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Category: Analytics

Is A Supply Chain Analytics Certification A Good Investment Of Your Time and Efforts?

Posted on by Imarticus Learning

Supply Chain Management is a rapidly growing field with tremendous potential for career growth. With the advancement of technology and globalisation, the demands on supply chain professionals have increased exponentially. A successful career in Supply Chain Management involves analysing data, understanding customer needs, and managing resources to ensure customer satisfaction.

Supply Chain professionals are highly sought after due to their ability to forecast market trends and respond quickly to changes in demand. They are expected to create efficient strategies for optimising inventory levels, manufacturing processes, distribution networks and transportation systems to reduce costs and improve customer service. Additionally, they must understand how each element of the supply chain affects one another to identify opportunities for improvement.

Those pursuing a career in Supply Chain Management should have strong analytical skills, make informed decisions quickly, and be comfortable working with various stakeholders. Supply Chain Managers must also possess excellent communication and problem-solving skills to collaborate with other departments and develop innovative solutions effectively.

How can a Supply Chain Analytics certification help gain industry insights?

best supply chain management and analytics courses

A Supply Chain Analytics certification provides professionals with the knowledge and skills necessary to identify trends and opportunities in the supply chain. Through a supply chain management course with analytics certification, individuals can improve their understanding of analytics tools, develop strategies for optimising performance, and gain insight into industry best practices. In addition, this certification can equip professionals with the ability to make data-driven decisions that will benefit their organisation.

Furthermore, Supply Chain Analysts can apply for certifications such as PMI’s SCMA (Supply Chain Management Analyst) or APICS’ Certified Supply Chain Professional (CSCP). These certifications provide comprehensive training on all aspects of supply chain management, from inventory control, logistics planning, demand forecasting and more. With these credentials, Supply Chain Analysts can demonstrate their expertise and add value to their organisation.

Pursuing a career in Supply Chain Management can open up numerous opportunities for professionals looking to build successful careers.

Certifications for Supply Chain professionals can provide them with the necessary knowledge and skills to develop efficient strategies that will benefit organisations in today’s competitive business environment.

The outlook for supply chain analysts in the industry is very positive over the next few years. According to the Bureau of Labor Statistics (BLS), employment for all logisticians, which includes supply chain analysts, is projected to grow 5% from 2019-2029, faster than the average for all occupations. A continued increase in global trade and rising customer expectations for quick delivery of goods drive growth in this field. Therefore, it’s likely that demand for experienced and knowledgeable supply chain analysts will remain high through 2023 and beyond.

What skills do you gain after a Supply Chain Analytics certification?

A Supply Chain Analytics certification can equip professionals with the ability to:

  • Analyse large amounts of data,
  • Interpret and conclude trends,
  • Implement changes that improve efficiency throughout the supply chain,
  • Identify areas for improvement in the organisation’s supply chain processes,
  • Collaboratively develop innovative solutions.

To become a supply chain analyst, the students, through the course, also learn how to use various analytics tools such as Big Data, Predictive Analytics, Machine Learning, and Artificial Intelligence (AI) to enhance decision-making capabilities.

Learn and Grow with Imarticus Learning:

The professional certification in supply chain management with Analytics from Imarticus Learning is a future-proof way to make a career with a new-age curriculum.

These certifications for the supply chain profession have been designed in collaboration with CEC, IIT Roorkee and industry leaders to provide a cutting-edge experience for candidates who wish to enter the operations and supply chain industry.

This course enables you to make data-driven decisions at strategic, operational, and tactical levels. With the current shortage of professionals with process and analytics talents, this certification prepares you for high-demand job roles such as Demand Planner, Supply Planner, and Supply and Operations Planner.

Course USPs: 

  • Premium education standards to be competitive
  • Unique pedagogy by IIT faculty & industry leaders.
  • The program prepares students to gain from trending opportunities.
  • Campus Immersion at IIT Roorkee

Learning and Training for Apache Hadoop Online

Posted on by Imarticus Learning

The amount of data generated online is increasing at a rapid pace. Organisations use raw data to derive meaningful insights to make decisions. Companies are adopting Big Data tools to process vast volumes of data from many sources. Apache Hadoop is a significant disruptor in Big Data. This technology has proved useful in capitalising on Big Data. For a career in Big Data and analytics, one must understand Apache Hadoop. A PG in Data Analytics course from a reliable and certified source is the way forward.

