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Author: Imarticus Learning

How Companies Apply Agile Methodologies and Practices in Business?

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Agile methodologies and practices have transcended the software development industry to impact almost all business sectors. The idea is to become an agile organization that’s quick in responding to marketplace and environmental changes.

Agile creates innovative, multidisciplinary, and cross-functional teams which encourage growth, boost self-organization, increase employee engagement, and break organizational barriers to nurture communication and collaboration.

While strategy analysis helps business analysts to identify and meet the strategic and vital needs of the organization, Agile methodologies and practices facilitate quick response to changes. Thus, both strategy analysis and Agile practices go hand in hand to help companies flourish.

Applying Agile Behaviour and Practices

The individuals making up the business team adapting to new mindsets and behaviors is the key to implement Agile practices. In addition, companies must advocate a supportive environment that allows individuals to respond better to change and increase business value.

Scheduling Daily 15-minute Stand-Ups

A great alternative to lengthy staff meetings, organizing 10-15 minute stand-ups daily helps in staying up-to-date with the team’s tasks and efforts. In addition, it encourages an atmosphere of transparency and accountability where team members answer three questions:

  • What have I done since the last stand-up?
  • What will I do today?
  • What challenges do I face?

Breaking Down Projects Into Iterations

Project management has become a critical aspect of most businesses. But in reality, most companies run into a crisis when the project becomes too large and complex to handle. The Agile methodology stresses breaking down the project into achievable chunks for better project management. Known as “iterations” or “sprints” in software development, dividing the work into measurable pieces helps estimate the project duration and reduces the employees’ stress.

Creating a Transparent Backlog of Prioritised Tasks

In Scrum, a product backlog is an orderly list of all that is needed for a product’s improvement. It’s part of the product development process where new elements can be added and reprioritized. Maintaining a transparent backlog gives an overview of the team’s work division and helps monitor both the short and long-term progress.

Partnering with End-Users for Continuous Feedback

Waiting until the end of a process to show your work to clients results in a significant waste of time and resources. What if the client is not satisfied with your work? You would have to go back and start from scratch, which is no less than a nightmare for the team. However, Agile methodology emphasizes constant feedback on the go. Hence, you can rectify mistakes at early stages, save time, and ensure that the project is heading in the right direction.

Tasks and Duties of an Agile Business Analyst

Agile business analyst coursRegardless of the business analyst certification, an Agile business analyst course must be prepared to fulfill the following responsibilities:

  • Focusing on understanding business problems
  • Ensuring that requirements align with current business needs
  • Being an expert in the business domain to be able to answer questions from the development team
  • Delivering products frequently and within the shortest timescale possible

How To Look for Business Analytics Courses in India?

If you’re looking for business analytics courses in India, there are quite a few courses available online. Among these, Imarticus offers a Post Graduate Program for Agile Business Analysts. It’s a comprehensive 6-month business analyst certification program to help individuals prepare for the responsibilities of being an Agile Business Analyst. The course is packed with hands-on training and multiple case studies to prepare professionals who can confidently face the competitive business world.

Cryptocurrency Mining: What It Is and How Blockchain is Changing Finance?

Posted on by Imarticus Learning

The world of Cryptocurrency is changing the way we do financial transactions. Cryptocurrencies are a digital currency that relies on cryptography to secure and verify transactions on its network.

Blockchain technology underpins the current Cryptocurrency boom by providing an open-source, distributed ledger system that can be programmed to record virtually anything with transaction data or information about ownership – not just Cryptocurrencies.

Let’s dive into some details!

What is Crypto-mining?

Cryptocurrency mining is a process comprising of adding transaction records to Cryptocurrency’s public ledger of past transactions. Cryptocurrency mining serves as a record-keeping service for Cryptocurrencies, which are used to keep track of who owns what and prevents fraud.

Mining makes it difficult for third parties to make counterfeit Cryptocurrencies because anyone can check the validity of digital currency with its distributed consensus system. Blockchain technology provides the backbone for Cryptos by enabling an open-source, decentralized ledger that does not use a central administrator or intermediary; this means that all data on the blockchain is publicly visible and encrypted, ensuring transparency and security in cryptocurrency transactions from start to finish.

How Crypto Mining Works?

