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Month: August 2022

Avoid these 6 mistakes while preparing a financial statement

Posted on by Imarticus Learning

Avoid these 6 mistakes while preparing a financial statement

Financial statements are prepared on a particular date and show the business’s position as of that date. Therefore, it is essential to prepare financial statements accurately. They are the basis on which future business decisions are taken. However, there are chances that certain inadvertent errors may arise while preparing company financial statements.

What are these common mistakes that you should avoid while preparing What are these common mistakes that you should avoid while preparing financial statements? This is followed by how you can learn financial analysis to become a professional financial analyst.

Upcoming data and analytics trends in 2022

Posted on by Imarticus Learning

Upcoming data and analytics trends in 2022

Data-driven decisions are the norm for today’s tech industry, and there is a subsequent demand for employees skilled in data analytics. Insights without actions are a thing of the past, which is why young professionals are turning to data analyst certification courses in addition to their education. The data and analytics trends shaping 2022 are insights and their necessary actions, real-time data analysis and decision-making, and implementation of artificial intelligence and machine learning, among others.

Why is it Important to Keep Up with Data and Analytics Trends and Learn Data Analytics?

Simply put, such courses help professionals stand out and have a better chance at job interviews. You would probably agree that choosing the right data analyst certification course is a top priority, as there can be courses that still comprise an outdated syllabus. You would want to learn data analytics from a course that encompasses the current trends in the market, and that’s how it should be.

Let’s look at some upcoming data and analytics trends to help you find the right data analyst certification course.

AI-powered Analytics

Artificial Intelligence (AI) has been gaining importance every year in each field, and data and analytics are one of the fields that stands to gain tremendously from its implication. AI has significantly improved decision-making quality by providing access to novel data sources. Amounts of data amassed by companies are forever increasing to know more about their target customers, making it challenging to analyse all of it correctly.

Machine learning (ML) and AI are powerful technologies that allow organisations to make the most out of valuable insights resulting from vast amounts of data. While these technologies are necessary now, they will soon be an essential part of organisations in the coming years. The number of organisations leveraging AI and ML will increase as they look to identify patterns, boost sales, and improve efficiency.

Data Fabric

Transforming current models into data fabric models allows businesses to store, locate, and leverage customer data more effectively. It serves as a robust framework to standardise an organisation’s data management techniques and provides consistent capabilities in multi-cloud environments. With constantly increasing data complexity, businesses will resort to this framework. This framework can reuse and combine various integration styles, technologies, and data hub skills.

The data fabric model significantly reduces maintenance, design, and deployment, lowering system complexity. Its comprehensive approach makes for more relevant customer experiences. Businesses get simplified access to more significant amounts of data, which means more informed decisions regarding customer behaviour and interactions.

Real-time Data Processing

Organisations want to act quickly, and who can blame them when a day later might be too late? Whether it pertains to developing a marketing campaign or something else, real-time data processing and decision-making are a couple of essential aspects within this list of data analytics trends. Businesses can no longer rely on or utilise data sets that are analysed monthly; this is how they stay ahead of the competition these days. There is a need for constant and continuous analysis of data sets in a bid to uncover underlying patterns or changes in customer behaviour.

Real-time data processing and decision-making require newfound adaptability and agility for teams to act on time and seize opportunities. The focus on real-time data processing, analysis, and decision-making will continue as businesses want to respond to changes as they arise to stay ahead of the competition.

Agile and Composable Data & Analytics

Composable data and analytics infrastructure have unmatched potential in terms of scale. The reasons for the popularity of composable and agile data and analytics are comprehensive resource management choices and automation options. Composable infrastructure helps speed up crucial business processes while also circumventing overprovision problems.

The data fabric model acts as the foundation required for agile and composable data and analytics. Capabilities such as driving DataOps and processing hardware are significantly improved, with reduced costs, by only providing data as needed and moving data to other storage systems.

