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Bookeeping v/s Accounting: What’s the Difference?

Posted on by Imarticus Learning

The finance and accounting domain is burgeoning with new career paths as technology and newer trends keep popping up. Used interchangeably, accounting and bookkeeping are two popular terms the financial industry lives by. 

Accounting, as widely known, refers to analysing, interpreting, classifying, reporting and summarising a business’s financial data. Bookkeeping is limited to recording financial transactions. The two concepts are fundamentally different, each requiring a different skill set. For instance, an aspiring accountant may need to sit for the CMA exam, which isn’t necessary for a bookkeeper. 

Read the article if you are confused about the two and cannot decide which career option is for you. It will walk you through the difference between the two job roles and the responsibilities each entails. 

Bookkeepers v/s Accountants: How are they different?

The differences between bookkeepers and accountants are minor but necessary for defining their responsibilities. While bookkeepers focus on daily updation, accountants are responsible for the more prominent financial image of the company. Read on to learn the job roles and responsibilities of bookkeeping and accounting.

Bookkeeping

Bookkeeping is securing a company’s financial transactions in an organised manner, usually in a ledger. Recording and maintaining such transactions always comes in handy during tax audits and rechecking any financial transaction-based errors. The process is a part of the more extensive work of accounting.

Key Responsibilities

The key responsibilities of a bookkeeper in accounting are as follows:

  • Preparing an updated ledger
  • Separating different essential accounts
  • Developing bookkeeping rules and procedures
  • Running payrolls and invoice generation
  • Ensuring financial ledgers as legally compatible 
  • Maintaining secondary and tertiary accounts, if needed
  • Allocating finances properly to maintain the balance sheet
  • Assisting during trials and tax audits

Accounting

Accounting is measuring, securing and analysing a company’s financial assets in a way that positively affects its growth. In an organisation, an accountant is responsible for creating all-important financial decisions. They are also responsible for tax audits, balance sheet updation, bank statements and error-free financial records.

Key Responsibilities

The key responsibilities of an accountant are as follows:

  • Overviewing and managing all account transactions
  • Analysing budgetary trends and preparing forecasts
  • Ensure timely bank-related transactions in the company
  • Prepare audit-related financial documents
  • Presenting the company’s financial goals 
  • Assisting positive growth in the company’s financial graph

What are the differences between bookkeeping and accounting?

A regular accounting cycle has eight levels: 

  1. New transaction
  2. An entry in the accounting ledger
  3. Posting
  4. Updating the balance sheet
  5. Worksheet duty
  6. Adjusting the trial balances in the trial sheet
  7. Generating a financial statement
  8. Closing the ledger

The first six assignments are in the domain of the bookkeeper. The accountant performs the last two. Apart from the basics, here are some more fundamental differences between the two jobs:

Educational qualifications

Bookkeeping and accounting require different educational qualifications mentioned in the eligibility criteria. 

Bookkeepers can join directly after high secondary completion or with some work experience, depending on the organisation’s needs. 

Accountants need a bachelor’s degree or higher. Many aspiring candidates prepare for the CMA exam or enrol for similar postgraduate diplomas.

Specific skills

Bookkeepers can work without extreme technical or job-specific knowledge. 

Accountants need accounting degrees and previous work experience. The accountant requires technical competence and specialised analytical skills to present the company’s financial growth and trends to the stakeholders. Communication skills and basic knowledge of reports/slides are required to present the company’s financial growth.

Important financial decisions

The complexity of the job is a lot less for bookkeepers. However, their work entails minute attention to financial details and a solid mathematical bent of the mind. Any mistake in the daily updation of a ledger can lead to accumulated errors. However, bookkeepers are outside the decision-making space. 

Accountants require extremely high analytic skills to focus on the company’s financial figures. The accountant’s predictions and decisions pull the company’s graph upward. 

Career potential

Accounting offers a long-term and secure employment opportunity. Even for beginners, this ensures a salary as per industry standards. The competition in the field is high, but there is a rising demand for it. 

Bookkeeping jobs are an excellent start for internships or short-term jobs. Bookkeeping candidates receive a decent salary, and the competition for entry-level jobs is less. Many choose bookkeeping as a potential work experience-gaining job while preparing for higher studies or competitive examinations. 

Conclusion

Choosing the right career in finance can be confusing. Examining the different job roles, eligibility criteria, and required qualifications is necessary to decide the right profession. You can start your career by enrolling in the right finance course.

Imarticus Learning’s Certified Management Accountant (CMA) course in accounting, financial, and business analytics domains is the perfect choice for aspiring accountants. It comes with pass protection that ensures students pass the CMA exam. Imarticus charges 50% of the total fee after passing the examination. The course provides unlimited access to study materials, practical projects, and expert mentoring.  

Book your seats today, or visit Imarticus Learning for more.

How to Become a Supply Chain Analyst

Posted on by Imarticus Learning

A supply chain analyst develops an efficient way to make a robust supply chain strategy with the help of data analytics. Also, he/she interprets and leverages data to enhance performance resulting in overall improvement. 

As daunting as the career might sound, becoming a supply chain analyst is relatively easy. With the correct supply chain analytics certification, one can bag job opportunities as an analyst in leading companies. However, prospective candidates must know and understand the skills required to become a supply chain analyst. 

In this article, let’s learn about the job roles of a supply chain analyst and the steps to become one. 