Cryptocurrency Mining involves processes of solving complex mathematical problems to generate more Bitcoins. Cryptocurrencies are digital currencies that exist only as computer code and have no physical form, such as gold or paper money. Cryptocurrency mining generates cryptocurrency coins by running complicated calculations on computers.

Cryptocurrency mining can be done with home hardware and requires minimal technical knowledge. Miners create cryptocurrencies until they reach their maximum number of coins generated over time. A limit is set at the beginning of the generation process to have unlimited cryptocurrencies available to mine!

Mining for cryptocurrency has proven extremely difficult because it takes a lot of time, effort, electricity, and expensive equipment to mine cryptocurrency.

Reasons to Rely on Blockchain Technology

Blockchain technology provides an alternative solution for transferring money or valuables without going through a third party such as PayPal or Visa Inc., which can charge high fees to users who send payments across borders.

Blockchain training allows everyone involved in the transaction to see all of its details. Still, it does not show any personal information about either sender or receiver using blockchain-based transactions. This makes this type of transfer very safe and reliable!

How blockchain is transforming the Fintech Industry

The power of blockchain technology has resolved millions of challenges faced by the Fintech industry. A conjuncture of fintech & blockchain has helped to remove Intermediaries, data integrity, cut-off costs, created assets, and leveraged distribution. Blockchain has helped behold data privacy and authentication in a better way.

Everyday use of blockchain has been seen through the Australian Securities Exchange, which recently executed a specific project and transferred its post-trade clearance and settlement through blockchain technology.

Grow with Fintech Courses from Imarticus Learning

The crypto & blockchain craze may make some aspire for a career in fintech. This calls for learning through a Fintech course or cryptocurrency course. Imarticus Learning offers courses ranging from blockchain and crowdfunding to peer-to-peer lending and Robo-wealth-managers.

To be professional, well-versed in fintech, you need to look for fintech courses online that enhance your knowledge of Blockchain. MBA in Fintech can boost your knowledge of blockchain & cryptocurrencies.

At Imarticus Learning, online education is framed for in-depth learning about Trade Finance, Blockchain, and cryptocurrency. Designed by industry experts, the programs give the best insights into business, communication, domain expertise, and management skills.

Reach out now through the Live Chat Support system or seek virtual assistance for course details!

The Difference Between The Sell Side & The Buy Side in Investment Banking

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It is a known fact that, if you are a finance enthusiast or even interested in the industry of Investment Banking, it is essential to know two primary sides in this field. These two are known as the buy side and the sell side and for anyone who is contemplating a career in Investment Banking, it becomes important to know the difference between the two. Studies state that these two sides, make up for both the halves of the Financial Markets.

In spite of this, there are a number of professionals who find it very difficult to grasp, the exact meanings of these two concepts. Let’s try and dissect them for our convenience. The sell side is basically associated with all of those entities and processes, that facilitate the decision making of those entities, which are involved in the buy side. While on the other hand, the buy side is basically associated with all of those entities, that are primarily involved in making the investments.

When it comes to the various institutions and firms, that work on the sell side of Investment Banking, these include firms that involve Investment Banking, Commercial Banking, Stock Brokers, Market Makers and other Corporate Finance firms.

On the other hand, the buy side is inclusive of Asset Managers, Hedge Funds, Institutional Investors, Retail Investors and so on. The professionals or analysts, who work on the sell side, are usually higher in number than those involved in the buy side, mainly because of the fact, that their work is dedicated to analyzing specific sectors and companies.

The companies, that are involved in sell side are in charge of keeping track of the Stocks, the performance of various companies, as well as projecting the future financial transactions. These companies basically belong to the field of Equity Research and are responsible for ‘selling’ of ideas,  and their work involves analyzing a number of quarterly results of all the financial reports of a particular firm.

The buy side includes a number of firms, which are involved in deploying their capital, it essentially is a pool of funds, whose primary use is for investing. We can thus infer, that these firms on the sell side are basically involved in providing services to all those firms that are involved in taking investment decisions.

Moving on to the jobs of the professionals, working on these two different but equally important sides, we can conclude that the goal of a sell side is to basically advise on research and close the deal; while on the other hand, the ultimate goal of the buy side is to generate investment returns for their various clients.