Conclusion

Data and analytics aim to create a flexible, friendly, and smooth user experience by leveraging technologies such as AI and ML. The above data and analytics trends enable team leaders to connect their actions to the insights they receive, promote productivity and agility, encourage inter-departmental collaborations, and enhance the organisation’s analytics capabilities.

For those wondering how to become a data analyst, take a look at this data analytics certification course by Imarticus Learning. This data analytics certification course encompasses a vast syllabus with the latest data and analytics trends, specially designed to provide aspiring professionals with current industry practices and skills.

Python libraries that are hidden gems in data science

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Python libraries that are hidden gems in data science

Python has exploded in the data science community in recent years. This is because it has such a robust ecosystem of libraries and tools for data scientists to use. Python has become increasingly popular as a development and research tool in the data science community. It is one of the most popular programming languages for implementing machine learning and deep learning programs.

Python’s active community and open-source packages like Pandas, Tensorflow, and Keras have led it to become The Language for Data Science. Currently, there are over 137,000 Python libraries available to programmers all over the world.

Data science is all about finding hidden patterns in data. You can use various techniques to sift through data to find relationships and meaning. Python makes data analysis easy with its various libraries that allow you to dive deep into mathematical algorithms. Many different Python libraries and tools can be used for data science.

While these libraries can help you simplify your analysis, it is challenging to learn everything about them. Most beginners miss out on Python’s lesser-known libraries, methods, and functions that can make their lives easier and their codes more efficient. However, by exploring all of Python’s features, you can set yourself apart from other programmers.

This blog is about some of these lesser-known gems in Python data science libraries that are hidden away and really should be more popular. These hidden gems include:

Mito

The Mito Python library allows us to analyze data in seconds. Mito simplifies the data framework and does not require knowledge of all Pandas’ methods and functions. It also generates code, allowing us to see which methods and functions are used.

Missingno

One can use data visualizations to manage missing values more effectively with Missingo. There are four plots in the Missingno library for visualizing data completeness: bar plots, matrix plots, heatmaps, and dendrograms. There are advantages to each method for identifying omitted data. You can locate missing values, their extent, and whether they are correlated with one another. If analyzed closely, missing values may reveal a hidden story that is often overlooked.

Bamboolib

Data analysis and visualization are the most critical but tedious processes. In Jupyter Notebook and JupyterLab, Bamboolib provides developers with a GUI for Pandas DataFrames, allowing them to integrate Python seamlessly. A hidden gem library for analyzing, imagining, and managing information, it is a brilliant and highly supportive tool. As it doesn’t require any coding knowledge, it can be used by individuals who don’t come from a programming background.

PPScore

PPScore, developed by Bamboolib developers, is a library for predicting power in datasets. PPScore is a correlation matrix. In a particular dataset, the PPScore can identify linear and non-linear relationships among columns in an asymmetric way. In PPScore, 0 represents no predictive power, and 1 illustrates perfect predictive power. This can be used instead of the correlation (matrix).

AutoViz

Data analysis and exploratory tasks can be performed using this tool. Even large datasets can be visualized with the library, which can handle even the most complicated tasks. Data visualization can be retrieved with a single code. The library automatically helps visualize JSON, CSV, and txt files.

Pillow

Pillow library extends the Python interpreter’s image processing capabilities by providing various image formats, representations, and methods for image processing. Pillow has many capabilities, such as image transformation, rotation, resizing, statistics, etc. Designed for fast access to data stored in pixels, it supports a wide range of file formats.

Dabl

In Data Analysis Baseline Library (Dabl), the boilerplate task is reduced, and the components are automated. The Scikit-Learn library inspired it. Several features of the Dabl library make it easy to analyze, process, and model data in Python. You can automate several steps of your Data Science pipeline with Dabl. In Data Science, data preprocessing, data cleaning, and feature engineering constitute 80% of the work and can be automated with Dabl.

