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Risk underwriting teams: How are risks assessed?

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Risks assess by underwriting teams, which are composed of experts in risk type. For example, the commercial team will determine risks related to commercial clients, while the retail group will evaluate risks for retail clients. This blog post will explore how these professionals assess risk types with a focus on defining specific terms.

Understanding these terms is vital for both people considering new lines of business and those who want to improve their current practices to analyze risk levels better and make more informed decisions about what they can offer clients.

The factors on which risk assets depends

Lending & Credit Products

Lenders use a formalized approach to assess the creditworthiness of an individual or business borrower based on their behavioral and financial history. This information collects in a credit report, which summarizes credit history over time with a scoring model that assigns a 300-850. Anything below 600 is considered subprime, and 600-700 is considered near-prime or “second chance” lending. For example, if there is a credit card user with a score of 700, they are likely to pay their monthly payment on time but may carry an unusually high balance on the card at a time when interest rates are low.

Credit reports look at certain factors that may signal higher risk to lenders, such as missed payments on loans or credit cards, requests for new credit lines, and lack of repayment history on existing lines of credit.  If there is a pattern of credit denials, then the person or business may be considered less likely to repay future loans.

Credit reports also provide insight into how borrowers manage their budgets. For instance, individuals (and businesses) with high debt levels relative to their income are at higher risk because they must simultaneously make payments on multiple loans. It reduces their ability to repay all of their obligations on time.

Personal guarantors

If an individual or business doesn’t have a strong enough credit history to meet the lender’s criteria, they may get a loan if they secure it with collateral such as real estate. Lenders will assess this risk and determine whether the asset’s value is enough to cover the total amount owed in case of default.

Credit analysis

This term comes from credit underwriters and refers to a more detailed review of the borrower’s to repay a loan based on cash flow projections and other information such as documentation about assets and liabilities. These professionals typically look at all the borrower’s financials, including income and living expenses.

Capital Markets Products

Products that fall into this category include bonds, stocks, and derivatives such as futures and options. For example, a corporation issues a bond with a face value of $1 million to raise capital to fund its operations. As the corporation repays the loan, that $1 million returns to bondholders. Underwriters analyze a corporation’s credit history and financial documents as part of their decision to evaluate whether to issue debt (bonds).

Enroll today in a Credit risk underwriting course with Imarticus Learning

The only program in the world teaches students all they need to know about lending, credit risk analysis course, credit management, legal and regulatory requirements, and the influence of new-age technologies. They can acquire a robust toolbox that helps students grasp India’s credit management course online, study the whole loan evaluation and due diligence process. Therefore students can conduct financial analysis through the Credit Risk Analysis Course and Credit management Course online.

Some course USP:

  • The Credit risk underwriting course lets the students learn job-relevant skills that prepare them for an exciting career.
  • Impress employers & showcase skills with a certification endorsed by India’s most prestigious academic collaborations.
  • World-Class Academic Professors to learn from through live online sessions and discussions. It will help students understand the practical implementation with real industry projects and assignments.

How Can A Supply Chain Management Course Help Professionals?

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Supply Chain Management is a relatively new concept in the business world, but it has become increasingly important. Supply Chain Managers are responsible for ensuring that items and materials never run out. They work to ensure that their company is profitable by keeping costs low and having enough products to sell.

A supply chain management course can help professionals learn how this process works and give them an edge in the job market!

Supply Chain Management: An Overview

Supply chain management is a profession that has been gaining popularity over the past few years. The supply chain refers to the process of delivering goods from suppliers or manufacturers to customers. The supply chain may also include warehousing, production, and distribution, as well as retailing. This industry encompasses everything from sourcing raw materials for manufacturing products to how those products are marketed and sold at stores after they have been manufactured.

Supply chain management is a process that links the production and distribution of goods, materials, and services. The goal is to deliver what the customer needs as efficiently as possible. The process helps companies to manage the flow to help maximize efficiency.

Supply Chain Management Career: An Invincible Option

Organizations always look for ways to increase production while reducing costs. A supply chain management course can provide professionals with an understanding of how retailers work together to meet consumer needs.