The job role of a supply chain analyst

Besides being a professional who ensures the company’s supplies meet the customer’s demand, a supply chain analyst plans production, manages inventory management, sources raw material, plans demand, designs supply chain network and plans distribution. The other duties include:

  • Collection and analysis: A supply chain analyst collects and analyses different supply chain data by implementing accurate supply chain methods.
  • Management and coordination: Supply chain analysts have to manage and coordinate vivid supply chain operations with the staff involved in the process.
  • Quality assurance and inventory analysis: A supply chain analyst oversees quality assurance and inventory analysis. By doing inventory analysis, they design robust reports to help the enterprise in prospects.
  • Supply chain hazard identification and analysis: A supply chain has many hazards. A supply chain analyst helps to identify issues and develops strategies to resolve them quickly and efficiently.
  • Training and conflict resolution: A supply chain analyst must possess leadership skills to train his/her staff and resolve any conflict arising amongst team members.
  • Business administration and effective communication: A supply chain analyst is responsible for business administration and must have communication skills to deal with the clientele and their team.
  • Business expansion and strategic initiatives: A supply chain analyst takes up strategic initiatives to expand the business horizon. They adopt many ways to make the business approachable, thus incurring more profit.
  • Collaboration and evaluation: A supply chain analyst has to collaborate with people from different departments – sales and operations, design, marketing, etc. An analyst must use customer trends and previous activities to understand product demand effectively. They even analyse and evaluate routes and collaborate with transport companies to deliver products on time and in order. 

Skills required to become a supply chain analyst 

global supply chain management and operations officers course

The job of a supply chain analyst not only entails research and analysis but also has traces of leadership and effective communication. 

Technical skills 

A supply chain analyst should be well-versed in data analysis, mathematics, SQL, Excel, Hadoop and statistics. They analyse large and multi-dimensional data sets by incorporating various mathematical equations. These calculations also play a crucial role in the cost and savings of raw materials. 

Interpersonal skills 

Supply chain analysts have to work with various stakeholders. Hence, this requires top-notch interpersonal skills. It helps build effective relationships amongst stakeholders and teams and share ideas in a hassle-free way.

Organisational and project management skills 

Strong organisational skills would help a supply chain analyst to achieve long-term goals in a short time. Possessing the above-mentioned skills would not only help them to polish their leadership skills but also help them manage workload efficiently and pace up different projects. 

How to become a supply chain analyst: Eligibility 

A supply chain analyst needs to have specific prerequisite skills and qualifications. A bachelor’s degree in logistics or supply chain management is required to be eligible for the job. Other eligibility criteria are:

  • Candidates must have internship experiences from companies with a working supply chain for at least two years. They should have an understanding of inventory management.
  • An ideal candidate should have impeccable analytical skills and in-depth knowledge of logical reasoning and mathematics. They should also possess adequate knowledge of data collection and analysis.
  • A candidate must have sound theoretical and practical knowledge of data analysis and inventory management tools. It would help them develop useful insights from the data and act accordingly. 

Conclusion 

A supply chain analyst acts as a strategist in an organisation. This makes them an important part of an organisation where they are responsible for logistics, marketing, product management, quality assurance and other important sectors. They also provide insights into newer technologies and these tools further make the business efficient. 

If you are looking for a good supply chain management course, then check out Imarticus Learning’s Executive Certificate Programme in Global Chief Supply Chain and Operations Officer offered in partnership with IIM Raipur. This IIM Raipur supply chain management course will embark you on a journey to a new era of supply chain analytics. This 150-hour interactive session is taught by the skilled IIM Raipur faculty. 

Why Full Stack Developers Must Learn Kubernetes

Posted on by Imarticus Learning

Due to the emergence and growth of cloud computing and microservices, Kubernetes has become very important for a Full Stack Developer.  It is a crucial tool for managing and orchestrating essential containers. 

Nowadays, developers do a lot more than write codes and programs. Choosing the right infrastructure is crucial when working with microservices architecture. Companies count on developers to create and maintain the infrastructure.

In essence, Kubernetes has taken over as the industry standard for defining infrastructure. Read on to learn about Kubernetes and why Full Stack Developers must master Kubernetes.

What is Kubernetes?

Kubernetes is an open-source robust framework for container orchestration. It enables a Full Stack Web Developer to orchestrate and run container workloads automatically. Kubernetes provides numerous tools as a layer of abstraction. 

It helps deploy standardised full-stack applications across various platforms, including package managers, source plugins, monitoring tools, etc. Born out of Borg, a Google project, Kubernetes is considered one of the most popular container orchestration engines. It helps developers to manage a cluster of hundreds and thousands of workloads for running dynamic applications.

However, managing the Kubernetes cluster can be much more complex than managing a conventional application environment. It increases operational costs and is time-consuming. Also, it requires a specialist to monitor the operations. 

Why is it essential for a Full Stack Developer to learn Kubernetes?

Full Stack Developer course

A Full Stack Developer is proficient in handling an application’s front and back ends. The data structures and algorithms that Kubernetes offers are compatible with front and back-end development. Here are some of the reasons why a Full Stack Web Developer needs to learn Kunernetes: 

Easy availability

Kubernetes is an open-source software that can be used by anyone. It is a community lead effort instead and is available to developers free of cost. It does not require any contributions, and developers are welcome to use it for web development and related aspects. 

Enhanced productivity

Improving the efficiency of developers for web development is one of the major advantages of adopting Kubernetes. It helps one eliminate complex manual processes and can ultimately increase productivity for better results. Kubernetes automates a lot of tasks which results in greater efficiency, increasing the productivity of developers.

Stability of applications

The stability of an application is a deciding factor when it comes to evaluating its performance efficiency. Fortunately, users of Kubernetes have no reasons to worry about the performance efficiency of web applications because the platform provides unparalleled stability. Developers can always trust the stability of Kubernetes even if they are dealing with a very complex application.

Increased flexibility and portability

Kubernetes is compatible with practically every imaginable container runtime. The container type does not affect the flexibility of Kubernetes. It can operate with any type of infrastructure, including private and public cloud as well as on-premises services. It is easier for Full Stack Developers to design the perfect scalable solution with a higher degree of flexibility and portability with Kubernetes.