Let’s understand what Hadoop is all about.

What is Apache Hadoop?

Apache Hadoop is an open-source platform. It is used to store and process Big Data on a large scale. It offers reliable, scalable and distributed processing of massive amounts of data. Hadoop-based applications use data stored on clusters of commodity computers. These sysetms are inexpensive. Thus, Hadoop uses the computational power of an extensive network of clusters at a lower cost.

Doug Cutting and Mike Cafarella created the Big Data analytics platform in 2005. Many large businesses use Hadoop. It provides a cost-effective solution to store and process data. Big Data analytics is an emerging field used across many sectors. The good thing is that one can learn Hadoop online and prepare for a career in data analytics.

Applications of Apache Hadoop

Learning Hadoop can be excellent for a data analytics career. Let’s look at some of its primary uses in the real world.

Understanding customer requirements

best data analytics course

Companies in sectors like finance and telecom use Hadoop to get customer insights. For example, sales data determines when a specific product sells the most. Or why certain products sell more on particular hours or days. Hadoop can track social media data and online conversations about a business. Monitoring online data helps the business understand customers’ grievances and expectations. Hadoop’s insights can enhance the quality of service and improve customer satisfaction.

Security and law enforcement

Hadoop is also in use in the field of security. Many law enforcement agencies use it to become more efficient, proactive, and accountable. Hadoop enables them to detect suspicious activities and security breaches in real-time. The police department uses it to predict criminal activities and catch criminals. The national security agency of the USA uses it to prevent terrorist attacks.

Financial institutions also use Hadoop to detect any fraudulent transactions.

Healthcare intelligence

Healthcare providers and healthcare insurance companies are using Hadoop-based healthcare intelligence apps. These apps help process large data sets and devise smart business solutions at a lower cost. Hadoop’s scalable and inexpensive features can accommodate dynamic data and scale.

Financial trading and forecasting

Hadoop is quite popular in the field of financial trading. Its algorithm allows it to scan markets with predefined conditions and find trading opportunities. Most trading decisions are made using Hadoop in high-frequency trading.

Improving science and research

Hadoop plays a major role in the research field as well. A considerable amount of relevant data is extracted and analysed to conclude early. This saves time and effort and improves the quality of output.

Optimising business processes

The most common application of Hadoop is to optimise a company’s performance. It can improve various business processes. Workspaces are improved by monitoring the employees’ behaviour. Most business decisions can be taken with the help of insights derived using Hadoop.

Takeaway

Apache Hadoop has plenty of other applications as well. The good news is that one can easily learn Hadoop online. If you want a successful data science career, you need to build your knowledge base in the field. We at Imarticus Learning offer one of the best data science courses with placement. We have developed our Post graduate program in data analytics and machine learning after having an in-depth understanding of the data science job landscape. The data science course with placement has a cutting-edge curriculum that teaches all the in-demand data analytics tools and job-relevant skills. Applicants can also learn Hadoop online in this course.

This PG in data analytics course will transform learners into expert data scientists as the course includes real business projects, relevant case studies, and mentorship from industry experts. It guarantees interview opportunities for learners, as we have over 400 placement partners. Fresh graduates and early career professionals (0-5 years of experience) with a technical background are welcome to apply. Anyone interested in enrolling in the program can enquire about it or chat with us.

Data science is a highly rewarding career path with many job opportunities across several sectors. Our data science courses with placement will set anyone inclined to be a data analyst on the right path.

Your data analyst training course is incomplete without these features

Posted on by Imarticus Learning

Data analytics is one of the most trending careers in present times. Earlier, data was considered the new oil in the industry because of its requirement in almost every sector. These days its significance is more than oil, as none of the business sectors can survive without data and insights. 

Hence, there is an increasing need for professionals in this sector. And, you can find data analyst training in various educational institutes. But, the question is which one to choose amongst these courses. To help you solve this conundrum, the following is a list of features that a course for data analysis must contain.

5 must-have features of a data science and analytics course

As we have already mentioned, multiple data analytics courses are offered across various platforms. Some are made available online and others in colleges or universities. Some of them are free, some are paid, and some are based on the freemium model (a portion of the course is free and the rest is paid). But, which ones should you choose? This can be done with the help of a checklist which consists of some basic features. Without these, a data analyst training course is deemed incomplete. What features are these? Read on…

It should consist of placement assistance along with the training programme

 

Completing a data science and analytics course and securing a job right afterwards would help you secure a handsome salary package. Therefore, your data science course should have a placement programme and the partner companies should be some of the reputable names in the industry. Otherwise, you will not get the exposure you need to build a successful career in this domain.

