Contact Us
×

Author: Imarticus Learning

Role of Capital Markets in Providing Capital to SMEs

Posted on by Imarticus Learning

Small and medium-sized businesses (SMEs) are essential to the economy because they foster growth, innovation, and the creation of new jobs. Yet, Businesses need help to get financing, mainly because bank loans have strict lending standards.

Capital Market Course

Capital markets provide a viable solution for those interested in a career in financial services. SMEs can raise capital and achieve their growth objectives through financial instruments like stocks, bonds, and other securities.

The Importance of SMEs for Economic Growth

The significance of SMEs for job creation and GDP: The importance of SMEs for GDP and job creation: SMEs account for the majority of businesses and jobs globally, and they generate new employment opportunities and support economic growth.

SMEs as drivers of innovation: Small and medium-sized businesses are frequently more innovative and flexible than giant firms, which boosts productivity.

Promoting regional development: Small and medium-sized businesses (SMEs) can be particularly advantageous for regional development in rural areas, generating economic possibilities and jobs where giant corporations may not exist.

The need for access to capital: Businesses need access to cash to finance operations and grow their firms if they are to succeed and keep boosting the economy.

The role of capital markets: By giving SMEs access to a larger pool of funds, capital markets can support their expansion and development.

The Challenge of Accessing Capital for SMEs

The challenges of accessing capital for SMEs can include the following:

Limited access to traditional financing: It can be challenging for SMEs to obtain traditional bank loans and other funding sources, making it challenging for them to fund their operations or engage in expansion prospects.

High collateral requirements: Many lenders’ collateral requirements can be a significant obstacle for SMEs since they need additional assets to put up as security.

Limited credit history: SMEs frequently need a better credit history, making getting approved for loans or other types of funding challenging.

Lack of financial literacy: Many businesses need more financial literacy, making it easier to get funding and manage their finances efficiently.

Cyclical nature of business: Many SMEs work in extremely cyclical or seasonal sectors, which makes it challenging to sustain a steady cash flow.

Economic uncertainty: Lenders may be less willing to lend to SMEs due to market volatility and economic uncertainty, which may restrict their access to money.

Regulatory barriers: Some SMEs may need help to obtain financing due to regulatory barriers like bans on foreign investment or limitations on the types of businesses that qualify for government support.

Information asymmetry: Lending might be challenging since lenders need more details about the SME’s financial status or creditworthiness.

The Role of Capital Markets in Providing Capital to SMEs

Capital markets may be crucial in helping SMEs obtain funding. Capital markets provide a variety of funding choices that can be adapted to particular needs, in contrast to typical bank lending, which is restricted to smaller loan quantities and demands collateral.

Capital markets can help SMEs via, among other things:

Bond markets: Bonds that SMEs issue to raise money may attract investors searching for higher yields. Bonds may be more expensive than bank loans, but the funds produced can be invested or used for other things, including project expansion.

Equity markets: Small businesses can also raise money by issuing stock, which gives investors a stake in the company. It may be a desirable option for SMEs seeking to grow quickly or pursue other growth prospects.

Private equity: Companies will lend money to SMEs in return for a part of the business. It might be attractive for SMBs looking to expand swiftly or in need of cash for new projects or investments.

Crowdfunding: Businesses can access a big pool of potential investors through crowdfunding platforms willing to spend small amounts of money in return for a share of the company’s profits or other perks. It can be a terrific alternative for SMEs wishing to raise less money or have a solid customer base.

Advantages and Disadvantages of Raising Capital through Capital Markets

Advantages of Raising Capital through Capital Markets

  • Access to a larger pool of investors
  • Potential for greater liquidity
  • Potential for higher valuations
  • Ability to leverage public listing for future financing opportunities
  • Lower interest rates and more extended repayment periods for debt financing
  • Opportunity to attract new investors and stakeholders, including institutional investors

Disadvantages of Raising Capital through Capital Markets

  • High costs of compliance and regulatory requirements
  • Disclosure of sensitive information to the public
  • Short-term pressures from shareholders
  • Risk of market volatility and fluctuations

Different Types of Capital Markets for SMEs

There are several types of capital markets available to SMEs, including:

Private Equity Markets

These are the markets where investors lend capital to companies in exchange for shares of those companies. Private equity firms frequently invest in companies with a track record of success and look for funds for growth or acquisitions.

Venture Capital Markets

Investors offer money to start-ups in these markets if they have promising growth potential. Venture capitalists frequently invest in start-up companies that need money for R&D, market expansion, and product development.

Angel Investor Markets

Private investors finance new companies in these markets. Angel investors usually make smaller investments than venture capitalists and might be more willing to take on more risks.

Public Equity Markets

On these markets, businesses can raise money by selling stock to the general public. The shares are traded on the NASDAQ and the New York Stock Exchange (NYSE).

Public stock markets provide a funding source for well-established enterprises with a robust financial performance track record.

Crowdfunding Markets

These markets allow businesses to use internet platforms to raise money from several investors. Crowdfunding is a method that SMEs can utilise to raise money for their company.

Conclusion

For SMEs to expand and succeed, the role of capital markets in supplying them with financing is essential. While capital markets offer a variety of benefits and drawbacks, including access to a larger pool of investors and increasing regulatory requirements, it can take time for SMEs to get financing.

Thus, financial services professionals must thoroughly understand capital markets and how they affect SMEs.

Imarticus Learning’s IIM Lucknow Financial Services And Capital Markets course is an excellent choice if you want to pursue a career in financial services and capital markets. 

This course equips you with comprehensive training in financial services, capital markets, equity research, investment banking, and financial modelling to excel in various roles in the industry. Visit Imarticus Learning for more information. 

What is Financial Statement Analysis and How is it Different from Financial Analysis?

Posted on by Imarticus Learning

Analysing the financial statements of a company to facilitate decision-making is called Financial statement analysis. It involves evaluating and analysing businesses, budgets, projects and various finance-related transactions that help them to regulate their performance. In general, experts use financial analysis to determine the stability, solvency, or profitability of an entity and if they are enough for a monetary investment.