Offers multi-cloud capability

A fantastic benefit of adopting Kubernetes is that it allows one to get rid of traditional conventions and move to the modern cloud infrastructure. A Full Stack Developer can keep all their work in a single cloud as well as can distribute the workload and store it in different clouds. This helps strengthen the resilience of the infrastructure. In this way, a developer can extract the benefits that each cloud has in store to offer, ultimately lowering the expenditure of web development.

Offers systematised automation

It is very challenging to manually manage thousands of containers simultaneously. But Kubernetes helps to overcome this problem with almost zero effort on the part of developers. It is highly automated, and it can launch thousands of containers and manage them automatically. It is a great automation solution with built-in intelligence assisting human administrators. 

Provides better up-time

A server or a container is prone to crash and fail anytime. However, Kubernetes offers the feature of auto-recovery. It can automatically replace the faulty server or container and, thus, reduces the possibility of service interruptions to the users. This is how up time can be explained, the time period when fully functional services are available online. Kubernetes guarantees a high level of up-time.

Conclusion

Kubernetes has proven to be a reliable platform for container orchestration. The number of dynamic features the platform offers will enable you to achieve greater heights in web development and promote faster growth. If you aim to become a full stack developer, consider learning Kubernetes, as it is a high-demand technology with a proper workflow framework.

Do you want to kickstart your career as full stack web developer? Check out the Full Stack Development Programme by Imarticus. This will help you gain insights into the high-scale ability platform that Kubernetes is, as well as learn about GitHub, data structure and algorithms, and much more.  

All You Need To Know About Employee Onboarding

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Companies invest a significant amount of resources in hiring top talent for their team. But this is not where the hiring process ends. Managers have to ensure that the employee is introduced to the workplace, the business processes and the work culture. If this process isn’t properly carried out, it will lead to chaos and even attrition.

Also, businesses continuously struggle to reduce costs. In such a cutthroat environment, conducting the hiring process all over again will eat into the company’s profitability.

corporate training

This is why companies are now focusing on crafting an onboarding plan for new employees that is efficient and effective. It is vital to have an excellent onboarding experience as it boosts employee engagement and aids in retention.

In this blog, we explore how companies can revamp the employee onboarding process. This will build a solid foundation for fresh employees to deliver stellar performances from the get-go.

Golden Rules To Follow While Onboarding New Employees

Have A Standardised Process

The employee onboarding process needs to be an end-to-end solution, factoring in the various touch points between the company and a prospective hire. This journey begins as soon as a company starts engaging with new employees after a lengthy hiring process. This is generally when the company sends an offer letter.

Other steps include deciding the joining date, the waiting period, the orientation week and interaction with the employees. If this process is standardised, it becomes easier for everyone else to follow and smooths out any inefficiencies.

Reduce The Time Taken To Reach Proficiency

One of the key factors to track a smooth onboarding process is to calculate the time taken for the employee to become productive. A detailed onboarding process will ensure that it covers all queries and pain points. This equips the new hire to tackle their job in the most efficient method possible.

The Human Resources teams must work towards offering new hires all the tools required to make a smooth transition and become productive. He/she should learn all about the workflow, hierarchy and exact job roles during the employee onboarding process.

Take Help From Technology

As more companies shift from an onsite mode to remote work and hybrid setups, it is advisable to onboard all new hires via a single unified platform.

This approach makes it easy to build a standardised onboarding process, which can be leveraged to engage potential hires, from any destination, in any time zone.

Factor In Company Branding 

The onboarding process is the perfect opportunity to showcase the brand, the company, and its unique proposition. Even if the new hire does not stay with the company for long, they walk away with a good impression of the business and might even recommend the position to others.

Companies must put together an engaging onboarding kit to help employees understand the vision and mission, culture and legacy of the business.   

Communicate The Basics

Fresh employees must have a clear idea of several basic things. For instance, who must they report to, and who reports to them? They must also be briefed on how to handle grievances, the outline of their job and what is expected of them.

With technology playing such an important role in everyday operations, companies need to walk fresh hires through the various tech tools being used for smoother functioning.

Set Up Team Introductions

Working collaboratively is a growing need, especially for remote and hybrid teams. Companies must make it a part of the onboarding process to set up one-on-one team introductions.

It creates an opportunity to break the ice, and build a rapport. It is also advisable to match fresh hires with potential mentors who they can reach out to for challenges and inspiration.

In Conclusion

A new employee’s first impressions of the company set the expectation for the future. A well-crafted onboarding plan for new employees positions them for success and leads to long-term retention.

If your business is looking to invest in building robust employee onboarding

processes, connect with us at Imarticus and start a conversation.

Benefits of pursuing a course in investment banking

Posted on by Imarticus Learning

Investment banking is related to the field of finance that involves raising capital for companies and governments through underwriting and issuing securities and providing financial advisory services. 

Financial analysts’ total employment is expected to increase by 9% between 2021 and 2031, faster than the average for all occupations.

Over the next ten years, there are expected to be, on average, 32,000 new job openings for financial analyst careers. In addition, several employees are expected to be created due to the need to replace people who change careers or retire from the workforce.

Pursuing a course in investment banking can offer many advantages, that include high earning potential, valuable benefits packages, powerful networking, the opportunity to work with driven peers, and an adaptable skillset. 

 

We encourage readers to consider investing in their education and exploring the potential career opportunities of pursuing this field. With formal learning and training, individuals can help build a career in investment banking. 

Through this blog, we will explore some expected benefits of investment banking in detail and encourage our readers to consider career opportunities in investment banking.

Why is investment banking a lucrative career option?

Investment banking is one of the most intricate and essential financial systems in the world, and it offers a variety of career prospects. It involves various financial services, such as trading securities for one’s account, mergers and helping businesses with M&As, leveraged finance, restructuring, and new issues (Initial public offering), which serve corporate and governmental functions.

As an investment banker, several vital skills are required to be successful in the field. 