As the data science industry grows, these libraries will give you a competitive edge. Explore these Python hidden gems and stay on the lookout for more. Data is the new oil, and models are the new refineries in the new oil age. Using data science, one can use any data to extract meaningful information. A career in data science or analytics can be a significant step forward for your career. 

You can start with the “Certificate Program in Data Science and Machine Learning,” a 5-month course. This course is designed for beginners who wish to improve their data analytics skills in Python. Learn Python online and earn a data science certification from IIT Roorkee. 

Why your content marketing strategy is failing

Posted on by Imarticus Learning

Why your content marketing strategy is failing

Content marketing is the backbone of the marketing strategy for a business. With the necessity for every brand to establish an online presence today, content marketing has assumed a significant role. It refers to creating relevant and valuable content to target customers and establish brand identity. The content can be in different forms, such as emails, blogs, social media posts, videos, podcasts, e-books, and more.

No business today can imagine promoting brand awareness and its success without a consistent and high-quality content marketing strategy. The digital marketing strategy of a brand is nothing without good content. Content makes all the difference; evident from the data given below:

  • Businesses that include blogs get 67 percent more leads than the ones that do not
  • Forty-seven percent of customers go through 3 to 5 blogs or other content pieces of a business before engaging with a sales representative
  • Businesses with a content marketing strategy witness around 30 percent higher growth than companies not having such a strategy
  • Businesses investing in content marketing see a conversion rate six times higher than businesses that do not have a content strategy
  • Seventy-two percent of B2B marketers find content marketing helps to increase engagement and generate leads

Content is what helps a business to stand out among its competitors. Despite digital marketers realizing the importance of content marketing in the digital era, not every business is able to leverage it to the fullest. There might be flaws in a company’s content marketing strategy that lead to its failure. In case it happens, companies need to reconsider their strategy.

Here is a list of the most common reasons why content marketing does not produce the intended outcomes for businesses. Understand them to avoid or correct those mistakes.

  • No cohesive strategy

Most companies have no content plan, so they produce varied content pieces and then try to analyze what works and what doesn’t.

However, this will not serve any purpose. Brands need to have a cohesive strategy to hold content together. Before drafting a strategy, every business should know why they produce the content and what outcomes they expect.

  • No consistency

Consistency is the critical factor in the success of a content strategy. It ensures that your target audience is paying attention. So, if you post five articles one week and then nothing or very few pieces in the next two-three weeks, it will give no result.

Thus, businesses can build a content marketing calendar to schedule posts ahead of time and be consistent.

  • Not targeting the right audience

Content directed to a broad group of people or the wrong audience can waste efforts. Thus, it is essential to target a narrow demographic, understand the buyer persona, and tailor the content accordingly. Make sure that your content appeals to the right person.

  • Poor content creation

The quality of your content is a major determining factor in the success of your strategy. Unfortunately, very few companies produce relevant, engaging, and high-quality content. Mainly, low-quality writing, confusing layout, and poor research deteriorate the quality of content.

The abovementioned issues mainly arise when the company has an inexperienced content marketing team.

Content creation is a skill. Comprehensive content marketing courses are tailor-made to provide expertise to people in this domain. These courses are popular since content marketing skills are so much in demand. Every business, big or small, needs to implement a content marketing strategy to establish its online presence and survive. For that, it either requires an in-house digital marketing department or hires a digital marketing agency to do the same.

Fortunately, many organizations offer digital marketing online training to interested people of any academic background. Fresh graduates can also consider this a lucrative career option. One such great opportunity is the Post Graduate Program in Digital Marketing offered by Imarticus Learning.

The program is eligible for recent graduates with 0-2 years of experience. It is well-designed to give the candidates extensive and detailed coverage of digital marketing concepts in a more practical way. This is achieved by in-class and industry-oriented projects and case studies to give students real-life experience and develop job-relevant skills. The best thing is that it provides many placement opportunities to help students land their dream job.

To know more about the course and its curriculum, visit our website. You can even contact us through our chat support or drive to our training centers near you for specific queries. We have centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, and Ahmedabad.

