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Understanding the Difference Between Marketing Intelligence & Marketing Research

Posted on by Imarticus Learning

Creating a sound marketing plan requires market intelligence and market research. Marketing intelligence and research are two terms often used interchangeably. However, the meaning of the two is entirely different. 

Market research focuses mainly on your business, marketing plan, and product line. Market intelligence is information about the market, not necessarily a particular positioning. These are two separate things, though a diligent marketer will combine both when formulating a strategy, evaluating ongoing campaigns, and suggesting new goods and services to add to the range.

What is marketing intelligence?

Everyday information essential to a company’s marketing endeavours is known as marketing intelligence or market intelligence. This information can be examined and used to make smart decisions about the actions of competing businesses, consumer patterns, and potential markets.

Various things influence an organisation’s ability to stay ahead and its position in the market. Some crucial factors are the capacity to understand competitors in-depth, market conditions, and evolving consumer needs. CMOs can use this data to assess their strategies and improve future advertising efforts by considering both their views and those of the entire industry.

Market intelligence refers to all your company’s market elements, including rivals, customers, and goods. Access to those sources is essential because market intelligence data is continuously collected and updated from various sources. 

What is marketing research?

Market research, also known as marketing research, assesses the commercial viability of a new good or service by investigating the business’s markets, rivals, and clients. It is done to keep track of consumer buying trends in your business and the needs and desires of your target audience. It is crucial to any choices made regarding brand building and product growth. 

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When a company or organisation wants to know how consumers make expenditures or whether they are likely to pay a particular price for a product, market research assists in reaching valuable conclusions.

Market research is particular to an organisation, focuses on a single question, and is typically concerned with client requirements or preferences. An excellent example of market research is focus groups and in-person surveys, which are one-off projects independent of prior data.

Key differences between marketing intelligence and marketing research

Even though the two terms are similar, here are some points of difference that set them apart. 

Market Intelligence Market Research
Market intelligence is data that is essential to understanding a company’s markets. It is collected and evaluated to help decision makers grasp the market chance and business potential. The systematic process of collecting and evaluating data pertinent to a particular marketing plan is known as market research. 
Compared to marketing research, market intelligence is a more comprehensive notion. A specific exercise performed as part of a marketing plan is market research.
Market intelligence is used to determine marketing strategy. Marketing strategy affects how marketing research is executed.
Analysts with backgrounds in business analysis, financial management, and product management analyse market intelligence because it calls for a wide range of analytical skills. Analysts who analyse market research should ideally have training or expertise in behavioural sciences and mathematics.

Importance of marketing intelligence and marketing research 

Today, gathering marketing information is a necessity. Thanks to the information it offers, organisations can make decisions based on comprehensive information rather than hunches and speculation. 

Here are some reasons why gathering market information is crucial:

  • Informs businesses about their market opportunity, growth potential, and target audience
  • Aids with competitor research
  • Helps in creating a plan to achieve future objectives
  • Simplifies decision-making for your company by sifting through market chatter
  • Offers a consistent flow of data about the target market, the competitive landscape, consumer trends, and particular buyer personas
  • Enhances the position of your business by assisting with selecting profitable initiatives to invest in

In contrast to marketing intelligence, which is a continuous process, marketing research is a one-time activity that aims to provide answers to particular questions. 

However, its significance shouldn’t be ignored because it aids businesses in achieving the following goals:

  • Identify marketing possibilities by assisting in defining the target market
  • Reduces company risks by locating weak points in your marketing plan
  • Develop your go-to-market strategy
  • Produce pertinent marketing material
  • Select the most effective platforms for marketing and advertising
  • Discover neglected clientele
  • Determine client requirements
  • Outsell rivals by focusing on unsatisfied clients

Conclusion 

Depending on how they impact the marketing strategy and help achieve market goals, market research and marketing intelligence differ from one another. While marketing intelligence provides situational insights and interpretation so the business can foresee which strategy to use, market research offers a variety of alternatives to achieve the marketing strategy. 

Check out Imarticus’ Strategic Chief Marketing Officers course to learn more about the topic. This IIM Raipur CMO course has been designed considering market trends to make you ready for the industry, offering the best CMO training by esteemed faculty. This Chief Marketing Officer certification course can help you get a head start in your career. 

Impact of Central Bank Policies and Geopolitics in Capital Markets

Posted on by Imarticus Learning

Central Banks often issue monetary policies also known as central bank policies. These policies are launched to boost the economic growth of a nation. The main goal of these policies is to maintain the price of goods, reduce the unemployment rate by generating new jobs, and build a well-established economy. 

Most countries prioritise two things while creating their monetary policies. One is their internal economic as well as political issues and the other is the geopolitical situation. This helps them to deal with the uncertainty of the capital market.

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The capital market is so volatile that it can be influenced by any new monetary policies and new geopolitical issues. Therefore, one must possess enough knowledge about the volatility of the capital market before commencing a career in financial services. In this article, we will discuss in detail the impact of central bank policies and geopolitics in capital markets.

What do you know about the Capital Market?

The capital market is a financial market that allows several traders and customers to trade closely. Stocks, bonds, funds, etc are bought and sold by the individuals who are associated with this market. The participants of this market can either be an individual or any organisation.

The investments which are executed in the capital market are long-term investments. There are two kinds of capital markets one is the primary market while the other is the secondary market. Bombay Stock Exchange(BSE) is one of the perfect examples of a secondary market.