Some of these skills include:

  •    Financial Analysis: Investment bankers must have a firm grasp of economic concepts and be able to determine balance sheets, financial statements, and income statements. This includes an understanding of valuation techniques and financial modelling.
  •    Attention to Detail: Investment bankers must have excellent attention to detail, as even minor financial models or analysis errors can have significant consequences.
  •    Time Management: Investment bankers must be able to manage their time efficiently, as they often work on multiple projects simultaneously and must meet tight deadlines.
  •    Relationship Building: Investment bankers must build strong relationships with colleagues, clients, and other stakeholders. This requires strong interpersonal skills to work well in a team environment.
  •    Strategic Thinking: Investment bankers must think strategically and develop uniquely creative solutions to complex financial problems.

Overall, investment banking is a popular and fast-paced profession that needs a unique combination of analytical, communication, and interpersonal skills.

What Are the Benefits of an Investment Banking Course?

  •    High Earnings Potential

One of the most attractive benefits of pursuing investment banking courses is the potential for high earnings. Investment bankers are some of the highest-paid professionals in the finance industry, with salaries ranging from $100,000 to $200,000 or more. Additionally, many investment banks offer substantial bonuses, which can significantly increase an individual’s total compensation.

  •    Valuable Benefits Packages

In addition to high salaries and bonuses, investment banks often offer valuable benefits packages to their employees. These packages can include healthcare, retirement plans, life insurance, and other perks. The total value of these benefits can substantially increase and provide employees with financial security and peace of mind.

  •    Working with Driven Peers

Another benefit of pursuing a course in investment banking is the opportunity to work with driven peers. Investment banks typically recruit top talent from prestigious universities and business schools, which means that intelligent, motivated, and ambitious individuals will likely surround those working in this field. This can create a stimulating and challenging work environment that can push them to reach their full potential.

  •    Powerful Networking

Investment banking courses also provide opportunities for networking and building connections with industry professionals. For example, investment banks often hold recruiting events and information sessions for students, allowing them to connect with potential employers and learn more about the industry. Additionally, many investment bankers maintain strong client relationships, which can lead to valuable business connections and potential job opportunities.

  •    Adaptable Skillset

Pursuing a course in investment banking can also provide individuals with an adaptable skillset that can be applied to various industries and professions. Investment bankers develop skills in financial analysis, communication, problem-solving, and strategic thinking, which are valuable in almost any business setting. Additionally, the industry’s fast-paced and constantly changing nature can help individuals develop flexibility and adaptability, which are essential for success in any field.

The Final Words

Pursuing a course in investment banking can be an excellent choice for those searching for a dynamic and demanding career in finance. Investment banking is a fulfilling career for people dedicated to their professional development because of the potential for high compensation, the abundance of options for career growth, and the chance to work on fascinating and complex financial transactions. 

People can position themselves for success and a bright career in this exciting and profitable business by acquiring the necessary skills and information through an investment banking program.

 The Certified Investment Banking Operations Professional (CIBOP) program, offered by Imarticus Learning, is a flagship course that has received industry approval. This curriculum ensures 100% job placement and is best for students with fewer than three years of experience. Contact us through the chat support system, or visit one of our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Search Engine Marketing can be easy to learn: Here’s how

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Are you a student wondering how to increase the visibility of your website? Understanding search engine marketing tactics can be incredibly lucrative and beneficial for young entrepreneurs. 

Understanding your way around technology has become an invaluable skill these days, and the ability to make your digital presence more visible is one of those skills that can put you ahead in any industry. 

If you’re looking to comprehend how search engine marketing works quickly, this post will teach you all about it so that you can start implementing methods right away.

So if you want to learn the basics of search engine marketing in no time, read on! 

Keywords: The foundation of search engine marketing

 

Regarding search engine marketing, keywords play a critical and enduring role. To find the answers they’re looking for, people input keywords into their searches that are then used by search engines like Google to establish the relevance of a website’s content, returning the most relevant results. 

With a dedicated keyword strategy in place, businesses can also increase their profile and attract more potential customers based on words related to their business they might use while searching online.

SEM for students: The basics

  • Do Your Research 

Research is essential for success in any field. Before diving into your SEM project, ensure you know the SEO and SEM basics. This includes understanding how Google works and learning about keyword research and optimization strategies. There are plenty of free resources for students. Once you know the basics, you’ll be able to move on to more advanced concepts quickly.  

  • Get Educated 

The best way to start learning about SEM is by getting educated. That means reading up on the basics, so you have a broad understanding of what it is and how it works. Plenty of free online resources, such as articles and tutorials, will help get you started. Once you have a good base knowledge, you can start diving deeper into specific areas of SEM that interest you.  

  • Jump Right In 

Once you’ve got the basics down pat, it’s time to jump in and start practicing search engine marketing yourself. Start small and work your way up; create simple campaigns with limited budgets and see what results you can get. You can also use tools like Google Ads or Bing Ads to experiment with different campaigns without spending too much money or taking too many risks. This will help give you an idea of which strategies work and don’t so that when it comes time to create more extensive campaigns for bigger budgets, your chances of success are much higher.  

  • Stay Up To Date With Trends 

The world of search engine marketing is constantly changing, so it’s crucial to stay up-to-date with the latest changes happening in the industry. You will get better equipped to optimize your campaigns and increase their effectiveness if you know the most recent developments in the SEM industry, which may initially seem intimidating.

 Whether you are a beginner or an expert, there’s always something new to discover in search engine marketing. Do your research, start small, stay up-to-date with trends, and don’t forget that practice makes perfect–you’ll soon find yourself becoming an expert in no time! 

Discover IIT Roorkee digital marketing certification course with Imarticus Learning

With Imarticus Learning, learn about the IIT Roorkee digital marketing course. Businesses today rely on the latest technology and digital channels to communicate with their current and potential customers in the age of digital transformation. 