A Python Certification That Will Change Your Perspective On AI

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A Python Certification That Will Change Your Perspective On AI

With the progression of Python as a machine language, it has become one of the most sought-after in organizations in terms of software development. There are millions of users, who use Python as a programming language, specifically the new-age companies like Netflix, IBM, Amazon, etc. Also, with the emerging demand for Artificial intelligence (AI) as well as Machine learning (ML) in the mainstream industry, Python has become a convenient medium to learn the algorithms related to AI and ML. This is mainly due to its ability to provide in-depth learning for developing strategies around enterprises. 

This upcoming demand for Python in terms of AI and ML has led to the creation of various comprehensive programmes to learn Python online. Today almost everyone in the commercial space is seeking to upgrade their concepts using Python apart from AI like Artificial Neural Network, Natural Language Processing (NLP), K Means Theorem, Naïve Bayes Theorem, etc. This has also led to the development of many AI courses as well as Machine learning certification courses with Python as the core programming language in these courses.

Why Should You Opt for a Python Certification? 

Python, as one of the easiest and beginner-friendly languages, has been around for about 30 years now. Its age in the field might be misconstrued as the reason for it to become potentially obsolete, but it shall be a total misunderstanding to adapt such a notion about it. If anything it can adapt the most complicated codes in the easiest way possible and that probably is the reason why it is still around and here to stay for a long time. 

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A Python certification has become almost a necessity and an ideal step towards advancing your career. This is because most of the companies involved in AI and ML today, regard it as the de-facto for ML and AI in the industry. A Python certification reflects well in terms of proficiency in your background. It also shows your strength in programming and software development as Python is arguably the most preferred language when it comes to building top-notch tools and resources in the community.

Also, one of the most essential reasons to choose a Python certification for AI and ML is that it can change your perspective about how complicated these technical skills are. Most artificial learning projects have the base of Python but because Python is one of the less-complicated commitments towards learning AI and ML, hence it proclaims to ease your way as a developer.

What does a Python Certification Offer?

A Python certification can offer a varied range of technical knowledge to its learners. Let us look at some of the important features:

  • It can help you to build applications that have their base on the algorithms of deep learning.
  • You can learn how to deeply enforce AI to build arcade games.
  • You shall be able to build highly supervised models based on machine learning algorithms.
  • Most Python certification offers to learn Artificial Intelligence to build intelligent operators like face-detectors and solve the community problems in the world.
  • It also offers learning techniques of neural networks to fathom the understanding behind object tracking and detection.
  • It also offers a practical approach to implementing realistic projects and deeply enhances your skills by providing an overview of realistic insights on AI and ML.

Apart from these essentials, a Python certification has the potential to offer a lot more descriptive learning which depends on the type of certification that you opt for. There are many python certification courses that you can opt to do online.

Who Should You Do a Python Certification Course?

The following people can take the most advantage of an online Python certification course as per the experts in the field:

  • If you’re a working professional in the field whose intention is to upgrade your careers in analytics, ML, and AI.
  • The professionals who are indulged in the Big Data or data science domain.
  • If you are a professional who is working in Management Information systems (MIS).
  • A Python certification course is also suitable for budding entrepreneurs who want to take a shot in the industry.
  • It is also suitable for you if you are a fresh graduate or even a mid-level manager in your company.

The scope of Python certification has widened with the up-gradation of the language. With time this inexpensive course can give an edge to your career and introduce a whole new world of AI and MI that you may have not witnessed before.

A python certification is important for you to be well-adaptive and relevant to times. In this fast-paced world, especially with data analytics and digitisation coming into the picture, upgrading yourself with the required skills is needed for you to step ahead in the future.

A Look Into The Future: What Will The Credit Underwriting Industry Look In 10 Years?

Posted on by Imarticus Learning

A Look Into The Future: What Will The Credit Underwriting Industry Look In 10 Years?