The curriculum should be job oriented

If your course lacks the modules that are helpful for the job, then you are in for a rude shock, as none of the placement agencies like candidates who do not have skills that make them job-ready. By this, we mean that you should have knowledge of data science and analytics modules like Python, SQL, Power BI and Tableau. Without these courses in the curriculum, you will not even be considered for an interview. So, be on a sharp lookout while selecting the programme.

There should be live learning modules

The training methodology needs to be hands-on. The faculty should teach you all the basics of data science and analytics, as well as the prevalent practices in the industry. If you are able to grasp the whole mechanism, then you will be able to take on any role in your job in data analytics. However, if your programme does not have a live learning module, then you very well know what to do. 

The programme should contain some real-world projects

Without these, you are just another data analyst in the room. Live projects enable you to test your theoretical knowledge and check your progress as a professional. Moreover, you get a chance to experience the real-world application of what you are studying and how clients and companies work, along with the type of issues you are likely to face when working as a data analyst.

The programme should offer dedicated career services

To excel in a data analyst interview, you need to give your best. And to put your best foot forward, you need to participate in interview workshops, resume building sessions, profile building exercises and one-on-one mentorship. Your data analytics training should include proper career services so that you can easily land your dream job.   

A data science and analytics course enables access to one of the most prized job opportunities, which is highly rewarding if you grab it with both hands. So, it is extremely important that you find a course that fulfils your requirements and then gives you the professional advantage you need to advance in your career. In this regard, you can use the advice mentioned above to your advantage while researching for your PG in data analytics course.

And, if you are looking for a readymade solution, consider the postgraduate program in data analytics from Imarticus Learning. This course will get you placed in the top 500 companies, and you will get a chance to learn from a well-reputed faculty with decades of industry experience in data science and analytics.

Deep learning is easier than you think: Read on

Posted on by Imarticus Learning

Do you wonder how Google translates the entire paragraph into one language in seconds? Or about the recommendations we get on YouTube and Netflix? How do self-driven cars function? All these smart innovations are the product of Deep Learning.

Deep Learning is a part of ML and AI. It uses the multi-layered structure of the algorithm. This is known as a neural network.

Almost every technical item has AI integrated. So, a career in Data Analytics has a bright future. You can learn data analytics to start your career. This is an exciting and intriguing topic. But you need the right course and guidance to become an expert. A Deep Learning career will enable you to contribute to the futurist society.

 What is Deep Learning?

 DL falls under the subcategory of AI. It’s a general term for processing, enabling computers to function independently. In simple terms, it tries to mimic human behaviour to analyse and predict. DL algorithms analyse and conclude with logical structuring. In short, it has multiple layers of neural networks.

 What is the Difference between ML and DL?

 ML is the process where computers learn data by using algorithms to work independently. They don’t need external intervention. Whereas in DL, the performance is entirely end-to-end. Users give raw data as inputs. Now, the machine performs tasks like a human brain. Deep learning facilitates the processing of unstructured data. This includes images, texts, and documents.

One needs to understand DL and its algorithm scale with data. Only then can you enable it to perform machine learning.

 A Career in Deep Learning

Deep Learning Career is the most demanding and desirable course in this digital era. Everything is shifting to AI, and mastering this skill will offer us a better future, growth and good earning opportunities. The opening for a wide range of job profiles like software engineer, research analyst, data analyst, and data engineer is taking over huge packages.

Skills Required to Master Deep Learning 

To make a Deep Learning career and learn Data Analytics, we need specific skills as a student to exercise it rightly, such as software engineering skills, including a thorough understanding of Data Structures, Algorithms, Github, and the Software Development Life Cycle.