How do Central Bank Policies influence the Capital Market?

There are several Central Banks in the world. It is the main bank of a country whose main job is to look after the financial condition of its nation. To achieve this banks launch various monetary plans that stabilise economic fluctuation which means fluctuation is under proper control. 

The central banking policies can be broadly classified into three categories. The first one is the accommodative policy which is considered to be very expansionary and loose, while the second kind of policy is known as the restrictive policy which is usually tight and leads to a contradiction in the economy of a country. The last policy is the neutral policy which chooses the middle path. 

These various kinds of policies have direct as well as indirect impacts on the capital market. It directly impacts the interest rates, commodities, cash, bonds, equities as well as funds. And it indirectly affects the future of inflation. 

Here is how various monetary policies affect the capital market:

  • Accommodative Monetary Policy- 

When a nation opts for the accommodative policy the value of the cash decreases. This is mainly because the interest drops down and this will minimalise the returns. However, the market real estate improves with this type of policy.

People can easily avail the mortgage loans at low interest as it is quite profitable. Along with real estate, equities, commodities as well as stocks also witness a sharp robust due to low interest. However, bonds and currencies tend to yield lower during this type of monetary policy. 

  • Restrictive Monetary Policy- 

This is a rigid or tight monetary policy. During this policy, there is rapid economic growth and a reduction in inflation. During the restrictive monetary policy, many assets in the capital market perform poorly. 

As the interest rates increase during this phase bonds, equities, and real estate underperform. Therefore, it is quite expensive to buy equities and take a mortgage for real estate. However, cash and currencies tend to perform well during a restrictive monetary policy.

Cash and currencies tend to perform well because the interest rates increase. During the period between 2010 and 2013, Candana used a restrictive monetary policy that’s why their currency was performing better than the USA. 

How influential is Geopolitics in the Capital Market?

Geopolitics deals with political and social issues but at a global level. These issues include territorial disputes, water issues, military intervention, climatic change, disputes over natural resources, etc among various nations. Geopolitics is one of those mediums that can easily influence the capital market. 

The experts at Federal Reserve had invented the way one can measure the impact of Geopolitical tension on the capital market. This method is known as Geopolitical Risk Index (GPR). The GPR method is quite useful as Geopolitical incidents are very unpredictable and have a direct effect on the global economy and finances. 

Financial investors and traders are always intimidated by any new Geopolitical situation as it mostly affects the capital market negatively. The market returns are adversely affected. The biggest meltdown took place in the year 2008 that had negatively impacted the society and economy as many people failed to repay their loans.

Another situation took place during the Covid-19 pandemic. This pandemic had created great concern across the world and had an adverse impact on the financial market. As most of the ventures were forced to shut down due to the lockdown.

During calamities, diseases, and war the equity and finance market has to face downfall. However, Geopolitical issues are not permanent. Hence, after all the problems are sorted the companies which have a strong foundation will end up giving positive returns.  

Conclusion

To learn more about the monetary policies and capital market one needs to opt for an excellent online course. Therefore, Imarticus Learning has launched the IIM Lucknow Financial Services And Capital Markets course. This course is beneficial for those who want to start a career in financial services. 

This course of Imaticus Learning is a collaboration with IIM Lucknow so the best and most experienced faculty is going to lead this 6 months programme. So without any further delay get yourself enrolled in this online course to bag lucrative opportunities. 

Deep Learning in Medical Research and Disease Studies

Posted on by Imarticus Learning

Deep learning is a fast-expanding discipline with many uses, particularly in studying diseases and medical research. A job in deep learning requires proficiency in Python programming, including objects and lists.

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As a result, a Data Science and Machine Learning course provides comprehensive training in Python programming to equip individuals with the foundational knowledge needed for a career in this field.

In this blog, we will explore the various applications of deep learning in medical research and disease studies.

What is Deep Learning?

Artificial neural networks are used in Deep Learning, a subset of machine learning, to solve complex issues. Algorithms can perform tasks or make predictions without explicit programming by learning from relevant data.

Several applications, including autonomous vehicles and speech and picture recognition, use deep learning. It is modelled by how the human brain works, with its many layers of linked neurons processing and analysing information.

With deep learning techniques and advances in computational power, deep learning and machine learning with Python have become vital tools in artificial intelligence, with numerous practical applications in various fields.

Benefits of Using Deep Learning in Medical Research and Disease Studies

Deep learning has numerous advantages in medical research and disease studies, including:

Improved Analysis of Complex Data: Electronic health records, genomic data, and massive, complicated datasets like medical photographs can all be adequately analysed by deep learning algorithms. It may result in a new understanding of illness mechanisms, risk factors, and possible treatments.

Enhanced Medical Imaging Analysis: Deep learning systems can accurately analyse medical photos to find anomalies like tumours or lesions. It can help doctors diagnose more precisely and provide individualised treatment strategies.

Accelerated Drug Discovery and Development: Deep learning algorithms can identify potential drug targets and predict the efficacy and safety of drug candidates. It can help accelerate the drug discovery process and more quickly bring new treatments to patients.

Potential for Cost Savings: Deep learning enhances the effectiveness and accuracy of data processing, which can lower the expenses associated with medical research and drug development.