Credit underwriting is one of the emerging industries all around the world. Many market shifts have altered how the lending and insurance industries have delivered their service. In a pivotal scenario like this, it is only fair to gauge the potential and growth of this industry in the next decade. 

Moreover, if you are planning to have a credit risk underwriting career, then you should be aware of where you are going.

So, let’s check out

An Outlook on Credit Writing Industry in the Next 10 Years

Problems in the traditional lending system

Assessing the creditworthiness of an individual or a company is a complex job. Worst of all, it is a manual process. It is a dredging job, especially in a country like India, because the financial sector is making a gradual shift in digitizing its data. Moreover, the population is high and doing the job manually can be a strenuous one.

But how does it affect the borrower? Due to the slowness of the underwriting job, the lending system also is sluggish, so the borrowers are left stranded when they apply for a loan. The borrowers have to wait for weeks or months to get the loan approval or rejection.

Not only that, the people with poor credit scores did not have any scope for getting a loan. Those people who did not have a bank account also did not get a loan because they had no credit score. This way, the Indian lending sector was behaving quite inefficiently and needed something to put a new lease of life on it.

Fintech is bringing in a lot of changes

Thanks to the arrival of Fintech, there was an advent of technology in the Indian lending industry. But this technological surge was not noticed in India alone. Leading players in the lending sector noticed this technology trend entering the global lending space. But what changes did Fintech bring to the lending space?

When Fintech entered India, the startups were quite uneasy because they were in unfamiliar territory. Slowly, their footprints began to increase, and business began flowing in. Newer players also started entering this domain. As a result, from 2015 to 2019, there were around 1000 startups in the Fintech space with investments up to $1.94 Billion. In 2019, the lending for Fintech startups was around $320 Million.

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So, if you are looking for a credit risk underwriting career, Fintech companies should be on top of your priority list.

Generation of underwriting data became faster

With technology by its side, the Fintech companies started to generate data faster than ever. Loans were getting approved or rejected within dates. Customized credit solutions were being introduced. So many new loan applications were getting approved. Fintech is now moving at a blistering pace, faster than ever and with better customer engagement. With each step, Fintech is moving closer to automating the whole process. This will certainly change the whole lending sector, and most importantly, it will completely evolve the credit underwriting industry. Most importantly, with the cloud at play, it has displayed copious amounts of data in lending reports and the underwriting process.

The credit rating system will also change in the future. Lending will become easier and will not remain as cumbersome as it is today.

Data and technology will seamlessly converge into one

Newer data sets and modern technology will be driving an underwriting evolution. It is a possibility that it is expected that by 2030, Indian insurance companies will use AI in one form or other. It was also published in Deloitte’s 2022 insurance outlook. Many respondents who undertook the survey were sure that some alternative data would be available because of AI automation. Also, OCR (optical character recognition) will help in the digitization of manual records. It will make the underwriting process survive longer and stay as resilient in the future years. 

So, as a professional working in this sector and the aspirants can now take up a credit risk underwriting course and get a better understanding of how technology is changing this sector.

AI and Big Data will be powering real-time underwriting

With the introduction of AI and Big Data into underwriting, credit analysis and the generation of a credit score will become a lot easier than it is right now. Using AI, the whole system of creditworthiness will be automated. The computation of the market credibility of an entity will be extremely accurate and show the credit applicant’s true picture. This will help to sort out bad payers with good credit scores from good payers with thin credit scores. AI will easily distinguish a good risk from a bad risk. This creates opportunities for those applicants who were unable to secure a loan before.

Conclusion

To sum up, a credit risk underwriting career is a lucrative option, considering the number of new-age financial institutions entering the market. The scope here is now substantial.

So, to take up a credit risk underwriting online training from leading institutions like Imarticus Learning. The Credit Risk Underwriting Course will help you to grab your opportunity to become a professional in this field.

How to become a CFO in a year with IIM Indore

Posted on by Imarticus Learning

How to become a CFO in a year with IIM Indore

Financial modelling is a method to prepare a summary of the incomes and expenses of a company. Prepared in spreadsheets, these models help business owners to predict the financial future of their company.