Financial Analyst Course

It is an integral part of financial statement preparation and is extensively used by external stakeholders to evaluate the overall financial health and business value of an organisation. Financial analysis on the other hand is used to determine economic trends, build future business plans, set financial policies, and find out suitable companies and projects to invest in.  

This article will give you detailed information about financial statement analysis, its types and how it differs from financial analysis as a whole.  

Three Techniques Used in Financial Statement Analysis?

Financial statement analysis is an integral part of preparing the financial modelling spreadsheet that helps forecast business performance. Financial analysts generally use the following techniques to analyse the financial statements of a company. 

  • Horizontal analysis: This is carried out via the comparison of historical data and is used for detecting growth trends from various time periods. 
  • Vertical analysis: This is carried out via the comparison of items listed on a financial statement and their relation to each other. For example, an expense item can be expressed as the sales percentage of a company. 
  • Ratio analysis: This is the final and most important part of the analysis where the line-item data like P/E (Price-to-earnings) ratios, dividend yield or earnings per share.

Financial Statement Types 

To efficiently manage operations and run business forecasts, companies make use of financial statements like balance sheets, income statements, and cash flow statements to ensure that their stakeholders get maximum transparency. The different types of financial statements have been elucidated below:- 

  • Balance Sheet: This is a document that reports the financial worth of a company with regard to book value. It is usually divided into three segments namely:- 
  • Company assets: Cash and accounts are short-term assets that can be received and are proof of how efficiently the company is operating. 
  • Company liabilities: A company’s arrangements for expenses and how much debt capital is being paid off fall under company liabilities. 
  • The shareholder equity of the company: Detailed information about earnings from net income periodically and equity capital investments fall under shareholder equity. 

It is important for the balance sheet to balance the assets and liabilities keeping the shareholder equity equal. This figure serves as the company’s book value and is considered an integral performance metric.

  • Income Statement: This helps segregate the revenue earned against the expenses spent by a company to run its business activities. All in all, it refers to the net profit and loss of a company. It is broken into three segments for business efficiency analysis:- 
  • Revenue 
  • Operating profit
  • Net income is reached

Analysing income statement involves calculating gross profit, operating profit, and finally, net profit margin. 

  • Cash Flow Statement: This is more like an overview of the cash flows of a company starting from investing activities, financing activities and operating activities. Net income is added to the cash flow statement, which is further included for operating activities as a top-line item. Investing activities section in the cash flow statement includes cash flows from firm-wide investments where as the financing activities section includes cash flows from equity and debt financing. At the very bottom, one can find the outstanding cash that is available in the company. 
  • Free Cash Flow Statements/ Other Valuation Statements: Analysts are also known to use other valuation or free cash flow statements to determine company value. Free cash flow statements show the total present value by deducting the free cash flow estimated by a company to generate. It is highly valuable for private companies before they go public. 

Financial Analysis: A Brief Introduction

Financial analysis, unlike statement analysis, is used to monitor economic trends, decide what financial policy to set, make long-term plans, and pinpoint projects and companies to invest in. It can be done by both investment finance and corporate finance companies.

It is carried out by a financial analyst who synthesises financial data and thoroughly examines the financial statements of a company namely:-

  • Income statement
  • Balance sheet
  • Cash flow statement. 

Financial data is commonly analyzed by calculating ratios extracted from the data in the statements and comparing them against the company’s historical performance or the data of other companies.

Financial Analysis vs. Financial Statement Analysis

Both Financial analysis and financial statement analysis are involved in evaluating and analysing the financial statements of a company to facilitate economic decision-making. However, both have their key differences that need to be interpreted clearly for proper understanding. The differences have been elucidated below:-

Key parameters Financial Analysis Financial Statement Analysis
Definition Financial analysis refers to assessing and analysing the financial statements of a company for enhancing economic decision-making. Financial statement analysis refers to comprehending what is essentially indicated by the financial statements like balance sheet, cash flow, income and the like.
Purpose Financial analysis helps a company understand how much the results of a current period have changed from the past. Financial statements analysis is carried out to help companies make informed decisions to enhance future performance.
Time Financial analysis is straightforward and takes less time. Financial statement analysis involves extracting, reviewing and detecting connections within the information at hand, making it more time-consuming.

Conclusion

Financial statement analysis is an integral part of the financial modelling of a company because it helps provide in-depth information about the KPIs of a company over time. Financial analysis on the other hand is a more holistic term used to signify the processes involved in the analysis of a company’s financial health over time.  

If you are planning to pursue a career in this field, you must have a deep understanding of both as well as how different they are from each other. To kickstart your career as a financial analyst, you can consider signing up for the Financial Analysis Prodegree In Collaboration With KPMG offered by Imarticus Learning. 

A detailed overview of media planning and affiliate marketing

Posted on by Imarticus Learning

In today’s competitive digital setting, businesses must create and share several types of media content. It may include images, videos, text, and podcasts. This leads to increased brand awareness, engagement, conversions, and revenue.

At a CAGR of 13.9%, the global market for digital advertising and marketing is projected to reach $786.2 billion by 2026.

But managing and analyzing all this content can become overwhelming. And so, media planning and affiliate marketing are powerful strategies for attaining marketing goals. When used together, they can lead to even greater success.

Media planning focuses on identifying and utilizing the most effective channels for advertising. Whereas, affiliate marketing leverages the network and reach of third-party partners to drive business growth.

digital marketing online course

Steps involved in media planning

 

Media planning includes the processes of creating, distributing, and analyzing media content. It is an effective solution for organizing and managing processes. It can ensure that your business stands out from the competition in the digital world.

Here are the general steps involved in media planning for the online space:

Set marketing and advertising objectives.

Define the target audience.

Research digital media channels.

Develop a media plan.

Implement the media plan.

Monitor and evaluate the results.

Types of media planning

Three main categories are considered when building a media plan:

Paid media refers to advertising that is the result of paid placement from the brand. It is a quick and efficient way to reach a large audience and drive sales.

Owned media refers to content owned by the brand. It is less expensive than paid media.

Earned media refers to the publicity the brand gets from outlets other than its own company. It often comes directly from customers, which can help to improve the quality of the product or service.