Course Benefits For Learners:

  • Learn SEO online, comprehend the most recent trends and algorithms, and participate in digital marketing projects if you want to build a rewarding career in MarTech and digital marketing.
  • Through live online sessions and conversations, learners can receive instruction from some of India’s top educators and specialists.
  • We have created this advanced digital marketing certification course and MarTech course in collaboration with IIT Roorkee for those searching for the best online marketing course and wanting to learn industry fundamentals from a recognized university.

Importance of Data-Driven Decisions in Supply Chain Management

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Data-driven decision-making has become increasingly important in Supply Chain Sourcing and Management. Organisations require experts in supply chain analytics to collect, analyse and interpret data, thus optimising supply chain operations and achieving business objectives.

Pursuing a supply chain analytics certification course can provide individuals with the necessary skills and knowledge to make data-driven decisions and excel in supply chain management. 

This article will explore the importance of data-driven decision-making in supply chain management and how it can benefit organisations.

What Is Data-Driven Decision-Making?

Data-driven decision-making involves using data to inform and validate a course of action before committing to it. It can take various forms in business, such as collecting survey responses or launching products in test markets. 

global chief supply chain and management course

Integrating data into the decision-making process will depend on business goals and the types and quality of data available. 

While data collection and analysis have always been significant for large corporations and organisations, modern technology allows businesses of all sizes to collect, analyse, and interpret data into actionable insights. 

Here are some examples:

  • Collecting survey responses to identify products, services, and features that customers desire.
  • Conducting user testing to observe customer behaviour and identify potential issues before an entire release.
  • Launching new products or services in a test market to gauge performance and understand customer needs.
  • Analysing shifts in demographic data to determine business opportunities or threats.

Benefits of Data-Driven Decision-Making

Data-driven decision-making offers several benefits that can improve business performance and competitiveness. 

Some of the critical benefits of data-driven decision-making are:

Objective decision-making: Data-driven decision-making removes bias and subjectivity, ensuring fact-based decisions rather than opinions or assumptions.

Better accuracy: By leveraging data and analytics, organisations can make more accurate decisions aligned with their business goals and objectives.

Improved efficiency: Data-driven decision-making enables organisations to make faster and more informed decisions, reducing the time and resources required for decision-making.

Risk mitigation: Data-driven decision-making enables organisations to identify and mitigate risks by analysing data and identifying patterns and trends.

Cost reduction: Data-driven decision-making can reduce costs by identifying inefficiencies and optimising processes.

Improved customer experience: By analysing customer data, organisations can gain insights into customer behaviour and preferences, improving customer experience and loyalty.

Competitive advantage: Data-driven decision-making can give organisations a competitive advantage by enabling them to make more educated and effective decisions than their competitors.

Applications of Data-Driven Decision-Making in Supply Chain Management

Data-driven decision-making has numerous applications in supply chain management, including:

Demand forecasting: Supply chain managers can effectively estimate product demand using data-driven decision-making by analysing historical data and market trends, which enables them to optimise inventory and production planning.

Inventory optimisation: Supply chain managers can optimise inventory levels and save costs associated with excess or stock-out inventory by analysing data on inventory levels, lead times, and demand patterns.

Supplier selection and management: Supply chain managers may make informed judgements about which suppliers to engage with and how to manage those relationships by analysing supplier data on quality, cost, delivery time, and reliability.

Logistics optimisation: Supply chain managers may optimise logistics and cut down on transportation expenses by analysing data on lead times, delivery performance, and transportation costs.

Quality management: Supply chain managers can leverage data on product defects and customer complaints to make informed decisions about quality management and identify areas for improvement in the supply chain.

Risk management: Supply chain managers can make data-driven decisions regarding risk management and build strategies to mitigate risks by analysing data on supply chain interruptions and vulnerabilities.

Sustainability: Supply chain managers can establish methods to lessen their environmental effects and make data-driven decisions regarding sustainability by analysing data on waste, energy use, and carbon emissions.

Challenges in Implementing Data-Driven Decision-Making in Supply Chain Management

While data-driven decision-making offers many benefits in supply chain managementhttps://imarticus.org/blog/benefits-of-data-driven-decisions-in-supply-chain-management/, there are also several challenges that organisations may face when implementing it. 

Some of the key challenges are:

Data quality: Data accuracy, completeness, and consistency can impact the effectiveness of data-driven decision-making. Ensuring data quality requires proper data management processes and tools.

Data integration: In supply chain management, data comes from various sources, such as suppliers, logistics providers, and internal systems. Integrating and analysing this data can be challenging, as it may come in different formats and structures.

Data analysis: Analysing large amounts of data can be time-consuming and complex, requiring specialised skills and tools. Ensuring data is appropriately analysed and interpreted is critical to making informed decisions.

Change management: Implementing data-driven decision-making requires organisational culture, processes, and technology changes. Resistance to change can be a significant challenge that businesses must address.

Cost: Implementing data-driven decision-making requires investment in technology, tools, and resources. The cost of implementing and maintaining these systems can be a challenge for some organisations.

Data privacy and security: As data-driven decision-making involves collecting and analysing large amounts of data, ensuring the confidentiality and security of that data is critical. Organisations must ensure that data is protected adequately from breaches and misuse.

Human error: Human error can impact the accuracy and reliability of data-driven decision-making. Proper training and processes can minimise the risk of errors.