Deep Learning Applications in Medical Imaging Analysis

In the examination of medical imaging, deep learning has many uses. The most prominent ones are as follows:

  • Tumour detection and segmentation: Deep learning algorithms can accurately detect and segment tumours in diverse body areas by analysing medical pictures like MRI or CT scans.
  • Disease classification: Deep learning algorithms can analyse medical photos and categorise them according to whether they include specific diseases or conditions, like pneumonia or Alzheimer’s.
  • Image enhancement: Deep learning algorithms can enhance the precision and detail of medical pictures for better diagnosis and treatment planning.

Use of Deep Learning in Drug Discovery and Development

The ability to quickly find and generate new medications has been demonstrated to have considerable potential in drug discovery and development.

Deep expertise in this area has critical applications for things like:

  • Predicting drug-target interactions: Researchers can more quickly find medication candidates because deep learning algorithms can anticipate how a therapeutic molecule will interact with its target protein.
  • Virtual screening: Deep learning algorithms shorten the time and expense of conventional screening procedures by sifting through vast databases of compounds to find those with the most significant promise for drug development.
  • Designing new molecules: Researchers can examine a broader spectrum of prospective therapeutic options thanks to deep learning algorithms’ ability to optimise new drug compounds for specific targets.
  • Drug repurposing: Deep learning models can speed up and lower the cost of bringing novel therapies to market by discovering new applications for currently available pharmaceuticals.

Deep Learning in Genomics and Precision Medicine

Deep learning has also demonstrated considerable promise in the fields of genomics and precision medicine, which focus on analysing a person’s genetic makeup and customising medical care to their unique genetic profile.

Following are some examples of deep learning uses in this industry:

  • Genomic sequence analysis: Deep learning algorithms are capable of pattern recognition, gene function prediction, and genomic sequence analysis. It can aid in the identification of new pharmacological targets and the creation of specialised treatment regimens.
  • Disease diagnosis: Large genomic and clinical data sets can be used to train deep learning algorithms to detect diseases precisely based on a person’s genetic makeup.
  • Drug response prediction: To create individualised treatment programmes, deep learning models can be trained to anticipate a person’s response to a specific medicine based on their genetic profile.
  • Clinical decision support: Deep learning algorithms can help healthcare professionals make clinical decisions by analysing complex patient data and recommending treatments.

Limitations and Ethical Issues in Deep Learning for Medical Research

Using deep learning in medical research and illness investigations has several drawbacks and ethical concerns. Among them are:

Lack of transparency

Deep learning models are frequently called “black boxes” because they generate predictions using intricate algorithms that can be difficult to understand. The results’ dependability and accuracy may be questioned due to the demand for greater transparency.

Bias

The quality of deep learning models depends mainly on the training set of data. The model may generate biased or imperfect findings if the data is complete. In studies of diseases and medical research, bias can have detrimental effects.

Data privacy and security

Due to its vulnerability, the usage of medical data creates severe privacy and security issues. It is tough to secure patient privacy and stop data breaches since deep learning models need data to be practical.

Overreliance on technology

Deep learning models are powerful tools but should only be relied upon to partially replace human expertise and judgement. Researchers may need to rely more on technology and overlook critical contextual factors that can impact patient outcomes.

Limited generalisability

Deep learning algorithms are frequently taught on specific datasets and need to generalise more effectively to new ones. That may reduce their value in illness research and medical investigations.

Conclusion

Deep learning has immense potential in medical and disease studies, providing researchers with powerful tools for analysing and interpreting complex data.

The application of deep learning in medical imaging analysis, drug discovery, and genomics research has shown promising results. It can accelerate the development of new treatments and therapies for patients.

Imarticus Learning’s Certificate Program in Data Science and Machine Learning offers a holistic approach to learning Python programming, including the fundamentals of objects and lists.

This program is for individuals who wish to pursue a career in data science and machine learning. To learn more about this course, visit Imarticus Learning to learn more about the IIT Data Science course.

Learning from India’s best: Top courses provided by IIM Indore

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The (IIM) Indian Institute of Management Indore is a premier management institute in India. IIM Indore has consistently been ranked among the top business schools in India. An independent, public business school called the Indian Institute of Management Indore is in Indore, Madhya Pradesh, India (commonly abbreviated as IIM-I). 

IIM Indore, founded in 1996, is the sixth management school in the Indian Institute of Management (IIM) family and was recognized as a national institution of importance in 2017, along with the other IIMs.

So, what are the top courses offered by IIM Indore? 

Pursuing a course from IIM Indore can help you gain an edge in your career. The institute provides a range of courses, from full-time residential programs to short-term courses for working professionals. 

The PGP & EPGP courses aim to develop managerial and leadership skills among the participants. The FPM course is designed for students who wish to pursue a career in research and teaching. The MDP course is designed for working professionals who want to enhance their managerial skills.

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Pursuing executive education programs by IIM Indore can help you gain an edge in your career, and in this post, we will discuss the top programs provided by IIM Indore.

TOP Business Programs in India Offered by IIM Indore:

  • Post Graduate Programme in Management (PGP)

The Post Graduate Programme in Management is a two-year full-time residential course IIM Indore offers. The course is designed to give students an in-depth understanding of management concepts and practices. The eligibility criteria for the PGP course is a bachelor’s degree with at least 50% marks. The selection includes a written test, group discussion, and personal interviews.