Each of these types of media has its own unique advantages. So, a mix of media channels can be used to reach different marketing goals.

List of digital media channels

The six major categories of digital media channels are as follows:

Digital Media Channel Type of Media Planning
Paid Media Owned Media Earned Media
1. Search engine marketing PPC Organic search Backlinks
2. Social media marketing Sponsored post Company post Customer review
3. Digital advertising Programmatic bidding Native advertising Sponsorship
4. Digital PR (Public relations) Online advertorial Guest blogging Influencer mention
5. Digital partnership Affiliate marketing Co-branding Co-marketing
6. Digital messaging Push mobile message In-house e-mail Partner e-mail

Affiliate marketing

It is a type of performance-based marketing.

  • Affiliates promote a business through their networks, websites, or social media channels.

  • A business rewards one or more affiliates for each visitor or customer brought about by the affiliate’s marketing efforts.

  • This can be done by using digital channels to promote affiliate products or services.

    Example: Create social media ads, send affiliate promotions through email marketing, and add affiliate links to website content.

Become a digital marketing expert

A digital marketing certification course is a training program. It teaches the skills and knowledge necessary to plan, execute, and measure digital marketing campaigns. It covers a range of digital marketing tools and strategies. It also helps you to understand how to align digital marketing with media planning and affiliate marketing well.

Now, let’s learn the features of the digital marketing certification course offered by Imarticus Learning:

  • This training program is 228 hours long, where you can learn SEO, social media, content, performance, email, and analytics.

  • You will learn from real-world examples and case studies of successful digital marketing campaigns.

  • You will work on projects that focus on real-world digital marketing problems and get a chance to solve them.

  • This program is approved by the industry council and will give you an education that is up-to-date with the latest trends.

  • You will earn a digital marketing certificate upon successful completion of the course.

  • A Program Mentor will be assigned to you to support you throughout the journey. They will help you with any questions, track your progress, and give you tips.

  • This program can help you prepare for your dream job by giving you skills, experience, and connections to help you land a job in digital marketing.

Recent graduates who have 0-2 years of experience can apply for this course. The mode of instruction includes both classroom training and live online sessions.

What sets Imarticus Learning apart?

Digital channels are becoming increasingly important in today’s marketing landscape. As the world becomes more digital, businesses are finding ways to connect with their target audience through digital channels.

Imarticus Learning offers a digital marketing course with job interviews guarantee. So, interested candidates can opt for either online or offline mode of training. Get in touch with our representative to know more about the course.

Imarticus Learning is an award-winning ed-tech company. It provides courses in various fields such as finance, analytics, technology, and marketing.

Mergers and Acquisitions: Essentials and Best Practices

Posted on by Imarticus Learning

Mergers and Acquisitions (M&A) are key strategic transactions that can benefit a company significantly. However, they also come with inherent challenges and risks that require careful consideration and effective risk management strategies. 

In this blog, we will explore the essentials of M&A, including the different types of M&A, the benefits of considering M&A, key considerations to keep in mind during the M&A process, and best practices to ensure success. 

Investment Banking Training

Whether you’re a business owner, investor, or aspiring professional in Investment Banking, this blog will provide you with a comprehensive understanding of M&A and equip you with the necessary tools to navigate this complex field.

What are Mergers & Acquisitions (M&A)?

Two or more businesses may merge to accomplish strategic goals, or one company may purchase another. These transactions are referred to as mergers and acquisitions (M&A). It is a complicated process that involves several parties and can take many different shapes.

What Are the Different Types of M&A?

Depending on their strategic goals and the sorts of businesses involved, companies might engage in various mergers and acquisitions (M&A).

The most common types of M&A include:

Horizontal mergers: This M&A involves two businesses active within the same sector and along the same value chain. Horizontal mergers seek to increase market share, lessen competition, or realise economies of scale.

Vertical mergers: With this kind of M&A, a business buys or merges with a client or supplier within the same sector but at a different value chain level. Vertical mergers can help companies to cut expenses, increase efficiency, or take control of their supply chain.

Conglomerate mergers: Two businesses involved in this M&A are from unrelated industries. Conglomerate mergers may be motivated by diversifying the company’s operations, lowering risk, or penetrating new markets.

Market-extension mergers: This merger and acquisition combine two businesses that operate in the same sector but in different regions. Market-extension mergers can assist companies in gaining access to new clients, increasing their market share, or achieving economies of scale.

Key Considerations in M&A

Acquisitions and mergers (M&A) can be complex deals with significant risk and uncertainty. Before opting to pursue M&A, businesses must carefully assess several crucial factors.

Some of the critical concerns in M&A include:

  • Strategic fit: Businesses must consider whether the target company aligns with their goals. Throughout the process, whether the acquisition will aid the company’s expansion and growth objectives, business diversification, or entry into new markets is determined.
  • Financial performance: Businesses must evaluate the financial performance of the target company, including its sales, profitability, cash flow, and debt levels. 

Companies should also consider the acquisition’s financial implications, such as the cost of financing and the impact on the company’s balance sheet and income statement.

  • Due diligence: Businesses must carefully evaluate the target company’s legal, regulatory, and financial conditions. The target company’s financial statements, contracts, intellectual property, and legal and regulatory compliance are all subject to scrutiny as part of the due diligence process.
  • Integration planning: Businesses must create a detailed plan for integrating the operations, culture, and staff of the target company into their current operations. Planning for integration includes:
  • Identifying potential teamwork.
  • Creating a timeline for integration.
  • Addressing cultural and organisational differences.
  • Communication and stakeholder management: All parties involved in the transaction, such as employees, clients, suppliers, and shareholders, must be informed. Effective communication and stakeholder management are essential to minimise disruption and uphold confidence and trust.

Best Practices in M&A

Mergers and acquisitions (M&A) can be complex and risky to pursue. To increase their chances of success, businesses should follow specified best practices while engaging in mergers and acquisitions.

Some of the best practices in M&A include:

Develop a clear M&A strategy

A company’s M&A strategy should be well-defined and aligned with its business plan. The plan should have clear goals like expanding into new markets, diversifying the clientele, or achieving cost harmony.