Here is how a supply chain management course can help professionals:

supply chain management and analytics course by IIT, RoorkeeEfficient Collaboration: To swiftly and effectively deal with issues when they arise, it is vital to maintain a smoother flow of information across the supply chain to avoid any miscommunications and confusion.

Quality control improvements: To source better components and services, you must have better awareness & control of different links in the supply chain within your processes.

Keep up with demand: Supply and demand are factors that fluctuate in counter-intuitive ways. Improved data analysis & communication between producers, sellers, and suppliers can reduce the chance of supply hitting a bottleneck.

Cost Reduction: Improvement in quality control and inventory management brings along lower overheads & allows better optimization for profitability.

Mitigate risks:  A supply chain certification helps you figure out how to predict new challenges, for example, a supplier going out of business. Professionals can efficiently prepare for any unpredictable situation and minimize inefficient risk mitigation costs like unnecessary stockpiling.

Transform your SCM Career with Imarticus Learning:

If you are passionate about a supply chain management career, the Professional Certification in Supply Chain Management and Analytics course you need to enroll in today! The program has been designed in collaboration with DoMS and E-learning Centre, IIT Roorkee, and experienced industry leaders. The system provides a cutting-edge experience to candidates who wish to enter the operations and supply chain industry.

supply chain management and analytics courses by IIT, RoorkeeSupply chain certification enables professionals to make data-driven decisions at strategic, operational, and tactical levels. In the Supply Chain Management field, there is a shortage of professionals with process and analytics talents. This certification prepares you for high-demand job roles such as Demand Planner, Data Scientist, Supply Planner, and Supply and Operations Planner.

USP’s of Supply chain Management course

  • Master SCM know-how & much-needed skills in analytics through this cutting-edge curriculum designed by the DoMS & E-Learning Centre, IIT Roorkee.
  • Learn from one of the best faculties in India through live online sessions and discussions.
  • Get an opportunity to participate in the 3-day campus Immersion module to visit the IIT Roorkee campus.
  • Solve complex real-industry problems demanding a thorough understanding of concepts, mastery over a skill, and understanding the business context.
  • Supply chains generate massive amounts of data – Big Data, to be more specific.

For further details, contact us through the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, and Gurgaon.

Fundamentals: What does a Business Analysis Plan Contain?

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A Business Analysis Plan is a document that contains information about the business analysis process. A plan usually starts with a problem statement and then outlines solutions, research findings, and recommendations for improvements.

This blog post aims to understand what comprises a typical business analysis plan by providing an example of one. In addition, we’ll explore how these plans are beneficial for businesses both large and small alike. So let’s get started!

  1. The first and most important part of a Business Analysis Plan is the problem statement. The problem statement answers the following question: What is currently happening in your company that you would like to be different? For example, you work at an e-commerce store called Amazon, and one of our problems is slow checkout processes. A reason for this could be that servers cannot handle all of the traffic you get during peak hours. So, the problem statement might look something like this: “The checkout process takes too long at Amazon.com’s peak hours.”
  2. The next section is called proposed solutions. It is where you would state how you plan to resolve the problems outlined in the previous step. Possible things that include here are additional servers or changes to existing systems. If you wanted to add more servers, one solution might be to ask another company to provide extra computing power during peak hours through an implemented cloud system.
  3. The third section is called research findings, and it should include details about the project’s environment. This information will help you and others better understand the state of the business analyst training involved with your analysis work. Imagine that you have a company called IKEA, and their customers are families looking to furnish their homes.To better determine customers’ problems, research findings could include customer interviews where they asked them questions about their home decorating habits and any challenges faced when furnishing their homes. This information then allows you to create a plan that caters more directly to your customers’ wants.
  4. The next section is potential solutions which include possible approaches for finding optimal solutions. You might want to consider creating high-level solutions for each problem is solved. For example, if you are looking to improve the checkout process at Amazon, some potential solutions would be implementing an online chat service, adding more servers, or having employees work overnight shifts.
  5. The final part is called the implementation plan, which includes details on how your solution(s) deployed and the expected outcome after implementation is complete. It should describe how your solution addresses the problems outlined in Step 1 and any other benefits customers could experience from using a said solution.