Financial modelling is an exercise needed for corporate finance or asset pricing. With it, the fluctuations of the financial agents or markets get converted into numerical predictions. Generally, this prediction depends on future assumptions and the company’s historical performance. 

It requires preparing schedules (namely 3 statement models), cash flow statements, balance sheets, and income statements. From here, one can create more advanced models such as consolidation, IPO, Leveraged Buyout, Discounted Cash Flow (DCF), and merger models.

Uses of a Financial Model 

With the definition of financial modelling out of the way, it is essential to understand its usage. The utilization of such a system is widespread; executives use financial models inside a company to take decisions related to:

  • Management Accounting
  • Ratio analysis/ financial statement analysis 
  • Valuing a business 
  • Capital allocation (to determine the most effective investment strategy) 
  • Forecasting and budgeting for the upcoming years 
  • Divesting or selling business units or assets 
  • Expanding the business organically, such as entering new markets and opening new stores 
  • Making acquisitions (assets and/or businesses)
  • Raising capital (equity and/or debt) 
  • Projecting raw material requirements
  • Building a roadmap to business profitability 
  • Identification of undervalued securities 
  • Evaluation of portfolio performance 

Advantages of Financial Modelling 

Here are the various benefits of a financial model:

Helps a business to grow

A financial model highlights the areas that have the potential to generate higher profits. It also enables cost-benefit analysis for new projects. As such, executives can find out which projects or areas can bring growth and better profitability. 

Offers accurate budgets 

It designs financial forecasts and budgets by business data. With these forecasts and budgets, business activities remain within the prescribed structure. Moreover, it helps a company to allocate its financial resources in a more structured, well-planned way.

Generates prompt outputs

Often, a business takes time to determine the effect of a particular decision or to get the answer to a specific financial question. However, financial models deliver prompt results, which, in turn, facilitate quick decision-making.  

Ensures variance analysis 

A financial model helps to conduct variance analysis by correlating the actual outcomes of a company against its budget. Executives can carry on the performance review periodically to get feedback on the company’s operations. Certain advanced models allow companies to adjust their operations and improve overall profits. 

Prepares for uncertain situations 

It makes executives understand how a company operates and which factors can impact its business. They can evaluate the expected changes in a situation when there are fluctuations in the external and internal environment of a company. 

Decides the fund strategy 

It effectively predicts the expected cash outflows and inflows. Further, it helps to understand what will be the position of cash flow after meeting the loan repayments and interest expenses. With this, a business can determine whether to take a debt or how much debt they can take.

How to Enter the Field of Financial Modelling?

One can efficiently manage business finances and reduce financial risks through a recognized chartered financial analyst course in India. Go for the Certified Investment Banking Operations Professional course of Euronext to build your skills. 

Some platforms/institutes facilitate financial modelling certifications once a student has passed class 12th, while some others offer the same after a student has passed class 10th. There are no particular eligibility criteria to register for these courses. 

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However, candidates must have a preliminary knowledge of finance as well as the necessary skill set to pursue such courses. Students having an MBA or CA degree or CFA candidates may find the syllabus and curriculum more relevant.

Additionally, if you wish to become a successful financial analyst, opt for the job-ready financial analysis course of Imarticus in collaboration with KPMG.

Final Words

The demand for financial analysts has increased significantly over the years, and a well-trained professional can fetch a good salary package from any company. So, if you are interested in this area of operations, hopefully, this blog will help you to understand the fundamentals of this segment and operate accordingly.

5 social media marketing essentials to consider before you enrol for a social media marketing training

Posted on by Imarticus Learning

5 social media marketing essentials to consider before you enrol for a social media marketing training

Have you ever wondered why you see so many captivating brand advertising campaigns on various social media platforms like Facebook, Instagram, YouTube, or Pinterest? Why do people log in constantly to their Twitter and LinkedIn accounts? 