The system should also include a plan for integration and standards for assessing possible targets.

Seek professional advice

Businesses should seek the counsel of knowledgeable specialists, such as attorneys, accountants, and investment bankers, to help them negotiate the complexity of M&A.

Companies can identify dangers and possibilities with the assistance of professional counsel, which can also help them effectively negotiate favourable terms and carry out the deal.

Monitor and evaluate the performance

Following a merger, businesses should monitor and evaluate how the combined entity performs. It includes monitoring financial results, assessing integration project performance, and identifying residual issues or challenges.

By monitoring and assessment, businesses can identify areas for improvement and change their plan as necessary.

Maintain confidentiality

Sensitive information in M&A transactions should be kept private until the deal is finalised. Businesses should have plans to prevent the disclosure of personal data during the negotiation or due diligence stages.

Evaluate financing options

To choose the most affordable and flexible financing option for the transaction, businesses should compare various financing choices, including debt and equity.

The effect of financing on the balance sheet and the company’s income statement must also be considered.

Plan for contingencies

Companies should strive to address unforeseen circumstances, such as regulatory concerns or changes in market conditions since M&A transactions can be unpredictable. 

Businesses can also consider alternate acquisition targets if the primary target doesn’t work out.

Challenges and Risks in M&A

M&A transactions can be complex and demanding, with various risks, especially in the money market.

Among the difficulties and risks associated with M&A are:

  • Integration challenges: It can be challenging to merge two distinct businesses, and a poor merger can result in decreased productivity and increased expenditures.
  • Financial risks: Financial performance may be impacted by M&A transactions because they might be expensive and raise the company’s debt levels.
  • Regulatory and legal risks: Regulatory and legal risks associated with M&A deals include ensuring that intellectual property rights, antitrust, and competition rules are followed.
  • Strategic misalignment: Only when the strategic goals of the target firm and the acquiring company are compatible can M&A deals be successful.
  • Talent retention: Employee uncertainty and concern due to M&A transactions might increase the risk of talent loss.
  • Reputational risks: M&A deals can significantly affect a company’s reputation, especially if stakeholders don’t like the deal.

Conclusion

Mergers and Acquisitions are complex transactions that require careful consideration and effective risk management strategies to ensure success. In Investment Banking, staying updated on the latest trends, techniques, and best practices in M&A is essential. 

If you want to pursue a career in Investment Banking Operations, consider Imarticus Learning’s Certified Investment Banking Operations Professional (CIBOP). The CIBOP course covers various topics, including M&A, financial analysis, valuation, and risk management. It equips you with the skills and knowledge necessary to succeed in this dynamic field. 

Visit Imarticus Learning to learn more about the Investment Banking course and kickstart your career in investment banking.

How CMOs Can Use Marketing Intelligence & Research to Their Benefit

Posted on by Imarticus Learning

Marketing intelligence and research refer to the systematic process of analysing and interpreting information about the market, customers and competitors to make educated marketing decisions. It involves collecting data from various sources, such as market surveys, focus groups, customer feedback, sales data and social media analytics. This data helps identify market trends, customer preferences and growth opportunities, which in turn, aids in devising marketing strategies, product development, pricing and more.

Fierce competition in the business world is compelling CMOs to look for ways to stay ahead of the curve and drive business growth. One of the most effective ways to achieve this is by leveraging marketing intelligence and research to gain valuable insights into the market, customers and competitors. 

Are you an upcoming CMO looking to explore ways to use marketing intelligence and research to gain more control over supply chain availability and scout for potential business opportunities? This article will cover all that you need to know. 

Marketing Intelligence and Research and Their Benefits

Here are some key reasons why marketing intelligence and research are so crucial for CMOs:

Understanding Customer Behaviour

Marketing intelligence helps CMOs understand customer behaviour better. It helps increase customer engagement and ultimately drives sales. By gathering data about customer preferences, interests and buying patterns, CMOs can create marketing campaigns tailored to specific customer segments. 

For example, CMOs can use social media analytics to understand how customers engage with their brand. Creating targeted social media campaigns based on the acquired information will likely resonate with their audience.

Staying Ahead of the Competition

Marketing intelligence also helps CMOs stay ahead of the competition. By monitoring competitors’ marketing campaigns and strategies, CMOs can identify areas where their brand can improve. They can also identify new opportunities for growth and innovation.

Using competitive analysis can identify gaps in the market that the brand can fill. It can lead to the evolution of new products or services that better meet customer needs.

Improving Marketing ROI

Marketing intelligence and research can also help CMOs improve their marketing ROI (return on investment). By analysing marketing data, CMOs can distinguish between effective and ineffective campaigns, discarding the latter. They can then adjust their marketing strategies to focus on the campaigns that generate the highest ROI.

For example, CMOs can use A/B testing to determine which marketing messages resonate best with their audience. This information can then be used to optimise marketing campaigns and improve ROI.

Identifying Industry Trends

Marketing intelligence and research also help CMOs identify industry trends. By keeping up with industry news and analysis, CMOs can identify emerging trends and adapt their marketing strategies accordingly. 

CMOs can use industry reports and analysis to identify new technologies likely to impact their industry. Adopting the relevant technologies can put their brand at the forefront of their respective industry. 

Making Informed Business Decisions

Finally, marketing intelligence and research help CMOs make informed business decisions. By analysing marketing data and industry trends, CMOs can make decisions based on facts rather than intuition. It helps reduce risk and increase the likelihood of success.

Market research can help determine whether a new product or service will succeed. This information can assist in making an informed decision about investing in that product or service.

Common Challenges CMOs Face in Implementing Marketing Intelligence and Research

  • Limited budget for research and intelligence gathering
  • Lack of in-house expertise in data analytics and market research
  • Difficulty in accessing and integrating data from multiple sources
  • Resistance to change from traditional marketing strategies
  • Limited access to customer data due to privacy regulations
  • Difficulty in identifying and defining key performance indicators (KPIs) for measuring marketing effectiveness
  • Balancing short-term and long-term marketing goals
  • Difficulty in predicting consumer behaviour and market trends accurately
  • Managing and utilising large amounts of data effectively
  • Communicating research findings and insights effectively to other stakeholders within the organisation.

