries. This is the reason why more and more firms and professionals today are getting attracted to the process of Business Analytics or as it is popularly known BA.

Business Analytics gains importance. It is business analytics that makes it possible for the organisations to connect to their data, and use it effectively to identify new opportunities.

Which further leads to a better business environment, where you can make informed decisions, create an efficient operations environment, gain higher profits, and acquire happy customers.

Companies using Big Data Analytics gain value by…….

Cost Reduction, Cloud-Based Analytics, Hadoop, and similar technologies can not only bring down the cost of storing large amounts of data but at the same time they can bring about more ways of doing business.

Quicker Decision making, with the availability of in-memory analytics, and to add to that the ability to analyse the new sources of data, businesses can analyse real-time data, and make immediate decisions based on what they have learnt.

Segmented Products and Services, the power of analytics is that it can gauge customer needs so that organisations can create product catering to specific needs of the said customers.

Business Analysis

The only pitfall that organisations applying big data analytics initiatives need to be alert on, is the lack of internal analytics skills and the high cost of hiring experienced data scientist and data engineers to bridge the gap. If you are a fresher looking at career opportunities, with interest in data analytics, then getting yourself trained in techniques of Big Data Analytics, will be a fantastic career choice.

For companies, in particular, this field offers a host of benefits in terms of conducting various procedures such as data mining, completion of statistical and quantitative analysis in order to discern how results actually are achieved. Business analytics even helps companies by testing all of the previous decisions by using multi-dimensional testing methods as well as predictive modelling and predictive analysis in order to forecast future results.

It is this very field of operations which provides firms with the support that they need in order to make the most proactive and tactical decisions and also to make their decision making processes automated, in order to enable them to support all the real-time responses.

Business Analytics

Another concept which is quite similar to business analytics is business intelligence. Here it refers to only and only the process of collection of data from all of the sources that are available and only preparing it for Business Analytics. This includes automating and monitoring of all the sources basically for the main purpose of analysing them and then being able to provide proper results and insights for the same.

Today as the presence of data in our world becomes quite strong enough, there are a number of professionals who actually go get certified in business analytics from many esteemed institutes like Imarticus Learning in order to enter this field.

  • March, 5th, 2018
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