 Deep Learning Neural Network

● Convolutional networks

● RNNs

● LSTM

● Adam

● Dropout

● Batch Norm

● Xavier/He initialisation

 Probabilistic Methodology

● Distinctive and continuous distributions

● Cost functions with the highest likelihood

● Tasks and training data with hypotheses

● Maximum likelihood-based cost

● Cross-entropy

● Cost-forward networks for MSE

● Sigmoid units, MLP

● the influence of neuroscience

● Gradual ascent

● Chain rule with recursion

● Optimal bias-variance ratio

● Regularisation

 Practical

● Linear regression

● Softmax

● tanh

● REPLY

● Tensorflow

 Job For a Deep Learning Specialised Candidate

Deep Learning Career studies and courses are transforming the lives of professionals with ample opportunities on the way. Here are some common job roles which employ the used Deep Learning:

● Software Engineer

● Research Analyst

● Data Analyst

● Data Scientist

● Data Engineer

● Neuroinformatics

● Bioinformatician

● Image Recognition

● Software Developer

● Research Scientist

● Research Fellow

● Instructor for Deep Learning

● Applied Scientist

● Full Stack Web Developer for Deep Learning

● Lead Manager – Deep Learning

● Natural Language Process Engineer

 The question of how to become a Data Analyst lies in mastering Deep Learning. Once we get this specialisation, getting hired for such job profiles is easier.

 The average salary structure for the deep learning expert ranges from $77,562 per year for a Research Scientist to $60,255 per year for a Data Analyst engineer.

 Deep Learning Career Outlook 

Computer and Information Researchers are the most sought-after profile in Deep Learning. The correct blend to learn data analytics with a clear concept of deep learning is a lucrative career path for engineers.

It is a great idea to specialise in such a futuristic subject and excel in it. So, if you want to study Deep Learning, join Imarcitus and supercharge your career with us! Contact us online, or visit our training centers spread across top cities like Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, and Ahmedabad.

The nuances of operation planning supply chain management

Posted on by Imarticus Learning

Operation planning in supply chain management is a complex task. This is because the operation planning factors impact the production process. These factors include the availability of raw materials. They also include production facility capacity, demand for final product, and disruptions in the supply chain. Operation planning must also consider the company’s objectives. This blog post discusses the nuances of operation planning. It also shares how to overcome some challenges.

1. Forecasting

A challenge in operation planning is forecasting. Forecasting estimates future demand for a product or service. This is difficult because many factors impact demand. They are the economy, changes in consumer preferences and new competitors.

AI and ML are used to help forecast demand. They analyse data to see trends. This can then be used to predict more accurately.

2. Production Capacity

Another challenge is production capacity. It is the maximum amount of a product or service produced by a manufacturing process.

There are two types of production capacity. They are theoretical and practical. Theoretical capacity is the maximum output that can be achieved. That is if all the machines in a production system are used to their full potential. Practical capacity is the maximum output that can realistically be achieved.

Practical capacity is often lower than theoretical capacity. This is because of many factors. They are downtime, maintenance, and employee breaks.

To overcome this challenge, firms need to assess their production capacity accurately. They can do this by doing production capacity analysis. This is a process that assesses the capacity of the production system. This also identifies constraints.

Constraints need to be identified. Then, firms put try to improve production capacity. This could mean investing in new machinery. Training employees to use the existing machinery can be done too.

3. Supply Chain Disruptions

Another challenge is supply chain disruptions. It is an event that disrupts the flow of goods and materials in the supply chain.

Supply chain disruptions occur due to many reasons. They are natural disasters, political unrest, and transportation problems. They can also be caused by suppliers going out of business. Failing to meet delivery deadlines is another reason.

Supply chain disruptions have a major impact on businesses. They can cause production to stop entirely. They can also lead to shortages of raw materials and finished products.

Firms must address supply chain disruption risks. This could involve diversifying the supplier base. Having alternative sources of raw materials is there. Making contingency plans can also be done.

4. Miscellaneous Challenges

It is important to think of other challenges impacting operation planning. They are quality issues and regulatory changes.

Quality issues can occur when products do not meet the required standards. This could lead to customer returns, production delays, and financial losses.

Regulatory changes can impact operation planning if the products or services being produced are subject to government regulation. For example, if the government introduces new environmental regulations, this could impact the production process and the materials used.

New product development can also impact operation planning. This is because new products often require different production processes and materials. This can lead to supply chain disruptions and production capacity changes.

It is essential to consider all of these potential challenges when operation planning. By doing so, companies can be better prepared to deal with them if they do occur.

Conclusion

Operation planning is a complex process that must take into account many factors. The challenges discussed in this article are just some of the challenges that need to be considered.

Companies must overcome these challenges to ensure that their operation planning is successful. They can do this by conducting a production capacity analysis, implementing measures to mitigate the risks of supply chain disruptions, and considering all potential challenges.