Strategies for Overcoming These Challenges

  • Establish clear objectives and goals for the marketing intelligence and research initiative.
  • Ensure marketing intelligence and research initiative align with the overall business strategy.
  • Identify the right tools and technology to gather and analyse data effectively.
  • Build a team with the right skills and expertise to execute the initiative.
  • Ensure that the team has access to the necessary resources and budget to carry out the initiative.
  • Encourage collaboration and communication between different departments to ensure the initiative is integrated across the organisation.
  • Develop a plan for data governance, including data privacy and security policies.
  • Foster a culture of experimentation and learning, where failures are seen as learning opportunities.

Conclusion

As the business landscape continues to evolve, CMOs must stay on top of the latest trends and technologies to ensure they maximise the value of their marketing intelligence and research efforts. CMO training programs provide comprehensive knowledge of marketing concepts and strategies.

IIM Raipur’s CMO course, in collaboration with Imarticus Learning, is an excellent opportunity for marketing professionals to gain the requisite knowledge, skills and practical experience necessary to succeed. This Chief Marketing Officer certification course is designed to give a comprehensive understanding of marketing concepts, strategies and tactics and real-world experience.

Certifications: How it can help in a business analytics career in 2023

Posted on by Imarticus Learning

Introduction

Business analytics has emerged as a strong area of growth. Organisations have realised the importance of analytics. As a result, the demand for analytics professionals is on the rise. These professionals are expected to have a deep understanding of data and how it can improve business performance.

The secret to business analytics is to approach it as a strategic initiative. It should not be looked at just as a technical process. Certifications from reputed organisations can further your career path.

What is business analytics certification?

Business analytics certification is a professional certification programme. It works as proof of knowledge of an individual in this field. It also works as a confirmation of the skills. It helps build one’s credibility and career prospects. In addition, it improves earning potential.

A business analytics certification programme covers a wide variety of topics. Various platforms also come up with certifications that hold value in the industry. A certification in this field is important to showcase that an individual has the required skill and knowledge.

How to select the right business analytics certification?

Selecting the right business analytics certification can be challenging. There are a lot of options available. Here are some factors to consider while selecting the right one:

  1. Relevance to career goals

Choose a certification programme that aligns with one’s career goals. Consider the skills one wants to develop. Look for programmes that offer training in various areas. The important bit here is to match the expectation with the training being provided.

  1. Credibility

It is important to consider the credibility and reputation of the programme. Also, take into account the organisation’s reputation. Search for programmes that have the endorsement of companies and trade associations. This will help to make the right choice.

  1. Curriculum and course delivery

Review the curriculum and course delivery methods. Ensure that the programme covers the topics that are needed. Also, consider the course delivery method. Both these factors are important to understand if the option is relevant.

  1. Eligibility

Check the eligibility requirements of the programme. Some programmes may require specific educational qualifications, work experience or technical skills. The eligibility should be checked properly to ensure it is a good fit.

  1. Cost and duration

Consider the cost and duration of the certification programme. Ensure that the programme is affordable and fits within the budget and schedule. The cost of the programme should not be the only criterion for selection. It can be a case where the right option is a bit costly. But, it would add more value as compared to the cheapest one.

  1. Support and resources

Look for programmes that offer support and resources. Support like study materials, online forums and mentorship help a lot. These resources can help prepare for the certification exam and succeed in the career.

To summarise

Business analytics is a booming field. It is expected to have strong demand for professionals in the future. It is important to have the right certifications in place to identify the right opportunities.

Business analytics certifications can help one gain the necessary knowledge and skills. This knowledge can be used effectively in business decisions. These certifications can help to stand out in a competitive job market.

The Postgraduate Program in Data Science and Analytics from Imarticus Learning can be considered for an in-depth learning experience. It is among the most popular business analytics online courses available. This certificate programme in business analytics helps provide basic to advanced knowledge about business analytics and data science concepts.

What is Decision Analysis and Risk Modelling?

Posted on by Imarticus Learning

Analysing choices concerning predefined benchmarks is part of decision analysis, which helps people make wise choices. Risks, trade-offs, and probable outcomes are among the aspects that are taken into account.

On the other hand, risk modelling is an essential process that helps identify and assess potential dangers connected to a specific decision or condition. It comprises seeing possible threats and devising plans to deal with them successfully while utilising various tools and techniques.

certified management accounting course

The principles of decision analysis and risk modelling can be better understood by aspiring certified management accountants (CMAs) and finance professionals, as these abilities are essential for making wise company decisions.

Also, these ideas are crucial subjects addressed in the CMA Exam. Thus CMA USA training is an excellent approach to gaining proficiency in these ideas.

What is Decision Analysis?

Decision analysis (DA) is a method of decision-making that entails determining and evaluating each component of choice and then acting with the intention that results in the best outcome.

Decision analysis seeks to guarantee that choices are made with access to all pertinent data and options. For instance, a business can choose between two million-dollar investments, or an individual might use it to select between different retirement savings options.

The foundations of decision analysis can be utilised to handle a wide range of difficulties, from complicated commercial problems to straightforward day-to-day issues.

How Does Decision Analysis Work?

Decision analysis enables businesses to assess and simulate the possible results of various actions to choose the best move. The firm must comprehend many facets of a problem to make an informed decision to be productive.

Understanding the many objectives, outputs, and uncertainties involved in the analysis includes using probabilities to gauge how specific actions will pan out.

Framing the issue to permit additional examination is one of the most crucial elements. As the initial step in decision analysis, framing is developing a framework to assess the problem from several angles. These may consist of success indicators, action plans, and opportunity statements.

A model can be constructed to determine the favorability of various outcomes once the framework has been established.

Influence diagrams and decision trees are two types of models.

What Is Risk Modelling?

Compared to more conventional approaches, like purchasing insurance to protect your organisation. 

Creating practical risk analyses, emphasising how beneficial insurance may be, and adopting a more thorough approach to risk research and solutions are all part of risk modelling.

How Does Risk Modeling Work?