The answers to both the questions are the same – they all are doing social media marketing of their products, services, and skills by creating engaging posts for their prospective customers and clients. 

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Social media or digital marketing is the buzzword of this century that is helping businesses drive extensive market reach and attain profitable growth. Social media marketing is evolving as a high-demand career. These training courses are now selling like hotcakes in the EdTech industry. However, it is critical to have a deep understanding of the basics of social media marketing before picking the course of your choice.

So, if you are planning to pursue social media marketing training, read this article as it throws light on the five social media marketing essentials to consider before enrolling. These insights will help you make the prudent decision on the course to pursue to become a successful social media or digital marketer.

Five Social Media Marketing Essentials 

  1. Creating unique and engaging social media content is the key to reaching the target audience.

Social media marketing content addresses the customer’s pain points and solves their problems. It makes them feel connected to the product, service, or skill. The type and frequency of posting the content have an influential impact on the reach and responses. It increases brand loyalty, drives engagement, and boosts sales.

  • Social media marketing strategy differs for different social media platforms.

The same-size-fits-all hypothesis does not work in the social media world. You must know the tactics for creating and promoting thought-provoking marketing models using digital technologies. The social media marketing strategies must be in line with the needs and interests of the target audience across different platforms. 

 

  • Social media platforms are for building and fostering relationships with customers.

 

The target audience performs a pivotal role in social media marketing. With so many brands, messages, and users landing on social media platforms daily, you can stand out from the crowd only when you build one-to-one relationships with your target audience. You must know the strategies to engage with your followers and win their trust and loyalty for long-term association. 

 

  • Social media advertising is the doorway to extending your market reach.

 

Besides using compelling content to expand your market reach, you must be aware of the social media advertising tools. You need to ensure your message reaches the target audience and makes an impact to spark desired actions. Influencer and affiliate marketing are the two effective social media advertising techniques. 

 

  • Measuring the Return on Investment (ROI) of your social media marketing strategies is essential. 

 

Lastly, you must acquire the knowledge to compute the monetary and non-monetary results of your social media marketing pursuits. It includes calculating financial profits and benefits accrued due to increasing customer retention, brand loyalty, and awareness. Social media analytics reports provide data and metrics on traffic and engagements. It hence forms the basis of ROI measurement.

Consider the above points before enrolling in social media marketing training.

A Prodigious Course For Aspiring Social Media Marketers

Imarticus Learning, a technology-driven educational institute, offers a Post Graduate Program in Digital Marketing. The course provides all-inclusive, tech-enabled learning of digital marketing concepts. It aims to impart teaching on social media marketing concepts alongside other digital marketing tools such as content, SEO, paid media, e-mail, and e-commerce.

Imarticus provides five Google and one HubSpot Digital Marketing Certification through this course. You are eligible to apply if you are a graduate with 0-2 years of digital marketing experience.

So, enrol today if you aspire to broaden your skill set and leverage the influence of social media to excel in your career and business. The conceptual base and real-world case studies provide you with the secret sauces to gain a competitive edge using digital marketing techniques.

 Any Questions?

Contact us through our chat support or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad. 

Happy Learning!

The transformational power of efficient supply chain management

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The transformational power of efficient supply chain management

Supply chain management (SCM) is managing an organization’s supply chain to enable it to fulfill its mission, satisfy its customers and achieve its objectives. This blog post will discuss how efficient supply chain management can help grow your business over time.

The transformational power of efficient supply chain management

Supply chain management has been around since companies were managing their manufacturing operations, and it was often part of the “production department” or “manufacturing division” within a company. 

In today’s competitive environment, however, supply chain management has become much more complex than simply keeping track of raw materials and parts to make products for customers. It now involves managing everything from purchasing goods and services through distribution channels to customer service after the sale.

Logistics must be considered alongside SCM when looking at how best to manage your business’ overall logistics needs; these two elements work hand-in-hand with one another, so they don’t compete against each other but rather complement each other when creating successful outcomes across all areas involved in running an effective operation.