If you want to learn more about operation planning, overcoming these challenges, and embark on a career in this field, consider enrolling in Professional Certification in Supply Chain Management & Analytics by the prestigious IIT Roorkee. This program will give you the skills and knowledge you need to become a successful supply chain analyst.

Some key features of the operation planning course in supply chain management include Certification by IIT Roorkee, hands-on learning with real-world SCM projects, and live sessions with IIT Roorkee faculty and industry experts.

If you need assistance regarding the program, contact us through chat support or drive to our training centres in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad. We will be happy to assist you.

Training in Excel as A Data Analyst? Read On

Posted on by Imarticus Learning

There are different opinions when it comes to training for a job in data analysis. Some people will tell you that getting a degree from a top university is the only way to succeed. Others will say that experience is more important than anything else. And still, others will tell you that specific skills, like the ability to use Excel, are what matters. So, who should you believe?

As it turns out, all three groups of people are partially right. You can gain entry with a degree from a prestigious university. And yes, experience is essential. But when it comes to landing a job as a data analyst, specific skills—like the ability to use Excel—can decide between getting an offer and passing over.

Why Excel Skills Matter for Data Analysts?

Excel is the most commonly used program in business today. That’s because it’s a potent tool for everything from keeping track of sales numbers to performing complex financial analyses. And while Excel might seem like a program that anyone can use, the fact is that most people only know how to do the basics.

 

As a data analyst, though, you need to be able to do more than just the basics. You need to be able to use Excel to its fullest potential to find trends, uncover relationships, and make predictions. In other words, you need to be an expert. And that’s why having Excel training can be necessary when looking for a job as a data analyst.

Excel Skills You’ll Need as A Data Analyst

You will learn analytical and visualization techniques in this course, which will help you improve your current work performance and your job prospects in the future. If you’re in business or data analysis and want to enhance your employability, learn advanced Excel and basic Power BI.

So what kind of Excel skills do you need to land a job as a data analyst? 

Here are just a few of the things you should be able to do:

  • Import and export data from different software programs 
  • Use basic formulas and functions 
  • Create charts and graphs 
  • Perform simple statistical analysis 
  • Write macros 
  • Use pivot tables 

As you can see, having training in Excel can give you a real leg up when you’re looking for a job as a data analyst. However, it’s important to note that simply taking an excel course is not enough—you also need to learn python online and have some experience working with data to excel in this field. Still, if you’re looking for a way to enhance your chances of landing a job as a data analyst, getting training in Excel is certainly worth considering.

Discover PG in data analytics with Imarticus Learning

 You might be able to find employment at Tableau with the aid of this data analyst training. Create complex models using data science to produce vital business forecasts and insights using what you’ve learned.

Course Benefits for Students:

  • Students will be familiar with the most common data science methodologies and tools and the fundamentals of data analytics and machine learning.
  • Students who complete 25 real-world projects and case studies under the guidance of business partners will receive a data analytics course with placement.
  • The Data Analytics and machine learning course is an intensive program that will teach you how to use data analytics to solve real-world problems.
  • One of the most in-demand skills on the market is the capacity to display data using a data analytics tool.

Visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad, or get in touch via the chat support system.

Sports Analytics and Big Data: A Guide to Analyst Training

Posted on by Imarticus Learning

Big data and data analytics are becoming widely popular terms in today’s technologically dominant landscape. Numerous organisations and sectors are embracing these emerging technologies to make fruitful use of data. The sports industry is also leveraging big data analytics to revolutionise sports.

Data analytics and sports might seem completely unrelated. But, data analytics has proven useful in improving game quality, fan experience and player safety. Nowadays, sports analytics are taken very seriously by professional teams, managers, coaches and players.

 

Data analytics jobs are in huge demand these days. These jobs pay well and provide several opportunities to aspiring data scientists. If you are a sports fan, you can now have a rewarding career as a data analyst. Sports analytics is the perfect career choice for you, allowing you to pursue your love for sports. However, since data analytics is a technical field, you need to have proper data analyst training.

How is sports analytics changing the game?

It helps coaches make decisions regarding the recruitment of athletes.

Player recruitment is an important part of any sport, particularly at the professional level.

Many modern sports franchises are leveraging data analytics to recruit the right players for their teams.

Data is being used to identify and hire talented but undervalued players.

Universities are also using data analytics to discover potential upcoming athletes. This allows them to understand where to invest their time and efforts.