Making accurate assumptions about risk requires using historical data and simulation, extreme value theory (EVT), market risk, and expert elicitation. In addition to making assumptions, modelling calculates potential/maximum risk using economic, statistical, and financial methods.

Some people like categorising modelling into three primary categories: hybrid, qualitative, and quantitative. Comparative modelling relies more on experience and irrational knowledge than quantitative modelling on statistical facts and numerical evidence. The hybrid business model, combining the two, will benefit most companies.

Benefits of Decision Analysis

The benefits of decision analysis include the following:

Systematic and structured approach: Decision analysis is an organised, structured method of decision-making that helps guarantee all pertinent data is considered and analysed consistently and impartially.

Improved decision quality: Decision analysis can assist people and organisations in making better decisions and getting better results by discovering and evaluating all pertinent information and possible consequences.

Reduced uncertainty: By offering a transparent and impartial framework for weighing options and gauging risks, decision analysis can help eliminate uncertainty.

Increased efficiency: Decision analysis can assist people and organisations in making more effective use of their time and resources by dissecting difficult decisions into smaller, more manageable components.

Enhanced communication and collaboration: By giving decision-makers a common language and framework for weighing options and analysing risks, decision analysis can aid in communication and collaboration.

Improved risk management: Decision analysis may assist companies in reducing their exposure to risk and avoiding costly mistakes by identifying potential hazards and creating strategies to mitigate or manage such risks.

Benefits of Risk Modelling

Cost savings: Organisations can design systems to reduce costs and increase return on investment by using risk modelling to identify potential hazards and the expenses that go along with them.

Better resource allocation: Risk modelling can assist organisations in allocating their resources more effectively and efficiently by highlighting the most critical risks and possible outcomes.

Improved compliance: Businesses may develop strategies to comply with relevant laws and regulations using risk modelling to detect potential regulatory and compliance risks.

Better stakeholder engagement: By displaying a transparent and impartial approach to managing risks and making choices, risk modelling can assist companies in engaging stakeholders and fostering trust.

Improved competitive advantage: Organisations can obtain a competitive edge in their sector and experience long-term success by successfully managing risks and making more intelligent decisions.

Enhanced strategic planning: By identifying potential risks and opportunities and evaluating the possible effects of various scenarios, risk modelling can assist businesses in creating more successful strategies.

Difference Between Decision Analysis and Risk Modelling

Decision Analysis Risk Modelling
It is a systematic and organised method of decision-making. It is a statistical and analytical approach to risk assessment.
Evaluates all critical data and outcome possibilities. Stresses locating and calculating potential hazards.
Simplifies difficult decisions into simpler, more logical chunks. Reduces risks to manageable, smaller components.
Recognises and assesses trade-offs between alternatives. Analyses the likelihood and possible consequences of various risks.
Evaluates various factors and viewpoints to choose the best course of action. It recognises potential hazards and creates plans to reduce or control such risks.
Aims for better decision-making and better results. Strives to minimise risk exposure and prevent expensive errors.
Requires interpreting information and making subjective judgements. Utilises statistical analysis and objective data.
It can be used in a variety of situations where decisions need to be made. Utilised mainly concerning risk management.

Conclusion

Decision analysis and risk modelling are critical tools for businesses and finance professionals to make informed decisions in a rapidly changing environment. By utilising these techniques, professionals can mitigate risks, maximise opportunities, and improve their organisations’ bottom line.

If you want to enhance your skills and knowledge, consider taking Imarticus Learning’s Certified Management Accountant (CMA) course. This comprehensive US CMA course covers all aspects of the CMA Exam and provides hands-on training in the latest techniques and best practices in risk modelling and decision analysis. With this CMA USA training, you will gain the skills and knowledge to become a certified management accountant, an in-demand profession in the business and finance industries. 

Enrol now in Imarticus Learning’s CMA USA course and take the first step towards a successful career in management accounting.

Benefits of Data-Driven Decisions in Supply Chain Management

Posted on by Imarticus Learning

One of the major attributes driving business success is customer satisfaction. With proper data in hand, companies can work on their supply chain management strategy to cater to customer demands and combat delivery inefficiencies. Supply chain as well as procurement process management produces huge volumes of data. It is important for leaders to adopt the right approach to using valuable data for improved operations. 

Supply chain leaders like the Chief Supply Chain and Operations Officer uses Machine Learning and AI models for improving supply chain operations. Automating a data pipeline is also of great help. A data-driven supply chain provides higher agility and greater productivity, particularly when there are chances of disruptions. Professionals who have completed a supply chain management certification course deal with this subject better. 

Understanding data-driven supply chain management

Data-driven supply chain management includes data usage strategically for better prediction of inventory and production changes, which is closer to real-time. This directly plays a crucial role in quicker decision-making. 

When it comes to a data-driven approach to devising a supply chain management strategy, primarily there is the use of new data sources like AI or ML technologies for making predictions. Data-driven supply chains provide a complete and vivid picture of the entire supply chain performance. 

Benefits of data-driven decisions in supply chain management

As a Chief Supply Chain and Operations Officer, you cannot undermine the importance and benefits of data-driven decisions in supply chain management. Let us look at some of these benefits:

  • Actionable insights

With the use of data-driven decisions within the supply chain, businesses can gain insights into the demands of various products and materials. This helps in getting more accurate forecasts. With access to data in real-time, organisations are in a position to adjust to demand fluctuations or emerging trends. This opens up opportunities in generating more revenue. 

Businesses also get an insight into the logistical capacity requirements thus dealing with inventory undersupply or oversupply issues successfully. Data-driven decisions help in meeting a balance between demand and supply, leading to cost-savings and more importantly, enhanced customer experience. 

  • Improved accountability and end-to-end visibility

When businesses implement data-driven decisions in devising strategies for supply chain management, they have improved accountability of the whole work. Moreover, there is a detailed record of every step in the supply management chain offering end-to-end visibility. 

Transparency in various operations is a vital point of a sustainable supply chain. With real-time data-driven decisions, organisations have complete transparency, which proves to be useful for all stakeholders. Transparency is inclusive of the due diligence measures in supplier appointments, identifying procurement sources as part of procurement process management and the metrics used for calculating carbon emissions. 