The PGP course at IIM Indore is known for its case study approach, which helps students develop problem-solving and analytical skills. The course also includes an international immersion program, where students can study at partner institutes in countries such as France, Spain, and Singapore. The institute also provides industry exposure through internships & live projects.

  • Executive Post Graduate Programme in Management (EPGP)

The Executive Post Graduate Programme in Management is a one-year full-time residential course for experienced professionals. The course is aimed at developing leadership and managerial skills among the participants. 

The eligibility criteria for the EPGP course is a bachelor’s degree with at least 50% marks and five years of work experience. The selection includes a written test, group discussion, and personal interviews.

The EPGP course at IIM Indore is unique in its mix of online and offline modules. The course includes an international immersion program, where participants can study at partner institutes in countries such as Australia and the United States. The institute also provides industry exposure through internships and live projects.

  • Fellow Programme in Management (FPM)

The Fellow Programme in Management is a doctoral-level program designed for students who wish to pursue a career in research and teaching. The course is aimed at developing research skills among the participants. 

The eligibility criteria for the FPM course is a master’s degree with at least 55% marks or a professional qualification such as CA/ICWA/CS with a minimum of 50% marks. The selection process includes a written test, research proposal, and personal interview.

The FPM course at IIM Indore is known for its research-oriented approach. The course includes industry collaboration, where participants can work on live projects with industry partners. The institute also provides publication opportunities to FPM students through its research journals.

  • Management Development Programme (MDP)

The Management Development Programme (MDP) is a short-term course designed for working professionals who wish to enhance their managerial skills. The course aims to develop leadership, communication, and problem-solving skills among the participants. 

The eligibility criteria for the MDP course is a bachelor’s degree with a minimum of 50% marks and a minimum of two years of work experience. The MDP course among IIM Indore courses is customized according to the needs of the participants. 

The Final Words

IIM Indore is among the greatest institutions in India for management education. The institute equips professionals and students with the skills needed to excel in business through its top-rated courses and highly qualified staff. A course at IIM Indore can help you reach your goals, whether you want to progress your profession or launch a new one.

The courses offered by IIM Indore include experienced faculty members and an industry-oriented curriculum. The institute also provides certification to participants upon completion of the system.

Enroll in the Postgraduate Certificate Programme for Emerging CFO Course at IIM Indore in partnership with Imarticus Learning. This course advances your job and develops your financial leadership abilities. You’ll gain an in-depth understanding of management and finances with this online CFO executive training, which could lead to many opportunities!

How can a Financial Services and Capital Market Certification Help Professionals

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There are multiple opportunities when considering the scope of financial services and the capital market. The capital market is closely related to capital investment. There is a growing consciousness about investing profitably, with investment returns contributing a major chunk to an individual’s earnings. 

It is a great time to learn more about financial services and the capital market by enrolling for the IIM Lucknow capital market certification course. This will help one imbibe in-depth knowledge about the capital market, making investing and earning profits in capital markets easier. 

Read on to learn how financial services and capital market certifications help professionals in this competitively growing financial world. 

Reasons to enrol in this certification programme 

Capital Market Course

Dealing in the capital market is not easy. One must have a particular skill set to become a successful capital market professional. A capital market certification course helps professionals in learning skills that are important to have a better understanding of this competitive professional world: 

  • Understanding of financial terms

Having proper knowledge of capital markets and the financial world can aid one in comprehending financial jargon that is incomprehensible to a layman. A capital market certification course can help professionals avoid financial jargon. Such a course simplifies the terms like equity, derivatives, mutual funds, currency, etc. 

Professionals can scale greater heights in their careers with proper knowledge of financial terms and a better understanding of stock market concepts.

  • Specialised research skills

Capital market professionals should always dig deep for relevant data and information. A financial services certification course can be the best fit to help such professionals learn how to proceed when searching for relevant information in the capital market. This programme helps individuals create calendars, keep track of economic releases and participate in political movements, etc.

It is important for stock market professionals to maintain regular notes of changes in securities they are trading in. The research mainly focuses on identifying the best segment to maximise profit. 

  • Financial analytics

Performing quality market analysis is an integral part of trading in capital markets. Financial services course teaches how to analyse the stock market and understand the relevant information about the different types of securities they can invest in. Looking at the various trends and financial patterns helps a capital market professional decide the best technical approach for trading in a particular security.

Capital market professionals can develop their analytical skills by focusing more on trading in relatively safe securities. Opting for the right approach is better than focusing more on the monetary factor.

  • Financial modelling

Learning the technique of financial modelling is another essential skill that capital market professionals need to develop. Financial modelling is a technique of representing a company’s past, present and anticipated future operations in numerical value. 

Financial modelling is an extremely important and indispensable decision-making tool. A financial services course makes it easier for concerned professionals to learn this technique. 

  • Ability to remain calm in stressful situations

Profit and loss are two sides of the same coin when dealing with the stock market. The IIM financial services certification course is the best fit for teaching how to handle loss and take strategic decisions early in career.

  • Discipline and patience

Patience and discipline are two very important skills that are a must-have for a capital market professional. An effective capital market certification course helps one inculcate the qualities of being more disciplined and helps develop patience. It allows professionals to get accustomed to the highs and lows of trading in the stock market.

  • Regular maintenance of records

Keeping a record of the stock details one trades in is essential. Maintaining a record journal is integral as it helps concerned individuals learn from their mistakes and know what works in their favour. 