An analyst, working on the sell side, has to generate independent reports, on the basis of their own research, while an analyst working on the buy side use these very reports, in order to conduct their recommendations on the kind of investment decisions that their client must take. These fields provide a lot of lucrative opportunities, provided a candidate has specialization certificates, from industry-endorsed training institutes like Imarticus Learning.

Liked this blog? Read similar blogs here:
Evolution of Investment Banking
Why A Career In Investment Banking Would Be The Best Decision For You?
Investment Banking Soon to be Taken Over by Artificial Intelligence

What is the Technical Data Analyst Skillset for The Digital Enterprise?

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As data science is regarded as the “new oil” for the technology industry, there is a surge in the demand for skilled professionals. Data Analytics is finding its application in nearly all aspects of life, from education to healthcare, social media, e-commerce, and fintech, to mention some. As a professional, data scientist plays a pivotal role in the business ecosystem and influence business decisions.

data analytics coursesAnalytics, in general, has three important components – business context, technological intentions, and data science.

Data science is a broad term that encompasses different expertise like research – both operations research and statistical research, machine learning algorithms, and deep learning.

No matter which aspect of data science are you planning to focus on, you need to understand the key skills that make up a good data analyst. Read on to learn about the skills you need to excel in a data analyst career.

MS Excel

One of the most widely used app for data visualization as well as financial, statistical, and mathematical calculations, excel is the basic tool one needs to master while looking for a career in data science. The pivot tables are one of the most popular tools used in data analytics. Charts are excellent tools for data visualization. Slicers and filters allow organizing data while the formula-based techniques are great for creating aggregate reports, while other features like Vlookup help process a large number of data bits into a well-organized structure, enabling easy comprehension.

Data Warehousing

In simple words, data warehousing involves the collection of data, organizing them, and storing them. Data analysts and projects managers are usually responsible for data warehousing, where they handle the safekeeping of the data, ensure that the privacy rules are strictly adhered to, and monitor them. Data analysts should be able to integrate the data collected from different sources, analyze and create analytical reports, and support decision-making.

Data Retrieval Skills – SQL

The Structured Query Language (SQL) is used to connect with the database. Whether updating a database or retrieving data from it, SQL is the standard language used by Relational Database Management Systems (RDMS).  SQL skills are mandatory if you wish to have a career in Big Data. However, learning SQL is simple, even non-technical people can learn it. It has become a basic skill used in many organizations to create, maintain and modify database structures and storing the collected data.

Coding and Programming Skills

Data analysts should master coding and programming to practice their knowledge. You don’t need to be a hard-core programmer, but you need to know the basics and should be comfortable with coding and programming to excel in this role.

While the primary responsibility of a data analyst is to analyze the data and derive meaningful insights from the, understanding the concepts such as functions, loops, if-else, and programming logic would be an advantage while dealing with a large amount of data.

Artificial Intelligence (AI) and Machine Learning

AI and machine learning help enhance data analytics. When you prepare a machine learning algorithm and provide it with a model, it gives you an output based on the model provided. For instance, if you train a machine learning algorithm and provide it with a predictive model, it will provide you with predictive analysis based on the data feed.

There is no absolute definition of skills needed to excel as a data analyst. Most data analyst courses cover the basic skills needed to secure a data analyst job. There is a buzz about big data and its application. Almost all industries are espousing data analytics. As technology improves, there could be overlaps in the job role, or the job roles could encompass wider aspects of data science. The better skilled you are the more are the chances to excel in a data analytic job.

Choosing between SAS, R, and Python for Big Data Solution

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SAS, R or Python, from where do would it be advisable to begin? This is the most widely recognised inquiry that each competitor confronts while entering the universe of Data Analytics. As the examination field keeps on developing, new devices and advancements have begun rising in the market, making the business experts ace them for better profession alternatives.

Today, extraordinary systematic devices are accessible in the market, yet the significant rivalry is seen between R, Python, and SAS. As in all situations where there are decisions and competition, a near noteworthy investigation is made between these three stages to locate the best fit.

Let us initially comprehend what R, Python, and SAS are?
R – It is the most widely used language of statistics. It is a language that depends on a progression of following subroutines. Due to its cost-effective approach, R is the profoundly favoured programming language among numerous information researchers. R is the best alternative accessible for information and plot visualisation that are important with regards to data analysis. It gains by its open source nature by making available the most recent methods quick.