It helps broadcasters create a better viewing experience for fans.

Sports commentary makes watching a sport more fun. The broadcasters provide stats and facts for viewers to understand the importance of each event. This makes the viewing experience more compelling. This is made possible by big data analytics.

Big data is also being used to increase live attendance in stadiums by satisfying fans and enhancing their overall experience of watching a game live. This can be done by analysing which games have better chances of selling swiftly and prompting frequent audiences to buy tickets.

Another way to compel audiences to watch games live is to improve the supply of items that are in high demand. This can include merchandise, eatables, etc., which can improve the viewer experience.

Big data can also be useful in tackling the factors which affect the viewer experience negatively. For instance, it can save viewers from the struggle of finding a parking spot by carrying out traffic analysis.

It is used to create better sporting strategies.

Strategy plays a significant role to win a game. Be it an individual sport or a team sport, players cannot compete without a strategy in mind.

Coaches make use of big data to create personalised winning strategies for each player and the team as a whole. For example, Liverpool FC’s coach used data analytics to compete against opponents and emerge as winners of the Premier League.

It helps in live data collection.

Data like speed, distance, mileage, etc. is difficult to gather manually. However, with wearable devices operated using artificial intelligence and machine learning technologies, vital data can be collected in real-time.

The devices are worn by players or attached to their clothes to keep track of player performance and fitness variables like heartbeat, speed, etc.

This data can help coaches in preparing an ideal fitness plan for players and improve their safety.

RFID tags are also attached to players or their sports equipment to collect crucial data.

It allows better judgment.

Many times, a situation occurs where the referees might find it challenging to take a decision. Thus, they might end up taking the wrong decision. This impacts the whole game and demoralises the players.

With big data and analytics, sports authorities now make use of devices that can track data which is difficult to be observed by the human eye. For example, it can give information on a strike or a ball hit that could be missed by referees.

Sports analytics is a relatively new field and the sports industry is still in the process of optimising its applications. Thus, it has a huge scope for research and development.

However, data analyst training is necessary to enter this job market. Our team at Imarticus Learning has designed an data Analytics and Machine Learning course to kickstart your data analyst career. Our Postgraduate Program in Data Analytics and Machine Learning comes with guaranteed interview opportunities and extensive career services. Graduates and professionals (with up to 5 years of experience) having a technical background are eligible to apply.

Sports analytics is an upcoming and interesting area of work. Join the big data revolution to make sports more fair, entertaining and competitive.

The Future of Programmatic Marketing: Machine Learning Certification Course in 2023

Posted on by Imarticus Learning

The world has observed rapid growth in Programmatic Marketing. Companies are expanding huge sums of money on programmatic advertisements. It was estimated that companies will spend around $542.31 billion in this industry. This number will continue to grow in the future. 

Machine learning plays a huge role in the industry of programmatic marketing. If you are willing to commence a career in programmatic marketing, then you will require an online machine learning certification course. In this article, we will discuss the future of programmatic marketing and the role of machine learning in it. 

What is Machine Learning?

One of the most important subfields of Artificial Intelligence (AI) is Machine Learning (ML). Machine learning allows a machine to remember and learn without any complicated programming language. The learning procedure is only possible by identifying patterns and analysing data. Industries around the globe can enhance their business and marketing by simply using machine learning. This technology furthermore strives to comprehend the customers and their behaviours. 

What is Programmatic Marketing?

Programmatic Marketing is the distribution of advertisement that does not involve any human being. In other words, this means selling and buying products with the help of advanced software in the digital space. To target customers, programmatic marketing extracts data like age, location as well as interest. This helps the companies to easily target their customers and yield more percentages. 

How is Machine Learning Used in the Field of Programmatic Marketing?

 

As we already know the definitions of machine learning and programmatic marketing, let’s learn how these two aspects are interdependent. Machine learning is mainly used in programmatic marketing to extract and analyse data from myriad sources. It also sorts customer data patterns and assists companies to understand their customers. This helps these companies to enhance themselves as well as their services and campaigns. For example, a retailer may use the insights to check the items the customers purchased during a particular season so that they can yield more revenue in the next year.

Machine learning can even target customers from various sources like social media and online traffic to advertise a particular product of a particular company. Like this, it can enhance the performance of the advertisements as well as the reach of the products. If a company is willing to increase its reach and campaign performance, then opting for machine learning will be the wisest decision.