A capital market course can be the best fit to learn how to write journal entries and learn the most convenient way of filling the gaps between profit and loss.

  • Good communication and negotiation skills

Good communication skill is a common requirement in almost every field of work. However, stock market professionals must have exemplary negotiation skills in addition to communication. Financial service providers must be convincing enough to win people’s trust, especially concerning company funds. 

The IIM Financial services certification course helps one learn how to negotiate with potential clients.

Conclusion

The scope of the capital market is ever-increasing. Professionals in the capital market help companies make better investments. They are in high demand as organisations want a team of talented capital market professionals so that they can make sound investments on behalf of the organisation.

If you want to make a successful career in this field, the IIM Lucknow capital market certification can be your guiding light. Sign up for the IIM Lucknow Advanced Management Programme in Financial Services and Capital Markets presented by Imarticus and gain the necessary insights in this discipline.

Reasons Why Financial Modelling is Important in 2023

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Making a quantitative depiction of a company’s financial status is called financial modelling. Making forecasts and estimations of a company’s future performance, financial situation and cash flows entail building a financial model, a tool that leverages financial data.

Financial Analysis

Financial models may incorporate a variety of financial data, such as revenue estimates, costs, taxes, depreciation and cash flows. They are often created using spreadsheet software like Microsoft Excel or Google Sheets.

Businesses and investors may use financial modelling to understand the economic effects of their activities and make wise strategic decisions.

Applications of financial modelling

Financial modelling is helpful in:

  • Making predictions about future performance and financial results
  • Assessing prospective purchases or investment opportunities
  • Examining the effects of different financial choices or situations
  • Creating a budget and making plans for the future
  • Preparing balance sheets, cash flow statements and income statements for economic use.

10 benefits of financial modelling

In 2023, financial modelling will still be a crucial tool for investors and enterprises. The following are a few of the main advantages of financial modelling in 2023:

  1. Precise forecasting: Using financial modelling, companies may make precise financial estimates based on past data, current market conditions and assumptions.
  2. Risk reduction: By examining multiple possibilities and making sensible assumptions, financial modelling may assist firms in identifying and reducing financial risks.
  3. Better decision-making: It gives firms a mathematical foundation for making decisions, allowing them to weigh their choices and select the best course of action.
  4. Improved communication: When expressing financial information to stakeholders like investors, lenders and board members, financial modelling offers a shared language.
  5. Resource optimisation: By locating the most lucrative investments and skillfully handling their finances, financial modelling assists organisations in making optimum use of their resources.
  6. Efficiency gain: Financial process automation can assist in cutting down on the time and resources needed for financial analysis and reporting.
  7. Improved strategic planning: It gives firms a comprehensive grasp of the financial ramifications of various situations, which helps them plan and carry out their strategic ambitions.
  8. Better capital allocation: By determining the most lucrative investments and managing their finances effectively, financial modelling may assist organisations in allocating their resources more effectively.
  9. Better risk-adjusted returns: By determining the ideal ratio of risk to return, financial modelling may assist organisations in achieving higher risk-adjusted returns.
  10. Better valuation: Businesses may make better investment choices by valuing their assets, initiatives and investments more precisely using financial modelling.

Career paths related to financial modelling

Financial modelling skills are highly valued in the finance and investment industry, and there are several career paths available for professionals with expertise in financial modelling. Here are some examples:

  1. Investment Banking: It is a key skill required for investment banking professionals who work on complex financial models to advise clients on mergers and acquisitions, capital raising and other strategic transactions.
  2. Private Equity: Private equity firms also require financial modelling skills to evaluate investment opportunities, assess risks and forecast financial performance.
  3. Equity Research: Equity research analysts use financial modelling to evaluate and forecast the financial performance of publicly traded companies, which investors use to make investment decisions.
  4. Corporate Finance: It is a key skill required for corporate finance professionals who create financial models to support budgeting, forecasting and capital allocation decisions.
  5. Consulting: It is used extensively in management consulting to analyse and evaluate business operations, identify growth opportunities and assess financial risks.
  6. Asset Management: Asset Managers use financial modelling to forecast financial performance, evaluate investment opportunities and manage risk in portfolios.
  7. Risk Management: Risk management professionals use financial modelling to analyse financial risks and create models that predict the likelihood of future events and their potential impact.

Why will financial modelling still be important in 2023?

Using spreadsheet programmes like MS Excel, financial modelling may provide a statement that quantifies the company’s past, present and potential future. It is an economical technique that assesses possible concepts and calculates risks. It aids businesses in gathering their financial data, analysing the results and reaching major business choices. Valium 2 mg

Also, it can assist in developing long-term solutions for the company’s various financial issues. Most significantly, it creates accurate financial statements that convey to outsiders the company’s financial health. It is an essential competency when the company is considering mergers and acquisitions, attempting to raise funds, or trying to draw in new investors.

Wrapping Up

A financial model is a vital corporate tool used often in the finance sector. The Financial Analysis Prodegree in Collaboration with KPMG programme by Imarticus provides students with a comprehensive understanding of financial analysis and its application in various business scenarios. The programme covers a wide range of topics, including financial statement analysis, ratio analysis, cash flow analysis and valuation techniques to help students develop the necessary skills to become financial analysts.

It is delivered through classroom lectures, hands-on exercises, case studies and online learning modules. Upon completion, students will receive a certification from Imarticus and KPMG, which can help enhance their career prospects.