Enroll today with Imarticus Learning

The Agile Business Analyst course is a six-month program that will prepare the student for the tasks of an Agile Business Analyst. This placement-driven program teaches students to handle modern business analysis processes with appropriate tools and approaches through several case studies, role-playing activities, and business analyst training.

This program features a one-of-a-kind pricing structure in which students pay their fees only when they get a job offer with a minimum income of 5 lakhs per annum, with the possibility of earning up to 12 lakhs per year.

Some course USP:

  • The Agile business analyst course lets the students learn job-relevant skills that prepare them for an exciting Analyst career.
  • Impress employers & showcase skills with a certification endorsed by India’s most prestigious academic collaborations.
  • World-Class Academic Professors to learn from through live online sessions and discussions. It will help students understand the practical implementation with real industry projects and assignments.

How can a machine learning and artificial intelligence course help you become a social media analyst?

Posted on by Imarticus Learning

Social media has become an integral part of our lives. It is how we keep up to date with the world, and it is also a way for businesses to promote their products/services. With all of this in mind, many people are looking for ways to get into the social media industry.

One of the popular routes is through a job in social media analysis. Social media analysts are becoming more and more important as time goes on. This position requires you to monitor and analyze data on your company’s various social channels.

Thus, machine learning and artificial intelligence courses are becoming more popular among people looking for a potent solution.

How AI and ML are used in social media?

Social media is a very lucrative and competitive industry. Those who can best analyze data, find useful patterns and insights into the business end up earning the most money. This has led to many big players such as Twitter, Facebook, and LinkedIn investing heavily in AI systems that help them better understand their users’ behaviors without even gathering any specific user information!

Social media marketing agencies also use these analytics tools for understanding consumer behavior around products or services offered on social channels like Instagram & Snapchat. The same technologies are used by internet giants like Amazon and Google to offer seemingly personalized search results with just one keyword input from anyone trying out something new online – be it buying a product or browsing through material freely available on the web!

This ongoing trend of personalization based upon customer behavior and interests has made AI a huge part of our lives today.

How do ML and AI courses help you become a social media analyst?

Many companies are now looking for social media analysts to help them understand consumer insights and market expansion opportunities. If you want to become a successful analyst, it is important that you learn how machine learning and artificial intelligence can aid your efforts as marketers in various ways.

Here’s how ML and AI help you become a social media analyst:

Track consumer behavior patterns. ML and AI help you understand the behavioral pattern of your customers by tracking their social media activity. This information enables you to make a business decision or product development strategy that will help gain customer attention in the future!

Increase ROI with AI-assisted marketing campaigns: ML and AI will help you identify the best marketing campaign to increase your brand exposure. You can use AI-driven tools such as chatbots, ads bots, etc., for effective customer engagement using social media platforms like Facebook or Twitter!

Use Sentiment Analysis: You can easily understand consumer sentiment by tracking what they say about a product on different platforms with ML assistance. This information is crucial in understanding their needs so that you can provide them with better quality products/services!

These were just some of the many ways how ML & AI courses can help you become a successful Social Media Analyst!

Elevate your social media analyst’s profile with Imarticus Learning

Imarticus Learning offers Machine Learning and Artificial Intelligence courses. The comprehensive curriculum of these courses will help you build a strong foundation in machine learning, data analysis, deep learning, and artificial intelligence to take on complex problems for social media strategies.

What’s unique about this AI ML certification course?

  • Cutting-edge curriculum and certification by E&ICT Academy, IIT Guwahati
  • Opportunity to participate in campus immersion module
  • Learn what new-age AI & ML Engineers do in a real-world scenario
  • Build an impressive AI & ML project portfolio for future employers

This comprehensive program can take your career a step ahead towards rewarding opportunities in this domain.

What is Scope Vision in Business Analytics?

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Business analytics is the process of analyzing data to make better decisions about business performance. Analytics can use in various fields and industries, such as healthcare, marketing, and sports. This post will explain the Scope and Vision of Business Analytics.