  • Improved inventory and logistics management

Inventory and logistics management are integral parts of the supply chain management process. With data-driven decisions, vendors and suppliers have immediate updates if there are any kinds of order backlogs. Along with attending to the backlogs immediately, businesses can devise strategies to adjust the inventory management process.  

The logistics department also benefits from data-driven decisions as they receive real-time information regarding their consignments, different cargo batches and updated delivery status of each consignment. With enhanced operational management, you can track your goods conveniently. The final result is a happy and satisfied customer. 

  • Better planning capacity

Every business wants to expand and for that proper planning is a prerequisite. Data-driven decisions in supply chain management provide valuable insights into emerging trends and the demand for a product. This proves to be highly useful for future project planning and devising and implementing effective business strategies. 

For instance, in a manufacturing company, real-time data and visibility offer valuable insights into various things including manufacturing inefficiencies, production volumes, various challenges related to raw material sourcing, etc. When businesses get more accurate information from data, they can have better planning. With planning, a business gets a competitive edge over others. 

  • Cost-savings

Data-driven decisions help in saving good amounts of money in supply chain operations. This is done by making sure that the demands for raw materials and related products are fulfilled timely. This is important so that there is no delay in the production plants or in the assembly lines. Supply chain operations can be made cost-effective if the products move on the quickest routes in the shortest time span. 

With necessary insights and transparent visibility from data-driven decisions, supply chain executives are successful in addressing various challenges in the supply chain.  Some of these include boosting profitability, reducing wastage and increasing operational efficiencies. 

  • Enhanced customer experience

Whether it is procurement process management or supply chain management, the main aim of any business is to provide the best customer experience. A Chief Supply Chain and Operations Officer implements data-driven decisions for enhanced customer experience. The majority of customers have a positive and smooth experience, making them happy customers. 

With real-time data, officers and managers monitor and analyse supply chain operations closely. They can work on ways to increase accuracy and minimise waiting times for product deliveries to customers. As a result, customers receive their orders on or before time and in good condition. 

Conclusion

Businesses are realising the value and importance of data and data-driven decisions in supply chain management and procurement process management. Right from making improved data-driven decisions for a particular supply chain management strategy to enhancing end-to-end operations, businesses are leveraging data in the best possible manner. 

If you are interested in making a career in the supply chain industry as a Chief Supply Chain and Operations Officer, a supply chain management certification course will be of great help. You can take up an IIM supply chain management programme and become a leader in the supply chain and operations industry. 

Imarticus Learning in collaboration with IIM Raipur offers an Executive Certificate Programme for Global Chief Supply Chain and Operations Officer. This 10-month programme targets senior supply chain professionals and helps them in acquiring operational, technological, strategic and personal skills for carving a niche in the supply chain industry. The study programme has six modules, covering various critical features of supply chain management and operations. 

What does the future of cryptocurrency look like?

Posted on by Imarticus Learning

The rise of cryptocurrency has completely changed how we think about money and transactions. The financial sector has been drastically altered by the emergence of cryptocurrencies like Bitcoin, Ethereum, and others in previously unthinkable ways. But what lies in store for cryptocurrencies in the future? Will it stay strong, alter the financial environment, or disappear into obscurity?

MBA in Fintech course

The future of cryptocurrencies is a hotly debated subject as the twenty-first century advances. Numerous experts believe that as more people become aware of cryptocurrencies’ potential advantages and utility, their use and acceptance will only increase.  

Here are ten points that shed some light on what the future of cryptocurrency may look like.

  • Increased adoption: Cryptocurrencies are becoming more widely accepted as a means of payment, and this trend is likely to continue. As more people become aware of cryptocurrencies and their benefits, they will likely be more willing to use them in everyday transactions. 
  • Greater regulation: Governments worldwide are starting to take notice of cryptocurrencies and are beginning to create rules to govern their use. While this may be seen as a negative by some, it will likely lead to greater adoption and acceptance of cryptocurrencies by businesses and individuals. 
  • More stable prices: One of the cryptocurrencies’ biggest criticisms is their volatility. However, as more people use cryptocurrencies and become more widely accepted, their costs will likely become more stable. It will also make cryptocurrencies a more viable option for investment and payment. 
  • Increased privacy: Privacy is a significant concern for many people regarding financial transactions. Cryptocurrencies offer a level of privacy that is unmatched by traditional financial institutions. People are becoming more concerned about privacy and will likely begin using cryptocurrencies. 
  • Improved security: Cryptocurrencies are secured by advanced cryptography, which makes them almost impossible to counterfeit or hack. As more people become aware of this level of protection, more people will likely begin using cryptocurrencies. 
  • New use cases: While cryptocurrencies are primarily used for payment, they can be used for other purposes. As new use cases for cryptocurrencies are discovered, their value will also likely increase. 
  • Increased efficiency: Cryptocurrencies offer a level of efficiency unmatched by traditional financial institutions. People can process transactions quickly and inexpensively without the need for intermediaries. As more people become aware of this level of efficiency, more people will likely begin using cryptocurrencies. 
  • Greater accessibility: Cryptocurrencies are accessible to anyone with an internet connection, regardless of where they are. It makes them an ideal option for people who do not have access to traditional financial institutions. As more people become aware of this level of accessibility, more people will likely begin using cryptocurrencies. 
  • Integration with traditional financial institutions: While cryptocurrencies are often seen as a replacement for conventional financial institutions, they also have the potential to be integrated with them. For example, cryptocurrencies could facilitate cross-border payments or provide more secure and efficient transactions. As more traditional financial institutions explore the potential of cryptocurrencies, they will likely become more widely accepted. 
  • Continued innovation: Cryptocurrencies are a relatively new technology, and there is still much innovation. With recent developments, cryptocurrencies will become even more widely accepted and valuable. This innovation could come from new use cases, improved security, or increased efficiency.

The future of cryptocurrency looks bright and promising. While there are still challenges, such as regulatory hurdles and price volatility, the benefits of cryptocurrencies are clear. As more people become aware of these benefits, cryptocurrencies will likely become more widely accepted and used, leading to a more efficient and secure financial system.