Reasons Fintech Should Keep Its Faith in Blockchain Technology

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Financial technology, also known as fintech, is a recently formulated technology that helps consumers to receive streamlined financial services. Fintech addresses almost all aspects of the finance sector. 

Fintech has revolutionised the world of finance. From updating bank transactions to formulating decisions regarding investments and stocks, every financial work can be accomplished by using either a mobile phone or a computer.

A lot of fintech’s success is riding upon blockchain. It has given birth to cryptocurrency, one of the most popular financial technology. However, with growing concerns over crypto’s instability, faith in blockchain, too, is receding. This article will discuss in detail why fintech must not lose its faith in blockchain technology.

Blockchain technology and cryptocurrency

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Blockchain is a kind of database that is distributed among various nodes of a computer system. A blockchain is quite different from a typical database. Here the data is usually stored in the form of blocks of varying sizes, while the database store data in the form of tables. 

Once a block with a certain size has been filled up with enough information, it is closed. Subsequently, that block automatically gets linked with the previously filled blocks and eventually forms a chain. This cycle keeps on continuing hence the data chain gets extended. 

Blockchain technology is mostly used in cryptocurrency to maintain a secure and hassle-free transaction over various computer networks. Cryptocurrency is an excellent example of fintech. It is a digital form of currency that is designed to be used across the internet without any assistance from third parties. 

Cryptocurrency is not issued by any central bank hence no government can control it. The first cryptocurrency, Bitcoin, was launched in 2008 and is still in immense demand.  

Reasons fintech should keep its faith in blockchain technology

Recently, blockchain’s reputation has been adversely affected due to the great downfall of various cryptocurrencies. Besides cryptocurrencies, many NFTs are also facing a downfall. However, fintech must not lose faith in blockchain as this technology has a lot to offer in the field of finance and beyond. 

Secured payments

Blockchains use technologies that do not allow any third party to intervene when there is an ongoing payment. Therefore, sectors that deal with fintech, like the banking sector or the investment sector opt for blockchain. 

Bring down cost

Blockchain technology will also assist fintech companies in reducing their infrastructure cost. Hence, banks can stop availing services from intermediaries or other third parties. Blockchain can also help various banks reduce the cost of creating new contracts. 

In a statistical prediction, it was stated that blockchain could reduce costs by $20 billion USD.

Rapid transaction of money

Blockchain technology can transfer money faster than traditional systems. It takes a few seconds to complete the entire transaction. Therefore, banks can execute rapid transactions.

Blockchain technology avoids any third party while executing a transaction. Therefore, the transaction time has reduced significantly, thus, increasing in number.  

Top-notch security

Fintech sectors deal with a large amount of capital. Hence, it requires a top-notch security level to safeguard all the capital. Blockchain technology can easily secure all transactions with its technology. 

No one can easily decode transaction details or information because implementing blockchain protects them from third parties. Secured transactions take place using two keys, one is the public key, and the other is the private key. Private key shares information of the transaction between two specific parties. 

Responsibility

Blockchain technology is essential for fintech because it carries all the responsibilities against fraud and misuse of assets. It reduces transaction errors that occur during the transfer of money. It also brings down cases of fabricated information. 

Conclusion

Blockchain still has a very promising future even after all setbacks it has witnessed. It will benefit financial technology in the future and create more job opportunities. Therefore, if anyone is interested in commencing a career in fintech, then they can opt for an online fintech certtification course. 

Imarticus Learning has brought the SP Jain Fintech certification course for those who are willing to make a career in fintech. This course will incorporate the required knowledge and skills, including API, cloud computing, machine learning, IoT, AI, taught by renowned faculty. The course is spanned over 3 months and opens gateways through partnerships with industry giants. Apart from access to an online library housing more than 900,000 books, students get the esteemed SP Jain alumni status. Enrol in this course to bag alluring job opportunities today! 

Steps to Become a Cybersecurity Analyst

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Data of every nature, whether sensitive or not, is stored and transmitted online daily by everyone, from businesses to government entities and even individuals. Consequently, securing that data is of utmost importance, with hackers innovating more sophisticated tools to attack and corrupt data. The question lies in who can prevent and tackle these incidents. The answer is a cybersecurity analyst.

With the growing frequency of cyber threats and malware attacks, there is a constant rise in demand for cybersecurity professionals. Thus, it is the right time to build a career in cybersecurity. Read on to learn how.

Who is a cybersecurity analyst?

Cybersecurity analysts are specialists that protect the network and systems of a company from possible cyberattacks. They monitor databases, computer infrastructure and systems to identify potential anomalies in various applications, programmes, networks, etc.

cybersecurity courses

Also, cybersecurity analysts take protective measures to prevent malicious activities and external damage. They use the most effective and latest methods to abate any security vulnerability that can impair the company’s normal functioning and cause significant damage.

What are the roles of a cybersecurity analyst?

A cybersecurity analyst has multiple responsibilities. Some of those are:

  • Managing software

A cybersecurity analyst needs to install, update and maintain various software on the systems and networks of the company. The aim here is to secure the system from potential threats.

  • Monitoring network

Proper monitoring of the network is another principal role of a cybersecurity analyst. Network monitoring is required to nullify any potential threats seeping in.