Who is  Business Analyst?

Business analysts encompass a wide range of business professionals. Analysts have a unique opportunity to contribute to many different functions within an organization, from sales and marketing to human resources and finance.

Analysts typically work on projects involving the following tasks:

  • Conducting needs analysis
  • Managing change initiatives
  • Managing projects

What is the Scope of Business Analyst job responsibilities?

Analysts’ job responsibilities are to be the liaison between Business and IT by capturing its requirements. Analysts can be involved in all areas of the project life cycle, starting from business strategy analysis, understanding the problem statement, and ensuring that required processes are defined correctly, leading to successful application implementation.

Few Scope of Analyst job responsibilities can be defined as follows:

Business analysts typically perform the following activities:

  • Business strategy analysis
  • Business case/Business opportunity review
  • Defining requirements
  • Creating process flows and Data flows diagrams
  • Mapping data and processes

Business Analyst Scope and Vision

The Business analyst must be working closely with the client to understand their business needs and which solution will best fit their requirements.

The analyst’s Scope and vision are to understand the problem in detail, and the Business requirement document should be able to communicate Business requirements.

Business Analyst Roles & Responsibilities:

Individuals who work as business analysts in India expect to assist in strategic planning through real-time analysis. A business analyst’s role and functions are as follows:

  1. The BA collaborates to identify quality and enhance operations.
  2. The BA is also engaged in the business system’s development and maintenance.
  3. Their primary responsibility is to collect, document, and analyze a variety of business needs.
  4. They assist in the resolution of business issues as needed and the development of technological solutions.
  5. They also assist with system testing and the creation of system documentation and user guides.

How to get Business Analyst Certification?

Students always have a query on how to get a Business Analyst Certification. Students can get a Business Analyst Certification by pursuing the course from a reputed institute.

Imarticus Learning provides a Business Analyst course with placement assurance. This certification will teach students how to use their knowledge and skills to help businesses achieve success by analyzing their needs!

Enroll Today with Imarticus Learning!

The Agile Business Analyst PG Program is a six-month program that will prepare students for an Agile Business Analyst role. The Agile Business Analyst course with placement assistance teaches students to handle business analysis processes with practical tools. It approaches through several case studies, role-playing sessions, and hands-on learning. Students can get hired at top companies and start-ups with salaries ranging from 5 to 12 lakhs per year.

Some course USP:

  • The business analyst course lets the students learn job-relevant skills that prepare them for an exciting Analyst career.
  • Impress employers & showcase skills with a certification endorsed by India’s most prestigious academic collaborations.
  • World-Class Academic Professors to learn from through live online sessions and discussions. It will help students understand the practical implementation with real industry projects and assignments.

Contact us through the live chat support system or schedule a visit to training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, and Gurgaon.

Why Should Engineers Learn Data Science Differently?

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Why Should Engineers Learn Data Science Differently?

Data science and engineers have a lot in common. They both need to know how to collect, store, analyse and visualize data. Engineers are taught these skills as part of their curriculum; however, they may not learn them as they would if they were learning Data Science from the start. The following is an overview of why engineers should learn Data Science differently than other disciplines.

A blog post intro paragraph engages professionals about why engineers should learn data science differs from other disciplines. Engineers are taught these skills as part of their curriculum but may not understand them simultaneously or efficiently without exposure to them earlier in life.

Why is Data Science important for Engineers?

Engineers always like to think about their work in processes and systems, also known as Systems Thinking. It is what enables them to build more efficient products by efficiently running those processes. By thinking of the world in this way, engineers can quickly solve data-related problems because they see all sides of an issue that deals with data.

It’s important to remember that engineering can be applied in any industry, including Data Science. As a data scientist, it’s often necessary to run specific processes and analyze the results. Engineers excel as they can take these processes and incorporate them into the current system that the company may already have set up, saving time and money in some cases.

Benefits of Learning Data Science for engineers.

Therefore it is necessary to run specific processes and analyze results where engineers excel in taking these processes and incorporating them into current systems that a company may already have set up.