Python – It is a multi-purpose programming language. It has increased monstrous prominence as a result of its information mining libraries and capacities that can be generally used to play out any statistical operations. Python is another open source scripting language that has developed to envelop.

SAS – Statistical Analysis System (SAS) is a superior programming suite introduced to investigate substantial datasets in a well-organised format that looks good. Today, numerous worldwide organisations and million dollar organisations generally incline toward this product. It offers the clients a decent GUI, a variety of measurable capacities, alongside an undeniable specialised help. Nonetheless, it is a much costly alternative accessible in the market when compared with R and Python. Also, it is not an open source.

To know which tool suits best according to your necessities, let us examine a portion of the critical traits for the devices.

  1. While discussing the cost of utilisation, SAS is a costly business programming accessible in the market. While R and Python are the open source devices that can be accessed for no cost. This is the thing that makes R and Python broadly mainstream among numerous new companies and settled organisations working in the field of data analysis.
  2. As the Internet use has developed twofold with time, more information is produced each day making it hard to store and manage it adequately. However, SAS accompanies a decent easy to understand GUI; it misses the mark regarding the capacities required for taking care of and dealing with the data. The bundles like Plyr, DPlyr, and so on and expansions like NumPy, Panda, and so forth. It gives Python a smoother approach for information stockpiling and control. While, R works just on RAM, which makes it hard to run even a little undertaking.
  3. SAS is a costly programming, for the most part, utilised crosswise over enormous MNCs which constrains the career opportunities to a particular level. While R and Python are profoundly favourite crosswise over new businesses, entrenched organisations, and MNCs, which exhibits an incredible breadth of better career openings at overall industry levels. In this manner, conveying R and Python confirmation qualifications on your resume will unquestionably copy the likelihood of getting procured.

Conclusion

  • In case you are a fresher and great at science and mathematics, at that point R is the best alternative, to begin with. Be that as it may, on the off chance that you are great at programming and coding, at that point Python is the best choice to begin.
  • In case you are an expert with a few years industry encounter, at that point upgradation is connected on either R Python coordination or SAS Python coordination.

What is Equity in Investment Banking?

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A career in finance may take many paths, including investment banking and equity research. But, you need to choose the best banking courses after graduation that can prepare you for various branches of business and finance. If you want to know about equity in investment banking, then you must first understand how investment banking works and why equity is important. So, let us begin by learning what is investment banking in simple terms.

What is Investment Banking?

Investment banking is a division of any bank or financial institution that serves any organization, corporation, or even the government. Investment banking provides these institutions or corporations with underwriting for raising capital or mergers and acquisitions, as well as other advisory services. The job of investment banks is to act as an intermediary between the investors and the corporations that are in need of capital to grow their business.

Investment Banking course with placement in IndiaTo understand investment banking better, you can choose any of the multiple investment banking courses in India available online. These investment banking courses will help you understand the technicalities of investment banking better.

You can check out the certificate in Investment banking course details to see if it is one of the best banking courses after graduation you can go for.

When paying the investment banking course fees, one should look for a program that gives an in-depth knowledge of the topic at hand so that the investment is not regretted later. Out of the many investment banking courses in India, only a few cover equity in investment banking. You can check out one such certificate in investment banking course details here.

What is Equity in Investment Banking?

In finance and banking, equity is more commonly referred to as the shareholders’ equity. For privately held companies, it may also be called owner’s equity. Equity is the value that is attributable to the owners of the business. It is the value or amount of money that the shareholders of the company would be returned in case the assets of the company are liquidated and all of the debt of the company is paid off in liquidation.

In the case of acquisition, equity is the total value of the company’s sales minus any of the liabilities which is not transferred during the sale. Shareholder equity represents the book value of the company. It is one of the most important pieces of data used by analysts to assess the financial health of the company.

There are two types of equity values:

Book value – It is calculated by taking out the difference between assets and liabilities on the balance sheet of the company.

 Market value – It is determined by the current share price or estimated value of shares calculated by professionals.

When choosing what course to do for investment banking, one should zero in on a program that also teaches about shareholders’ equity in investment banking. This will not only give you a deep understanding of how investment banking works but also how equity operates along with investment banking and the difference between the two.