  • Security planning

A cybersecurity analyst also needs to develop a security plan for the organisation. The analyst should consider every cybersecurity detail. They must also keep the organisation’s key members abreast of the security details.

  • Reports

A cybersecurity analyst has to compile reports on flaws and vulnerabilities of the system and enlist the possible measures to resolve these issues.

  • Ensure compliance

A cybersecurity analyst ensures that the organisation is adhering to various regulatory standards. For example, if an organisation has chosen ISO 27001 as its information security standard, then the analyst ensures that the organisation follows it explicitly.

  • Research

Cybersecurity professionals should constantly research ways to improve security and keep themselves updated with every new malware. They need to look for all the latest technologies that can protect the system better.

What are the skills required for a cybersecurity analyst?

There is a range of skills that a cybersecurity analyst need to muster. Some of the more important ones are:

  • Programming

Skills in programming languages like C++ and JavaScript help detect encoded threats.

  • Hacking

Cybersecurity analysts also work as certified ethical hackers. It enables them to have a better understanding of incoming threats.

  • Knowledge of protocols

You should also know various protocols like privacy and access to building a system that is well protected.

  • Networking

Proper know-how of the networking elements enables one to understand threats better.

Steps to becoming a Cybersecurity Analyst

A cybersecurity analyst plays a critical role in any organisation. It requires proper knowledge and skills to become a cybersecurity specialist. Here are a few basic steps to becoming a cybersecurity analyst.

  • Learning the fundamentals

The first step is to learn the fundamentals of cybersecurity. A clear vision of the current threat to information systems, network architecture, firewalls and much more is required. Mostly, employers prefer a candidate with a degree or diploma in information technology or any related course. These courses provide all the fundamental skills and knowledge required. 

  • Earning a certificate

A certification means proficiency in a particular skill. And, that is what cybersecurity is about. Organisations often prefer candidates having certification from well-reputed institutes. Both entry-level and mid-career jobs require certification.

  • Experience gaining

Gaining experience is another crucial part of becoming a cybersecurity analyst. Some of the lower-level jobs don’t require a lot of experience. So, these jobs are more approachable for beginners. Having experience boosts the chances of landing the desired job. These experiences may include college internships, participation in online cybersecurity training labs, and part-time IT jobs.

  • Keeping updated

Cybersecurity is a rapidly evolving sphere in IT. Hackers discover new ways to attack systems daily. Hence, constant research and learning about the latest trends and advancements in technology is necessary to keep you in the loop.

  • Apply for job

After going through the previous four steps, the first thing is to look for a job that matches the skillset you have acquired. It often helps to land a job in cybersecurity if you have a good network. Having a little real-world experience can act as an added advantage.

Conclusion

If you are interested in cybersecurity, then the job of a cybersecurity analyst is a career you can consider. As the demand for cybersecurity is rising rapidly, you can land lucrative jobs with relevant skills.

Check out the postgraduate programme in cybersecurity brought to you by Imarticus. The course offers lab sessions on real-world problems and assured job placement. Become a certified ethical hacker under the guidance of industry experts.

How to Kickstart a Career in Digital Marketing

Posted on by Imarticus Learning

Advertisements on the internet and creative ads on social media are unmissable features. Just as ads on the billboard we see on the highway are traditional marketing, any advertisement propagated via an electronic gadget, like the pop-up ads on websites, makes up digital marketing.

Digital communication has become an indispensable part of our lives and is an essential digital marketing tool. Through online communication with potential buyers, any business can yield a perfect marketing strategy by understanding the needs and requirements of customers. A good digital marketing course will help kickstart a successful digital marketing career, teaching the essentials of marketing.

How to approach digital marketing as a beginner?

best digital marketing course

To have a versatile career in digital marketing, one has to start with the fundamentals. Here are the best ways to build your career in digital marketing from scratch:

  • Obtaining a degree: First comes awareness and thorough knowledge of the desired subject. Getting a bachelor’s degree in marketing or advertising will acquaint you with all the necessary information required at the basic level of online marketing techniques.
  • Garnering specific skills: Once you get the hang of the subject, you can start learning strategies and upskilling yourself, consequently setting yourself apart in the field. Some necessary digital marketing skills include learning to analyse data, write content and develop creative marketing strategies.
  • Getting experience: Any candidate is deemed more worthy if he/she has some prior experience in the field he/she is trying to pursue. Starting an entry-level digital marketing job will get you the needed experience and educate you on practical applications.
  • Strengthening your resume: Go for more courses, internships or even a boot camp on digital marketing. It will not only help grow your exposure to the subject, but the certificates will add to your CV and attract prospective recruiters. 

Inbound and outbound marketing

We’re often bombarded with lucrative emails with offers and discounts designed especially for our needs. This sort of marketing is known as outbound marketing, where an organisation tries to propagate its existence in every way possible, but it seldom warrants a favourable outcome. 

Digital marketing is traditionally considered a part of inbound marketing, where you appeal to already interested people. Instead of generating generic ads for all, you can create an individualistic and specific way to advertise your business. Thus, when starting with digital marketing, it is important to be creative and find economical ways to improve your business. 

Skills required for a digital marketing career

Search Engine Marketing 

A prominent ranking amongst search results should be implemented in your endeavour to make your business more relevant. Search engine optimisation (SEO) attempts to enhance results when you look for a topic on any search engine by attracting traffic to a particular website and increasing its rank when searched. 