Learning Data Science is important because of the benefits that engineers will gain. Engineers overall will be able to learn more efficiently about their field and how it fits into the bigger picture. By taking this information, they will be able to make smarter decisions in data-related situations.

Engineers should learn Data Science differently from other disciplines because it will make them understand better and more thoughtful about their field and how it fits into the bigger picture, enabling them to make smarter decisions in data-related situations.

Why Enrol in the Data Science program at Imarticus learning

Industry specialists created this postgraduate program to help students understand real-world Data Science applications from the ground up and build robust models to deliver business insights and predictions. The Data Science program is for recent graduates and early-career professionals (with 0-5 years of experience) who want to pursue Data Science and Analytics, one of the most in-demand fields.

Twenty-five in-class real-world projects and case studies from industry partners will help students become masters in data scientist careers. Exams, hackathons, capstone projects, and practice interviews will help students prepare for placements.

Some course USP:

  • The course lets the students learn job-relevant skills that prepare them for an exciting Data Scientist career.
  • Impress employers & showcase skills with a certification endorsed by India’s most prestigious academic collaborations.
  • World-Class Academic Professors to learn from through live online sessions and discussions. It will help students understand the practical implementation of real industry projects and assignments.

Contact us through the live chat support system or schedule a visit to training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, and Gurgaon.

What Are Some Fintech Companies?

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The Basics of Fintech

At the very core of any technological evolution is a determination to provide something better than what already prevails in the market. Can you think of any industry that is not influenced by technology? I am wondering it’s very hard to think of one. Fintech is the short form of Financial Technology, meaning the use of technology in the financial domain to provide better finance-related services over tthe traditional methods.  

The Fintech industry comprises companies and start-ups that are focused on providing solutions to various problems that exist in the industry. The bottom line of using cutting-edge technology in the financial domain is to provide more efficient services that could work in conjunction with our fast-paced world, ultimately increasing customer satisfaction. Let’s dig more into the players in the Fintech industry who are revolutionizing how people use banking and financial services.

Players in the Fintech Industry

Some of the key players in the Fintech domain are mentioned below.

Ant Financial 

One of the major global players in the Fintech industry is based in China. Established in October 2014, Ant Financial Services Group is on a mission to bring inclusive financial services worldwide. It is also the official operator of Alipay, the digital payment portal by the Alibaba group for its e-commerce platform.

Xero

Xero is one of the fastest-growing software as a service (SAAS) provider worldwide that already has more than 2 million subscribers. Founded in the year 2016 in New Zealand, it aims to provide accounting solutions for small and medium business enterprises through its cutting edge software technology. Xero has also backed the title for the World’s Most Innovative Growth Company in 2014 & 2015 by Forbes.

Avant

Founded in the year 2012, Avant is one of the key players in the Fintech domain. Originally registered as AvantCredit, Avant is a Chicago based Fintech firm that provides online credit solutions for customers. On a mission to eradicate the obstacles in the borrowing process and minimize the cost of borrowing for individuals, Avant brings more transparency to the whole system through its revolutionary technology. 

Tala

Tala is a game-changer in the Fintech domain for providing micro-loans through its smartphone application. Founded in the year 2011, Tala has a customer base like no other, it provides credit facilities to people in the remotest parts of the world. On a mission to expand financial access and choices to billions of underserved people worldwide, Tala is using technology for the best! 

PayPal

One of the most prominent players in the industry, PayPal was the harbinger of the Fintech revolution. With a customer base of more than 277 million active users, PayPal believes in empowering individuals and businesses to connect and prosper in the globalised economy through its digital financial services platform. It adds value by enabling individuals and merchants to indulge in monetary transactions in multiple currencies worldwide.

Stripe

Stripe is a US-based Fintech company that was founded in the year 2009. It uses its software technology to provide payment solutions for individuals and business owners that help to receive and make payments online. Stripe has built a customer base in the e-commerce domain by catering to the payment solution needs of the online business owners.

Robinhood

Robinhood is a US-based Fintech firm that provides investment solutions through its mobile and web applications. It was founded on the core principle of increasing participation of people in the finance industry through commission-free access to investing. Robinhood is a fast-growing company that already has a customer base of more than 6 million active users, a major percentage of which belongs to the millennial population.