You should choose the program of the many investment banking courses that prepares you for the journey ahead in this industry and makes your Investment Banking career trajectory go higher.

Related article:

How To Become Equity Research Analyst

What is Marketing Management?

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Marketing Management is a crucial process in charge of an organization’s marketing strategies. This process is responsible for coming up with marketing plans and ensuring that it is executed as accurately as possible. Marketing Management takes a holistic approach towards marketing in order to send a company’s message across to the potential consumers.

Marketing Management is also responsible for analyzing the financial market, competition, competition’s marketing strategies, and utilizing this information effectively to assist marketing models. Individuals from this field are also tasked with understanding the market, surveying potential customers, and researching demand on behalf of the company in order to build the best marketing tactics for resonating with your target consumers.

Marketing Management course Fundamentally, the Marketing Management course can be easily defined as the framework looking over the conceptualizing, designing, and execution of marketing strategies alongside marketing activities.

What are marketing managers?

Marketing managers provide firms or companies with plans to market their product or service in the best way possible, within the given budget. They are also tasked with ensuring that all the marketing plans are enacted successfully and the marketing activities are completed as desired.

Marketing managers are professionals who have finished a Marketing-centric MBA, online MBA course, or online distance MBA. It is preferable that Marketing managers have experience in Financial Markets as well as the fundamental knowledge of Business Environment Management and Business Strategy Management so that they can understand the business, the customers, the economic condition of the area, and the market itself.

What is marketing management concerned with?

According to the father of modern marketing, Philip Kotler, “Marketing Management is the art and science of choosing target markets and building a profitable relationship with them.” and it is exactly so. Marketing Management is concerned with choosing the right markets and target audiences as well as acquiring potential customers even before the product or service has been launched.

This is done by building a relationship with the customers and creating superior value, thus increasing the goodwill for the company or brand as well. The job or marketing interaction with customers is never truly over as Marketing Management must also ensure the customers keep growing and promotions or advertisements are altered in accordance with the market, trend, and economy. Marketing Management exists to promote business development, communication and sales.

Marketing Management considers many crucial factors obtained from Operation Management, Business Environment Management, Business Strategy Management, and implements strategies accordingly to suit the businesses.

This is why it is advised that those who are inspired to join this field should only choose the best online MBA courses or reputed online distance MBA courses.

Marketing Management courseThe best online MBA courses teach all required skills to provide superior marketing strategies and execute them for companies. Let us look at the different aspects that Marketing Management is concerned with other than creating superior marketing strategies.

  • Packaging, the actualization of ideas in accordance with trends, and sometimes even playing a role in the design of the product.
  • Promotion, advertising campaigns, marketing activities, sponsorships, and building affiliations.
  • Contributes with business strategies as well such as pricing the product, distribution, geographical targeting, etc.
  • Operation Management of marketing operations and massive processes (through call centers or internal marketing teams).
  • Realizing business goals by relying on the power of superior marketing.
  • Continuous and fluid conduction of marketing research, studying the competition and gathering customer responses.
  • Understanding the resources and budget, and accordingly planning the marketing model.

Conclusion

Marketing Management is a valuable requirement of any organization which is non-local in nature and wishes to expand. Marketing allows businesses to grow radically and it is the job of marketing managers to ensure that they do.

This is a desirable field with great benefits, however, companies always prefer individuals who have finished a PG program, such as the one from Imarticus Learning, an MBA, or an online MBA course. This is why it is recommended that individuals who wish to pursue this sector can join one of the best online MBA courses out there, and become adept at helping companies reach their goals.

How Is Ethical AI Different From Fair AI?

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Artificial Intelligence is turning out to be an integral part of every part of businesses and human lives at a surprisingly faster pace. As much as it is transforming lives and processing easier, it comes with its share of drawbacks.

The topic here is the ethical and fair side of AI that has already proven to be a problem even for the big giants like Amazon and Apple. So the question here is how to rectify the problem without compromising the usefulness of AI.

In order to solve the issue, it is important to understand the difference between ethical AI and fair AI. Although they are not much different from each other, knowing the thin thread that separates them is crucial.