A supply chain manager must be able to forecast what will happen with your product or service over time—and then make decisions based on those forecasts. If you’re not doing this well enough yet, then there’s no way you’ll be able to succeed in today’s competitive market environment!

The difference between logistics and supply chain management

Supply chain management is a broader concept than logistics. The former refers to the entire supply chain, whereas the latter is just one element of that chain. Supply chains are complex, multi-layered systems that require coordination across all stakeholders to function effectively. 

 

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This includes everything from upstream suppliers and manufacturers who provide raw materials or components for products you buy to retailers who sell those products directly. On top of this mixture of entities are third parties like freight forwarders, customs agents, and shippers who handle transportation logistics—the movement of goods between origin and destination.

Supply chain management is a key differentiator in today’s competitive environment.

While many other industries have struggled to keep up with the pace of change, supply chain management has remained an essential element of success for businesses across all sectors.

Supply chain management has become more complex over time as technology and globalization have facilitated the flow of goods worldwide. As such, companies must understand how they can partner with their suppliers to achieve maximum efficiency while reducing costs by minimizing waste and improving customer service through efficient operations at every step along the way.

The SCM process must be coordinated across all departments in an organization so that everyone knows what needs to get done and when. 

Explore a Career in Logistic Management with Imarticus Learning

The best supply chain management certification course will help managers make strategic, operational, and tactical decisions. Prepare to contribute to the development of more tactical and inventive global supply chains in the future by combining traditional supply chain online courses with data-driven decision-making.

 Course Benefits For Learners:

  • Students are exposed to essential technologies, including six real-world projects, to thoroughly understand the industry and prepare them for a successful career.
  • Completing a supply chain management online training allows students to prepare for highly sought-after jobs such as demand planners or data scientists!
  • Python will teach students how to be data-centric and improve supply chain decision-making.

Contact us through chat support, or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

Financial goal setting: Dos and Donts

Posted on by Imarticus Learning

Financial goal setting: Dos and Donts

If you have ever tried to set a financial goal, you have probably found that it’s easier said than done. You may feel overwhelmed by your finances or tired of them. This post will help you create SMART goals that are realistic and achievable but also specific enough so that they can get measured easily over time. 

Do make sure your goals are achievable

  • Make sure your goals are realistic.
  • Make sure they are specific and measurable.
  • Make sure they are relevant to you and your life, not just the world.
  • Make sure they are time-bound by setting a deadline to complete each step in achieving them (e.g., within one year).
  • Balance your values with financial goals, so you don’t sacrifice one for the other—it should be possible to achieve both!

Do make them specific

One of the best ways to set a goal is to be specific about what you want to achieve. Your goals must measure your progress and know how well you are doing.

Do make sure they are measurable

  • Measurable goals are clear, precise, and specific. They can be tracked and measured by the person or team with the plan, so they know whether or not they have succeeded in reaching their target.
  • Measurable goals also have a time frame.
  • The main thing is that your goal should be achievable by yourself (or anyone else with whom you work together). 

Don’t let them be too rigid

Your financial plan should always be flexible enough to adjust as circumstances change and new opportunities arise. If your goal is not flexible enough, then it will be difficult for you to reach it because there may be times when things look bleak, but they’ll still get better later on. 

Don’t just write down your goal. It is essential to reflect on them regularly

Reflecting on your goals regularly will help you stay motivated and ensure you are on track with them. If you don’t measure your progress, it can be challenging to know if you are making any headway or if something else needs to get done for the goal to reach.

It’s also essential for people who have set their sights on a particular goal but don’t know how they’re going to achieve it.

Don’t use too many metrics

When setting goals, you want to choose just a few metrics that are relevant to your life. They must be measurable, time-bound, specific, and realistic. You can’t expect to achieve all of them at once or within the next year—and even if you do, there’s no guarantee that they will result in a positive outcome.

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