Best Practices for Effective Data-Driven Decision-Making in Supply Chain Management

To ensure effective data-driven decision-making in supply chain management, organisations should follow these best practices:

  • Define clear objectives: Define the business objectives and key performance indicators (KPIs) you want to achieve using data-driven decision-making. 
  • Identify relevant data sources: Identify the data sources and types needed to achieve the objectives. 
  • Ensure data quality: Ensure the data collected is accurate, consistent, and complete. Implementing data quality controls and monitoring makes it achievable. 
  • Analyse data: Analyse the data to identify trends, patterns, and insights that can help inform decision-making. Use advanced analytics and visualisation tools to present the data meaningfully. 
  • Integrate data: Integrate the data from various sources and systems to gain a holistic view of the supply chain. It will help identify dependencies and potential bottlenecks. 
  • Establish data governance: Establish practices to ensure the security, privacy, and compliance of the data collected and analysed. 
  • Involve stakeholders: Involve stakeholders from different areas of the supply chain in the decision-making process. It can help ensure that business decisions align with the business objectives. 
  • Continuously monitor and improve: Monitor the data and KPIs to identify areas for improvement and refine the decision-making process.

Conclusion

Data-driven decision-making is crucial in complex and global supply chains. Effective implementation is necessary to overcome data quality, integration, and governance challenges. 

Many options are available for those interested in pursuing a career in supply chain management. Imarticus Learning’s IIM Raipur Supply Chain Management course is one such option.

Additionally, the Supply Chain Analytics Certification course offers various certifications. These courses help professionals gain the skills and knowledge to excel in supply chain sourcing and management. 

Visit Imarticus Learning for more information.

What are Deep Neural Networks and How are They Different From Artificial Neural Networks?

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Neural networks have become a more widely used data science and machine learning technique for various applications. Neural networks have used artificial neural networks (ANNs) for many years.

But, as technology has developed, Deep Neural Networks (DNNs) have become a more advanced variety of neural networks.

Machine learning requires a solid grasp of the distinctions between ANNs and DNNs, and working with them successfully necessitates a solid grasp of programming languages like Python.

By learning machine learning with Python, you can gain the skills to work with ANNs and DNNs to build more powerful machine-learning models for real-world applications. 

This blog will explore the differences between ANNs and DNNs, their structures, types, advantages, and applications.

Artificial Neural Networks

What is ANN?

ANNs comprise layers of interconnected nodes, or neurons, that process input data, output results, and receive input data. With an ANN, each neuron is linked to several other neurons, creating a network of nodes that can handle sophisticated data processing.

The single-layer perceptron is the most fundamental type of ANN; it comprises a single layer of neurons that analyse input data and provide a binary output.

Types of ANN

There are several types of ANNs, including:

Radial Basis Function Networks

ANNs with the aim of approximating functions are known as radial basis function networks (RBFNs). RBFNs use radial basis functions to convert the input data into a higher-dimensional space divided into classes or categories.

Self-Organizing Maps

Self-Organizing Maps (SOMs) are artificial neural networks (ANNs) made to figure out how to organise high-dimensional input, like pictures or sounds.

SOMs map the input data into a low-dimensional grid using a competitive learning process to visualise and analyse the data.

Feedforward Neural Networks

The simplest type of ANN is a feed-forward neural network, which has a single layer of input neurons, one or more hidden layers of processing neurons, and a layer of neurons for output.

Without any feedback connections between the layers, data travels from the input layer via the concealed layers to the output layer.

Advantages of DNN

Better Accuracy: In tasks requiring higher accuracy, like speech recognition, image identification, and natural language processing, DNNs can outperform traditional ANNs.

Reduced Feature Engineering: DNNs can automatically learn features from raw data since they require less feature engineering than classic ANNs, which results in more accurate and efficient models.

Improved Training: DNNs are more resilient and better equipped to manage data variances since they can be trained using massive volumes of data.

Applications of ANN

ANNs have numerous practical applications, including:

  • Image recognition
  • Natural language processing
  • Speech recognition
  • Robotics
  • Financial forecasting

Python packages like TensorFlow and Keras can be used to implement ANNs. These libraries have built-in tools for visualising ANN structures and functions for developing and training ANNs.

In machine learning methods, particularly ANNs, Python objects and lists can store and modify data.

Deep Neural Networks

DNNs comprise several layers of neurons, each of which processes incoming data before transmitting the results to the layer above it. Depending on the particular requirements of a task, a DNN’s structure can be modified to include different numbers of layers and neurons in each layer.

Types of DNN

There are several types of DNNs, including:

Long Short-Term Memory Networks

RNNs with Long Short-Term Memory (LSTM) is made to retain information for extended periods. To better handle sequential data, LSTMs include a gating mechanism that allows them to recall or forget data from earlier inputs selectively.

Convolutional Neural Networks

Convolutional Neural Networks (CNNs) are a specialisation of Deep Neural Networks (DNNs) that handle multi-dimensional input such as photographs. 

CNNs use convolutional layers to separate features from the input data, which they subsequently utilise to find patterns and objects in the data.

Recurrent Neural Networks

Recurrent Neural Networks (RNNs) are a subset of DNNs that handle time series data and plain language. RNNs utilise feedback connections among the network’s neurons, enabling them to recall prior inputs and draw on that knowledge when processing new inputs.

Advantages of DNN

Above other machine learning methods, Deep Neural Networks (DNNs) provide many advantages, including:

Improved accuracy: DNNs are more accurate than conventional machine learning models, especially when handling complex data.

Better scalability: DNNs are appropriate for big data applications since they can handle massive datasets with millions of samples.

Flexibility: DNNs are adaptable to many data formats and can be used to solve various issues, including natural language processing and picture recognition.

Applications of DNN

DNNs have numerous practical applications, including:

  • Image and video recognition
  • Natural language processing
  • Speech recognition
  • Autonomous vehicles
  • Healthcare
  • Finance

DNNs are very effective at tasks that call for high levels of accuracy and a lot of data. They are now an essential artificial intelligence component and have many possible applications in several fields.

Differences Between ANN and DNN

Machine learning algorithms like Artificial Neural Networks (ANNs) and Deep Neural Networks (DNNs) are made to recognise patterns in data and learn from them. Yet there are several significant distinctions between ANNs and DNNs.