The dilemma of ethical AI

While AI  algorithms help replace several tasks which usually the human mind accomplishes, there are several pressing issues regarding the ethical outcomes it causes. Both  AI and Machine learning requires data that is fed manually, there is still no definite criteria on what qualifies as non-biased that leads to an ethical result.

If the algorithm leads to an unwanted advantage for anyone while someone else ends up on the receiving end it is considered unethical. The problem is defining what are ethical terms and what constitutes unethical. To solve this issue, leading brands have slowed down their progress with regard to the AI development in their business end.

An ethical AI will be the one that can accomplish ethical prediction and quality outcomes without impacting humans in one way or the other.

When is it a fair AI?

When it comes to fairness in AI predictions and outcomes, it is all about perceptions. A fair decision to one might appear unfair to another. So it is not easy to judge the AI program as unfair or fair.

While there are several issues with the unfair outcome of AI programs, what it really needs is a smarter and sensible approach.

  • It needs cooperation between humans and the AI system to evaluate and judge fairness. The employees need to be more intuitive and apply more common sense to do the job well.
  • As humane as AI seems to be it needs a bit more humanity than already has. Here, it is the company’s choices and values that can be used to determine the fairness in the AI system under development or use.
  • While creating the algorithms even the smallest factor and the most unimportant aspect should also be considered to create a more effective filter. This approach prevents a wider range of unethical and unfair decisions by the AI system.

The future of ethical AI

Owing to the past mistakes in the field of AI, many of the Artificial Intelligence training courses are trying to include a moral side in their curriculum. Since most of the unfair decisions by the machine is due to the social and economical perception by the humans, it needs correction right from the root level.

difference between ethical AI and fair AIIn order to pursue an Artificial Intelligence career, one must start thinking ethically and be able to decide between what is fair and unfair for the right matters. This is where critical thinking comes in handy.

Though it is difficult to create a Fair AI, it is easier with Ethical AI as long as it does not cause a clear bias with many factors in consideration.

Conclusion

What it shows is that machines can only impersonate humans and they are yet to reach that feat emotionally and for logical thinking capability. For them to reach that point, humans must change their views, perceptions, and work ethics.

What is Big Data Analytics?

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Big data can always be related to massive volumes of data generated directly by the company or acquired from various sources. However, in order to truly utilize the data to its full potential, companies are always in dire need of skilled data analysts or business analysts. Big Data Analytics allows companies to use this data to their advantage by gaining valuable insights from this data, thus making more effective data-backed decisions.

Data Analytics Certification Courses with placement in IndiaThe Big Data Analytics course positively affects sales, decreases risks, optimizes production, helps understand customer behavior, and even allows companies to come up with more efficient marketing strategies.

This is all possible due to Big Data, Data Science, and analytics. Budding analysts are always advised to join well-orchestrated Data Science courses in order to acquire the skills required to effectively analyze the data.

The true intention of Big Data Analytics is always to promote more efficient use of resources and getting better results through data-centric suggestions from business analysts. It is highly recommended to opt for reputed business analytics courses in order to productively contribute to this field. Constructing data-based predictions is the key to making businesses run adequately.

Why is Big Data Analytics Important?

Fundamentally, Big Data Analytics allows companies to discover patterns, trends, and correlations from massive amounts of data. This allows companies to use the newly acquired information to their benefit, thus making more effective business decisions, increasing profits, and satisfying customers better.

From helping in marketing campaigns to improving production capabilities, Big Data Analytics can help with any sector that generates data. Analytics help companies make customers happier through understanding customer behavior and trends better.

Fintech courseData scientists and analysts help companies massively cut down operational costs by resources much more effectively. Decades back, even though “Big Data” did not exist, business analytics did. However, it was not a cost-effective process and demanded a lot of time.

Big Data Analytics online training allows data scientists and analysts to make this process much faster. With the advent of AI in analytics, Big Data Analytics can almost provide real-time insights from incoming data.

What is Data Science?

The value Data Science brings to business analytics is immense. It is responsible for everything in the process. Starting from sourcing the data and modeling it to the time that the required insights are acquired, Data Science powers it all. Data Science allows companies to effectively source transactional or raw data from various sources and then process it. This is where analysts come into play, they analyze this data and then help companies visualize the data.

What are the requirements to become a Data analyst?