Like SEO, search engine marketing (SEM) is also a significant part of digital marketing ━ websites, and businesses increase their rankings through payment to a particular search engine. This way, a small business might catch someone’s eye and attract an influx of customers. SEM helps businesses present the perfect online ad to convert buyers into loyal consumers. 

Content writing and communicating with buyers

Writing content online makes you accustomed to what a customer might or might not need, and you learn to communicate with buyers in a friendly yet dignified manner. It allows businesses to seem approachable yet strict when presenting themselves online. This is why having content writing as a skill is extremely important when venturing into digital marketing.

Communication is key in digital marketing. Once you understand what your customer wants, you can easily create a product suited for them and design distinct ads for any future undertakings.

Creative skills

Creativity indeed goes a long way in digital marketing; from catchy slogans to innovative campaigns, businesses depend greatly on what kind of content and advertisement they put out there. The better your ads, the more your customers are. This is what digital marketing will expect of a candidate, so honing your creativity will help you in this area. 

Conclusion

With a world that runs on technology, digital marketing has seen a massive boom. With almost everything being conducted online, we have come a long way from bumper sticker ads to finding what we are looking for online through a perfect advertisement. This makes handling digital marketing an important part of any business that wants to thrive online. 

Understanding how to deal with advertisements is fundamental to being good at marketing and having permanent customers. Imarticus’ digital marketing course can be the gateway to affluent employment. 

Data Science Using Tableau and Power BI

Posted on by Imarticus Learning

Data science creates coherent knowledge from incoherent structures of data using statistical processes and tools. In a world where technology reigns supreme even for the most minor issues, data science is a rapidly developing sector and is quite beneficial for anyone interested in exploring this area. 

To understand and work with data science, one has to be familiar with the workings and significance of the tools used to arrange unstructured data. These include Tableau and Power BI, two of the most widely used analytical tools in organising data. 

Read on to learn how a knowledge of these tools can help make a successful career in data science.

Data visualisation and its endless merits

 

Before using tools like Tableau and Power BI, it is imperative to know what data visualisation is and how it works. Imagine reading about the population statistics of a country over decades- the changes in the numbers become a lot easier to understand when presented with graphs or pie charts.

These graphs and charts in data visualisation are often created with the help of the programming language Python. Data visualisation with Python allows it to use libraries like Bokeh and Matplotlib, which contain unique intrinsic units, to create the required graphs from a mass of unstructured collected data. Tableau and Power BI help enhance such effortlessly receptive graphs and more. They also employ linear regression when sorting data- it helps predict the outcome of the dependent variables on the independent ones during data analysis and assists in data visualisation.

Data science using Tableau – Its uses and importance

Any organisation needs its data to be analysed in order to understand its progress and targets and take corresponding action. Founded in 2003, Tableau enters this scenario as an essential analytical tool that helps process the sea of data into great visuals allowing Data Scientists to understand and extract relevant information from the same.

How Tableau operates

  • Tableau uses TDE, or the Tableau Data Extract, to store and collect mass data, sometimes also Hyper, a technology that enhances the collection and analysis of the data through fast and efficient processing. 
  • Sometimes, errors occur while data is being stored or analysed. Tableau uses ETL Integration (Extract Transform and Load) to recognise, extract and fix the error. With a visually appealing and easy-to-grasp interface, one can do all of this with the help of Tableau Prep Builder. 
  • Anyone examining and willing to explore all kinds of data can connect to a vast array of databases anywhere using the Tableau Desktop. 
  • Local businesses or non-profit enterprises also make use of Tableau Public which does all of the same things as Tableau Desktop, but the sharing of the reports of the data exploration remains limited to the public domain. 
  • Finally, Tableau Server and Tableau Online provide security, efficiency and a large amount of collective accessibility and inspection of the data in your organisation. 
  • Tableau even allows one system to connect with another for further examination and scrutiny. 

Data science and its dependency on Power BI

Like Tableau, Power BI is a Business Intelligence (BI) technology that provides clarity to unorganised data, like creating a meaningful image by putting puzzle pieces together. Power BI was in its initial design in 2010 and was launched in 2011 by Microsoft as a desktop application that allowed anyone to inspect, understand and visualise data on their own.

Basic features of Power BI 

  • Power BI’s major appeal is the connection it offers to several data sources, from Excel to Google Analytics and even social media platforms like Facebook, Twitter and Reddit. 
  • It also allows analysts to connect to IoT (Internet of Things) devices, collect that data and transform it into creative visualisation and interaction. 
  • The Power BI Pro enables anyone to gather any data they want, survey it and create dashboards suited to their required needs. 
  • One can also control who has access to the new, processed data. Power BI simultaneously protects and shares data and insights across the organisation. 
  • It is regulated per General Data Protection Regulation (GDPR) and is easily operable on mobiles. 
  • With its Premium well-suited for large organisations and businesses, Power BI is a real step up for Data Scientists.

Conclusion

Data science as a branch has been extremely versatile in its growth in recent years, and a simple visual representation of anything complicated always yields a better understanding of the concept. This is why someone starting out with data science needs to be well-acquainted with Tableau and Power BI, their contribution to the field and their interchangeable usage because of their similarities. 

Imarticus’ PG in Data Science and Analytics is a data science course with job interview guarantee that will provide a thorough understanding of data science, the processes and tools needed to work with, the required training needed for upskilling, and consequent employment. 

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