Number of Layers

The number of network layers distinguishes ANNs from DNNs, which is one of their primary differences. Whereas DNNs can have dozens or even hundreds of layers, ANNs typically only have one or two layers of neurons.

It enables DNNs to analyse more intricate patterns and analyse complex data.

Complexity

DNNs have more layers and a more extensive architecture than ANNs, making them more complex overall. DNNs can evaluate more complex data and find subtler patterns thanks to this complexity.

Training Data Requirements

Due to their greater complexity and number of parameters, DNNs often need more training data than ANNs. DNNs might take longer and use more resources to train than ANNs do.

Computational Power

DNNs need more processing power than ANNs because of their bigger size and more intricate architecture. Particularly for large datasets, it may make it more difficult and expensive to train DNNs.

Performance

On complex tasks requiring the recognition of complicated patterns in data, DNNs typically perform better than ANNs. Yet, ANNs can still be helpful for more focused tasks that call for recognising simpler patterns.

Conclusion

The field of Artificial Neural Networks (ANNs) is rapidly expanding. It is being utilised in various industries and fields, making it an exciting area to explore in data science and machine learning. 

If you are interested in pursuing a career in this field. In that case, having a solid foundation in Python programming, particularly in dealing with Python Objects and List, and a thorough understanding of machine learning with Python is essential.

Imarticus Learning’s Certificate Program in Data Science and Machine Learning course offers a comprehensive curriculum that covers all aspects of data science and machine learning, including Python programming, machine learning algorithms, data visualisation, and more.

Take the first step towards a fulfilling career in the exciting field of data science by visiting Imarticus Learning and checking out our IIT data science course today.

Waste Reduction With Lean Supply Chain Management

Posted on by Imarticus Learning

A company’s capacity to run effectively and efficiently while cutting waste is crucial to its success. Waste is a problem that is particularly prevalent in the supply chain management industry.

By implementing lean supply chain management practices, companies can reduce costs, boost customer happiness, and improve operational performance.

Those pursuing a supply chain management career, such as a Supply and Operations Planner, will find their knowledge of waste reduction principles critical to their success.

The importance of waste reduction in supply chain management, lean supply chain management principles, the advantages of waste reduction, and best practices for applying it will all be covered in this article.

What is Lean Supply Chain Management?

supply chain management courses

Eliminating waste and maximising efficiency in the supply chain are vital components of the lean supply chain management philosophy. Finding and removing waste and inefficiencies in every part of the supply chain entails a continuous improvement process.

By reducing waste and maximising value, lean supply chain management seeks to build a lean and flexible supply network that can swiftly respond to consumer demands.

It is based on the ideas of lean manufacturing, which Toyota pioneered. Achieving a shared waste reduction and continual improvement objective entails integrating all supply chain stakeholders.

Creating a customer-centric supply chain that is responsive, effective, and sustainable is the ultimate goal of lean supply chain management.

Why Waste Reduction Matters in Supply Chain Management

Waste reduction is crucial to supply chain management since it affects the system’s effectiveness and efficiency. There are many different types of waste, which can increase expenses, lower product quality, and lengthen lead times.

Reducing waste can help businesses manage risks and supply chain interruptions while enhancing operational performance, customer satisfaction, and sustainability.

By putting waste reduction first, businesses streamline their operations, boost productivity, and lessen their environmental impact, promoting customer loyalty, increasing brand perception, and improving stakeholder relations.

Critical Principles of Waste Reduction in Lean Supply Chain Management

Lean supply chain management’s guiding principles for reducing waste are based on those of lean manufacturing and include the following:

Value – Eliminate the tasks that do not create value for the consumer and concentrate on those that do.

Flow – Ensure that products, information, and materials move through the supply chain promptly and efficiently.

Continuous improvement – Continuously identify and eliminate waste and inefficiencies by making ongoing progress.

Standardisation – To reduce variability and boost efficiency, standardise processes and procedures.

Visual management – Use visual tools to identify waste, perform monitoring, and share information throughout the supply chain.

By concentrating on these concepts, businesses may develop a culture of waste reduction and ongoing development, leading to a lean and effective supply chain that is responsive to consumer demand, minimises waste, and maximises value.

Benefits of Waste Reduction in Supply Chain Management

There are many benefits of waste reduction in supply chain management, including:

Improved operational performance – Companies may streamline their operations and boost efficiency by decreasing waste, leading to shorter lead times, higher-quality products, and enhanced performance.

Increased customer satisfaction – By decreasing waste and enhancing operational performance, firms may produce products and services that meet or exceed consumer expectations, resulting in better customer satisfaction and loyalty.

Decreased costs – Waste reduction enables businesses to cut back on wasteful spending, boost profitability, and create a supply chain that is more cost-efficient.

Improved sustainability – By minimising waste production and resource consumption, businesses may create a more ecologically friendly and sustainable supply chain.

Enhanced risk management – Companies can better manage risks and disruptions and lessen the effect of unplanned events on their operations by developing a more effective and agile supply chain.

Improved stakeholder relations – Companies can boost their brand, strengthen stakeholder relations, and draw in customers that respect environmentally friendly company practices by supporting waste reduction and sustainability.

Competitive advantage – Businesses may attract clients who respect environmentally friendly business practices by promoting trash reduction and sustainability.

Enhanced supply chain visibility – Companies can boost visibility into their supply chain and find inefficiencies and chances for improvement by employing standard processes and visual management tools.