 

What Are the Algorithms in Machine Learning? How Does It Work?

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Machine learning is a vast field comprising of various data related operations such as analysis, prediction, decision making and much more. These applications require a set of well-defined steps to proceed with the idea designed for model construction. A set of well-defined instructions that produces some output or accomplishes a particular task is called an algorithm. The machine learning algorithms are broadly classified into 3 categories – Supervised, Unsupervised and Reinforcement Learning.

To choose an appropriate algorithm in machine learning, identifying the kind of problem is very necessary as each of these algorithms obeys a different plan of attack to deal with the proposed problem. Supervised learning uses an approach where the output is already known to the user or the individual while unsupervised learning concentrates on the concept of similarity in properties of the objects. Reinforcement learning differs from both of them and uses the art of learning from experiences.

Supervised learning

Supervised learning is used in machine learning tasks such as classification, regression, and analysis. It is considered as a concept that deals with labeled values. This means that the objects are categorized or assigned to different classes based on their properties. The algorithm implementation in supervised learning is done by a two-step procedure namely model construction and model utilization.

Firstly, the given data is cleaned and divided into training and testing sets. The model gains the ability to produce output by learning from the instances contained in the training set. The test set gives a measure of the model performance by producing accuracy. The accuracy indicates the amount or rather the percentage of unseen data that was computed correctly by the applied algorithm.

There are several metrics to determine the performance of the model and improve it if the performance is not up to the mark. This includes performing tasks like cross-validation, parameter tuning, etc. Hence, we can conclude that supervised learning uses labeled classes and target values to classify an unseen data point.

Unsupervised learning

In contrast to the supervised approach that already knows the predicted outcome, unsupervised learning uses the basis of similarity in properties to classify the unseen data points in the given n-dimensional space.

The main idea is to take a data point that is new to the given space, extract the behaviors of the data point, compare it with the already existing properties of the other objects and accordingly classify or categorize them into the appropriate group. The common examples of unsupervised learning are clustering, Apriori and K-means algorithm.

Reinforcement learning

Reinforcement learning is very similar to the animal kingdom where the animals do not train their offspring to perform a particular task but they leave them out in the ecosystem to learn from the experiences that it gains while struggling to accomplish a particular task.

The basic idea of performing reinforcement learning is to let the model learn on its own. It uses a trial and error strategy to gain knowledge from the available environment. According to the experiences gained from the conditions, it is exposed to, appropriate predictions and decisions are made. Markov Decision Process is an example of reinforcement learning.

Conclusion

Because of the wide variety of applications offered by machine learning, there are several Machine learning courses dedicated to offering the training in machine learning algorithms so that an individual can recognize the problem efficiently and work towards building an appropriate solution. Learning and understanding of machine learning algorithms are very easy. It just needs a proper classification of the interest in performing the desired operation.

Why Big Data Analytics Is a Good Career Move?

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Data is wealth, this doesn’t sound hyperbole in the modern-day scenario. A data analyst turns raw data into meaningful information that enhances the business and market share and who doesn’t want to grow? Let us look at the key points discussed in the article justifying Big Data Analytics as a good career choice.

Statistics indicate that the average salary of a data analyst in India is 10 lakhs per annum and this salary will keep on growing as you level up. There is a demand for candidates in this corporate world who have good command over big data and its analytics.

Big data analytics is trending globally, surveys show that the USA will have around 2.7 million job postings in big data analytics by 2020. If you are going for big data as your career choice, not only will you gain knowledge over a variety of languages, applications, and strategies, you will also have a chance to grow as the flow of data is never going to stop.

Big data analytics closely works in coordination with the Internet of Things and the outcome of big data analytics helps in business development and predicting trends. Big data also supports various other streams. It is a vast field full of opportunities. Big data analytics is not all about programming languages and statistics, it is also a way of providing solutions to existing problems. It is a way of providing strategies that help in the growth of businesses.