Discover MBA in Fintech training program with Imarticus Learning

Are you looking to learn FinTech Online? A ground-breaking program, the MBA in Fintech offered by KL University provides comprehensive knowledge of the Fintech industry. This cryptocurrency Course offers practical training to address real-world challenges in the Fintech sector and a thorough understanding of how technology transforms the finance industry. 

Course USPs:

  •  Once you have completed the program, you will be prepared to pursue a career in the Fintech sector and choose the profile that best suits your interests. 
  • This Artificial intelligence in Fintech program explores the sector’s fundamentals. It gives students hands-on experience with cutting-edge technologies like API, Blockchain, Cloud Computing, AI, Machine Learning, RPA, IoT, and Big Data. 
  • The course offers a rare chance to gain a profound understanding of the dynamics of technology, which are constantly changing, and how they affect the financial and other sectors.

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

Why is Noise Removal Important for Datasets?

Posted on by Imarticus Learning

Noisy data in datasets impact the prediction of meaningful information. Studies stand evidence that noise in datasets leads to poor prediction results and decreased classification accuracy. Noise impacts algorithms in missing out patterns in any dataset. To be precise, noisy data is equivalent to meaningless data. 

Data Science Course

When you learn data mining, you get to know about data cleaning. Removing noisy data is an integral part of data cleaning as noise hampers data analysis significantly. Improper data collection processes often lead to low-level data errors. Also, irrelevant or partially relevant data objects might hinder data analysis. For enhancing data analysis, all such sources are considered noise.  

In data science training, you will learn the skills of removing noise from datasets. One such method is data visualisation with tableau. Neural networks are also quite efficient in handling noisy data. 

Effective ways of managing and removing noisy data from datasets

You must have heard the term ‘data smoothing’. It implies managing and removing noise from datasets. Let us look at some effective ways of managing and removing noisy data from datasets:

  • Regression

There are innumerable instances where the dataset contains a huge volume of unnecessary data. Regression helps in handling such data and smoothens it to quite an extent. For the purpose of analysis, regression helps in deciding the suitable variable. There are two variables in regression, which are as follows:

  • Linear Regression 

Linear regression deals with finding the best line for fitting between two variables so that one is used for predicting the other. 

  • Multiple Linear Regression

There is the involvement of two or more variables in multiple linear regression. By using regression, you can easily find a mathematical equation for fitting into the data. This helps in smoothing out the noise successfully to quite an extent. 

  • Binning

When you learn data mining, you will surely learn about binning. It is one of the best and most effective ways of handling noisy data in datasets. In binning, you can sort the data. You can then partition this data into bins of equal frequency. You can replace the sorted noisy data with bin boundary, bin mean or bin median methods.

Let us look at the three popular methods of binning for smoothing data:

  • Bin median method for data smoothing

In this data smoothing method, the median value replaces the existing values that are taken in the bin. 

  • Bin mean method for data smoothing

The mean value of the values in the bin replaces the actual value in the bin in this data smoothing process. 

  • Bin boundary method data smoothing

In this data smoothing method, the maximum and minimum values in the bin values are then replaced by the boundary value that is closest.

  • Outlier Analysis

Outliers are detected by clustering. It is evident from the name that close or similar values are organised in clusters or in the same groups. The values which do not fit into the cluster or fall apart are considered outliers or noise. 

However, outliers provide important information and should not be neglected. They are extreme values which deviate from other data observations. They might be indicative of novelty, experimental errors or even measurement variability. 

To be precise, an outlier is considered an observation which diverges from a sample’s overall pattern. Outliers are of different kinds. Some of the most common kinds are as follows:

  • Point outliers

These are single data points, which rest away quite far from the rest of the distribution.  

  • Univariate outliers

These outliers are found when you look at value distributions in a single feature space. 

  • Multivariate outliers

These outliers are found in an n-dimensional space containing n-features. The human brain finds it very difficult to decipher the various distributions in n-dimensional spaces. To understand these outliers, we have to train a model to do the work for us. 

  • Collective outliers

Collective outliers might be subsets of various novelties in data. For instance, it can be a signal indicating the discovery of any new or unique phenomena. 

  • Contextual outliers 

Contextual outliers are strong noises in datasets. Examples to illustrate this include punctuation symbols in text analysis or background noise signals while handling speech recognition. 

  • Clustering 

Clustering is one of the most commonly used ways for noise removal from datasets. In data science training, you will learn how to find outliers and also the skills of grouping data effectively. This way of noise removal is mainly used in unsupervised learning. 

  • Using neural networks

Another effective way of removing noise from datasets is by using neural networks. A neural network is an integral part of Artificial Intelligence (AI) and a subset of Machine Learning, in which computers are taught to process data inspired by the human brain. It is a kind of Machine Learning process known as Deep Learning where interconnected nodes are used in a layered structure for analysing data. 

  • Data visualisation with tableau

Tableau is a data processing programme which creates dynamic charts and graphs for visualising data in a professional, clean and organised manner. While removing noise from datasets, this programme proves to be truly effective. Clear identification of data is possible with data visualisation with tableau. 

Conclusion

Almost all industries are implementing Artificial Intelligence (AI), Machine Learning (ML) and Data Science tools and techniques in their works. All these technologies work with huge volumes of data, using the most valuable ones for improved decision-making and forecasting trends. Noise removal techniques help in removing unimportant and useless data from datasets to make them more valuable. 

If you are looking to make a career in data science, you can enrol for an IIT data science course from IIT Roorkee. You can also go for a Machine Learning certification course in conjunction with a data science programme. 

Imarticus Learning is your one-stop destination when you are seeking a Certificate Programme in Data Science and Machine Learning. Created with iHub DivyaSampark@IIT Roorkee, this programme enables data-driven informed decision-making using various data science skills. With the 5-month course, learn the fundamentals of Machine Learning and data science along with data mining. Acclaimed IIT faculty members conduct the course. Upon completion of the programme, you can make a career as a Data Analyst, Business Analyst, Data Scientist, Data Analytics Consultant, etc. 

Enrol for the course right away!

Get a free 1:1 Imarticus counselling
Get a free 1:1 Imarticus counselling