How to become a data analyst? It might sound complex but it is truly not that hard. There are many good Data Science courses or business analytics courses available online and offline that one can choose from. However, care must be taken when choosing a Data Science course in India or outside, ensuring that you get the best out of your time and energy. Any good Data Science course in India will cover the fundamental skills required to become a data analyst and prepare students to effectively use analytics tools when working with Big Data or data in general.

 

Conclusion

Big Data makes it possible for organizations to store and harness the capabilities of massive amounts of both structured and unstructured data. Even though what Data scientists do is similar, Big Data Analytics requires exceptional skills when working with large volumes of data. A good Data Science course in India is highly recommended such as this PG program in order to gather the required skills to work with Big Data and Analytics.

Related Article:

What is the difference between data science and data analytics?

How Artificial Intelligence Training Helps to Boost The Fashion and Advertising Agencies?

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In a fast progressing world such as ours, the need for an efficient tool to speed up the process of our work has increased. With that demand came the answer to all our problems, Artificial intelligence (also known as AI).

At this moment in time AI is being used across almost all major industries. A large number of establishments not using AI face being left behind in our extremely competitive economic race.

In this article, we will be shedding light on its advantages in the fashion and advertising industries.

AI and the fashion industry:

AI has established its role in the fashion industry quite firmly. Fashion retailers are going bankrupt due to the lack of importance given to AI. Due to this high demand, each year, the total expenditure on AI in the fashion industry is estimated to reach a whopping $7.3 billion by the end of 2020.

In the fashion industry, where only the top 20% of global brands are considered to be profitable, the need for a tool to maintain their relevancy is immense. It allows easy access to large chunks of data, customer personalization, and various other services which the fashion companies will not be feasible to run without.

AI is used mainly in three areas:

  1. Apparel design: Due to its ability to collect intricately detailed data sets, fashion companies are using this technology to better satisfy and understand customer needs and also be able to design better clothing from feedback. Zalando which is a German-based fashion platform has been designing its clothes using AI which picks up information depending on a wide set of customer choices which range from the material of clothing to clothing style and color.
  2. Making manufacturing easy: Fashion trends are fast-changing and there is a need for the pattern of change to be identified. AI is able to do this with ease while also being able to supply the apparel to shelves much faster than a normal retailer. Taking advantage of this, companies can confidently provide immediate service thus gratifying their customers based on their demands and needs. Examples of companies using this are brands such as Zara, TopShop, and H&M.
  3. Selling merchandise virtually: AI has the ability to break down the walls between the online and in-store shopping experience. This is being done through augmented and virtual reality technology, allowing customers to access apparel online using AR. Certain brands like Tommy Hilfiger are using virtual reality to create virtual pop-up retail stores.

Now you may ask how this works. AI is largely used in the fashion industry in the form of chatbots using which the fashion brand gathers information about the customer’s needs and desires. It has become an indispensable tool and is able to identify the customers fast changing desires.

AI and the Advertising industry:

AI plays a very important role in the advertising industry as well. It is able to identify elements that will resonate with the viewers, creating ads without any human involvement. It is also able to perform audience targeting and ad buying. Major platforms are using AI, taking advantage of its ability to determine if viewers would click on the ad they are being presented with.

It is able to intelligently identify and segment audiences, build ad creative, test variations, improve performance and also optimize spend. It has proven to be advantageous to digital advertising and the careers of marketing experts who plan and run ad companies.

Advertising at scale is something that is tricky and impossible for humans to perform and AI comes in quite handy here. The technology has the unique ability to detect patterns and predict what changes need to be made to a campaign to improve it against its specific KPI. This does not take days, hours, or even minutes but can be done in a span of just a few seconds.

The advantages of AI in advertising are hence as follows:

  1.  Increasing revenue through analyzing data at scale
  2. Reducing costs by acting on data faster and automatically
  3. Creating a massive competitive advantage

It plays a key role in real-time advertising, buying, and selling. This is most popularly done with the help of third-party apps like Facebook, Instagram, and Snapchat. These ads are suggested through AI looking at the links that are promoted by the user.

Taking all these facts into consideration it is pretty clear that a career in AI, especially in our day and age has huge scope and its benefits are undeniable! AI is transforming the fashion and the advertising industry as well as many other industries and thus considering artificial intelligence training at this point is a very smart thing to do!

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