You will have to convey your point of view in your workspace and how it will help in enhancing the business. These things will help you to grow as a good orator and leader. You will also make a lot of business relations in this career. Business intelligence (BI) will also come into play if you work as a data analyst. So, there are a lot of parallel fields if you are a data analyst, such as the importance of big data and its analytics nowadays.

Surveys show that there is a huge demand for big data analysts but there is not enough skill set in individuals to meet the criteria. If you have studied well then you should go in the field of big data analytics as you would be valued and respected there. This deficiency of good data analysts and data scientists are faced in all countries and that is why education centers are providing quality education on big data and related fields.

You can find a lot of online certified course on big data analytics by trusted sources. Every company is trying to gain an edge ahead over others in this competitive era by predicting smart trends and business ideas using big data analytics. There are a lot of companies that consider big data analytics as a topmost priority as it helps them in increasing the efficiency and quality of their business. Why would you reject to be a part of this cutting-edge technology?

Big data analytics is quite versatile, you can choose among prescriptive, predictive and descriptive analysis depending upon your interest and work environment. You can also choose among a variety of job designations such as big data analytics business consultants, big data analytics architect, big data analytics, etc.

Whatever smart solutions analytics is providing today, there is always a scope of improvement and a need for human intelligence. There is a lot of requirement of people in current days who can think out of the box, who can understand and analyze big data and help in improving the business. This was all about the pros of joining the field of big data analytics.

Why is Equity Research important?

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Investing in Equity has been considered a raffle for ages now which is enveloped by uncertainties. There is a perception that the investing game is all about fortunes and lucks and someday if a miracle happens, you can make millions overnight and if misfortune strikes you can lose millions in a minute.

All of it is true but to a very small extent. To save an investor from the wrath of the stock market, Equity research comes into the picture. Equity research acts as a shield for the investors and protects them in the best possible ways.

What is Equity Research?

 The literal meaning of Equity Research training is about your research before buying the stocks of any company. Equity research involves analyzing and studying various companies and the potential risks associated with those companies. Equity research is the first step towards your investing decision.

Companies listed on the stock exchanges are kept under the magnifying glass and the overall aspects which surround the company are carefully studied and examined. Equity research is carried out by professionals who have in-depth knowledge of the subject matter and can conclude on the basis of various results whether the stock should be bought or not. These professionals guide investors in making a purchase decision.

What are the steps involved in Equity Research?

  1. The economic conditions of the country where the investment has to be made are carefully studied and in-depth research has to be done. Various parameters like the Gross Domestic Product i.e. the GDP, the demand and supply factors, political conditions, etc. are taken into consideration as these factors affect the overall health of the economy and hence affect that company too where the investment is being planned.
  2. Various financial statements, data points, etc. are put under the scanner and are read carefully to understand the financial stability, capital structure, cash inflows and outflows, time period of dividend payments, etc. are carefully analyzed. Balance sheets are also analyzed so that a complete picture of the assets and liabilities can be ascertained. Profits and loss statements, income statements, cash flow statements are analyzed before investing in any company.
  3. Various performance indicators such as the revenue streams and the profitability of the business are analyzed. The history of the company where the investment has to be made is carefully analyzed. Past performances, the standing of the company with respect to its competitors, Quarterly and Annual results are carefully studied before making any investments in the company.
  4. The company is then valued by using various valuation models based on revenues, discounted cash flows, the sum of parts, Assets, and Liabilities, Goodwill, etc. This is done to come at a fair valuation of the company and also to understand whether the company is overvaluing or undervaluing itself at a given point in time.
  5. The fair prices of stocks are calculated mathematically and theoretically by using various valuation models and are then compared with the stock prices currently prevailing in the market. A deviation of a minor degree is usually ignored while computing the exactness of the share values.
  6. If the fair price calculated by the equity researcher turns out to be more than the prevailing equity share prices, the company in most cases have undervalued their shares by varying numbers. In such a case, the buying decision is made as the potential of the company is huge and the prices will most probably shoot up.

Conclusion
Investing is a game of gamble but with a systematic approach, it can be dealt with in a way that is a multiple-time better approach to make investments. With careful study and efficient equity research, one can reap the best benefits of their investments.

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