Best Practices for Implementing Lean Supply Chain Management to Reduce Waste

Here are some best practices for implementing lean supply chain management to reduce waste:

  • Identify and prioritise waste – The first step in minimising waste is to recognise where it occurs in your supply chain. Perform a waste analysis to determine waste sources and prioritise which areas to address. 
  • Standardise processes – Developing standardised procedures aids in minimising waste and reducing unpredictability. Implement regular work practises and visual management tools to make operations more dependable and manageable. 
  • Foster a culture of waste reduction – Engage staff members at all organisational levels to advance a culture of waste reduction and continual improvement. Motivate workers to recognise and report waste and reward those helping reduce waste. 
  • Optimise inventory – In the supply chain, excess inventory is a substantial source of waste. Use just-in-time inventory management to reduce waste, increase cash flow, and lower inventory levels. 
  • Streamline transportation – Waste might also happen during transportation. Optimise transportation modes and routes to minimise waste and lessen environmental impact. 
  • Improve supplier relationships – Establish waste reduction and ongoing improvement partnerships by working closely with suppliers. Work with suppliers to streamline procedures, shorten lead times, and cut waste. 
  • Embrace technology – Use technology to track and analyse data, automate procedures, and find areas that need work. Use supply chain management software to improve operations and visibility. 
  • Continuously monitor and improve – Continuous improvement is a fundamental lean supply chain management principle. To reduce waste and boost efficiency, constantly assess supply chain performance, pinpoint problem areas, and make necessary adjustments.

Conclusion

Lean supply chain management relies heavily on waste reduction, which boosts operational efficiency, increases sustainability, and lowers risk. Companies may boost productivity, foster teamwork, and gain a competitive edge by applying best practices for waste reduction in the supply chain.

To gain a deeper understanding of supply chain management and learn how to reduce waste effectively and optimise supply chain performance, consider pursuing a professional certification in supply chain management. 

Imarticus Learning’s Professional Certification in Supply Chain Management & Analytics course is designed for individuals seeking to enhance their skills and knowledge in supply chain management.

Graduates can pursue various roles, including Supply and Operations Planner, and gain a competitive edge in the job market while contributing to waste reduction efforts. Enrol now at Imarticus Learning to take the first step towards a successful career in supply chain management.

10 Things to Look for in a Fintech Course

Posted on by Imarticus Learning

Fintech works at the intersection of banking and technology. It uses technology to enhance and streamline financial services and procedures, such as banking, payments, investing, and insurance. Fintech refers to a wide variety of technologies and applications, such as mobile banking apps, online financing platforms, digital wallets, robo-advisors and blockchain-based solutions. Fintech is changing the financial industry by making it more approachable, efficient, and customer-centric.

Fintech Course

Fintech training can help you become more fiscally savvy and make better financial decisions. Taking a fintech course is like investing in a high-growth stock – it’s a smart move that can pay off big in a rapidly advancing global digital economy.

Why a fintech certification course is important for jobs in India?

Here are the reasons why a certificate in fintech is valuable in the Indian market:

  • With innumerable innovations and technological headways in finance, professionals with a certificate have a first-hand understanding of their work and its implications on the industry and its services. 
  • Fintech courses in India help professionals understand technological advancements and their impact on the industry, which can give them an edge over other candidates during job interviews. 
  • Fintech courses can aid students in securing their prospects.

Fintech is a lucrative sector that attracts many applicants competing for jobs, intensifying competition.

10 factors to consider while choosing a fintech course

The fintech industry’s rapid growth has increased demand for qualified personnel. As a result, several educational institutions are now offering fintech courses. They ensure you receive the best training possible. If you’re considering enrolling in a fintech certification course, then there are a few things you should look out for.

Curriculum: The curriculum is the first consideration when selecting a fintech course. Any pertinent fintech subjects, such as blockchain, cryptocurrencies, and digital payments, should be covered in the curriculum. Also, it must be current and pertinent to ongoing market trends.

Faculty: The course’s faculty should also be taken into account. The teachers should be seasoned experts with job experience in the fintech sector who are well-equipped to teach the material. To guarantee a well-rounded education, look for classes taught by a combination of academic experts with business professionals.

Industry collaborations: Because the fintech sector is developing quickly, selecting a course that offers collaborations with top fintech firms is critical. You can develop a network of connections in the business and obtain practical experience through these collaborations.

Flexibility: Courses in fintech should be adaptable enough to fit your schedule and learning preferences. Search for programmes that allow for online or hybrid learning, as well as part- or full-time enrollment.

Accreditation: It is crucial to ensure that the course you select satisfies the requirements established by regulatory and industry organisations. Search for programmes that have earned accreditation from respected bodies like AACSB or EQUIS.

Practical knowledge: The fintech sector highly values practical knowledge; thus, the school you pick should offer practical application of theoretical knowledge in simulated real-world scenarios. Look for programmes that provide case studies, internships, and other hands-on learning opportunities.

Career assistance: To shift into the fintech business, search for schools that offer career support. Assistance with preparing a résumé and cover letter, networking opportunities, and job placement services are some things to look out for.

Improve your skills: The fintech sector is quickly developing; therefore, keeping up with innovations and technology is essential. Look for programmes that host seminars, conferences and other industry-related events offering certifications.

Develop your network: In every industry, networking is essential, and the fintech sector is no exception. Top fintech institutes have well-placed alumni that can add to your network. In addition, to expand your network and get insightful information, join industry events, sign up for clubs and associations, and connect with industry leaders on LinkedIn.

 Understand the fintech industry: Finally, understanding the fintech business and its numerous segments is vital before pursuing a career. Make sure your chosen course covers fintech firms and the most recent trends, breakthroughs, and technology in the field.

Your success in this ever-changing field will depend on the fintech course you choose. You can ensure that you receive the greatest education possible and are adequately equipped to pursue a career in fintech.

Conclusion

The SP Jain School of Global Management and Imarticus Learning have partnered to offer a financial technology course. It gives students a unique and valuable learning experience by fusing the latest industry knowledge and methods with a rigorous academic curriculum. The programme covers many topics, like digital banking, blockchain technology, digital payments, and alternative financing. Additionally, you will receive the remarkable SP Jain fintech certification.

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