What Does the Future of Programmatic Marketing Store for Us?

The future of programmatic marketing is very bright and will keep on growing. Companies are already investing huge sums of money in this arena and this investment will increase in the future. As the world is getting dependent on programmatic marketing, many modifications will take place in future. Here we have discussed a few of those modifications. 

Supply Path Optimisation (SPO)

Supply Path Optimisation is a very new term and is being used very recently. However, according to the predictions, the usage of SPO will only increase in the future. The main purpose of SPO is to make the supply chain easier between publishers and advertisers.

Demand Path Optimisation (DPO)

Demand Path Optimisation is the inverse of Supply Path Optimisation. Its emphasis is on the buying factors rather than the selling factors.  When DPO is incorporated with SPO they create better transparent terms with the potential buyers.  DPO can boost revenues and reduce unnecessary risks from ad vendors.

Programmatic Audio

Programmatic Audio is something very similar to display advertising. However, here advertisements are played in the form of audio. This method can be used on the radio, podcasts and music streaming applications. 

A World Without Any Cookies 

Industries are planning to eradicate all the cookies used by third parties. By the end of 2023 companies are willing to terminate the two decades old practice. Subsequently, brands and marketers will use solutions that are user-oriented and will focus on privacy as well. 

Conclusion 

If you want to commence a career in programmatic marketing then you must enrol yourself in a certificate program in data science and machine learning. This online course will help you to earn the requisite skills and knowledge about programmatic advertisements. Besides, this program will also open many opportunities for those who want to commence a data scientist career. So without any further delay enrol yourself on the certified program by Imarticus Learning.

Earned a data science certification? What next?

Posted on by Imarticus Learning

A Data Science Certification course can be an excellent way for students to gain the skills and knowledge needed to pursue a career in data science. The course will provide an in-depth overview of data science concepts, techniques and technologies essential for success in this field. Through the certification program, students will develop the ability to manage and analyze large datasets effectively, create visualizations from their findings, build predictive models, and confidently use machine learning algorithms.

best data analytics course

By completing a Data Science Certification program, students can access job opportunities at established tech companies and cutting-edge startups that require skilled professionals familiar with data science tools and best practices. Furthermore, they will acquire the technical expertise necessary to tackle real-world problems and develop innovative solutions. With the acquired knowledge, students can pursue various roles, from data analyst to data engineer to data scientist.

By having a Data Science Certification, employers will recognize that you have the skill set needed to succeed in the ever-changing world of Big Data and Analytics. Your certification will also demonstrate that you have taken the initiative to acquire more specific skills related to this field and be committed to learning more.

How can PG in Data Analytics after data science certification help?

A PG in Data Analytics can help students build upon the skills and knowledge gained through completing a Data Science Certification program. This program offers hands-on projects, allowing students to further develop their expertise in data science tools while applying them to real-world scenarios. Students will learn advanced techniques such as natural language processing, deep learning, and image recognition that cannot be acquired through a certification program alone. Additionally, some postgraduate programs guide how to create a portfolio that successfully showcases your capabilities as a data scientist. Finally, the postgraduate program may offer mentorship from industry professionals or networking opportunities with other experts in the field, both of which are invaluable for career growth. Combining a Data Science Certification with a Post Graduate Program in Data Analytics gives students a strong foundation for developing a successful career in this field.

Thus, it is clear that with the help of a data science course with placement and a postgraduate program in data analytics, students can transform their careers and get desirable growth opportunities. With the acquired knowledge and skillset, they will be prepared to take on challenging roles in data science and remain competitive in this rapidly changing field.

How does Learning Hadoop help with Data Science and Data Analytics?

Learning Hadoop can be beneficial for those interested in data science and analytics. Hadoop is an open-source software framework that stores, processes, and analyses large datasets quickly and efficiently. It enables developers to write programs that process massive amounts of data across distributed clusters of computers. By learning Hadoop, students will gain the skills and expertise necessary to build more complex data systems and manage large-scale datasets. Furthermore, when you learn Hadoop online, it allows you to understand the different parts of a data science project, from building an ETL pipeline to producing meaningful insights. Therefore, adding Hadoop to your data science skill set can open up new possibilities for career development.

Making a Career Transition with Imarticus Learning:

Are you looking for an edge in the highly sought-after data science and analytics field? Imarticus Learning has just what you need! Their personalized Postgraduate Program In Data Science And Analytics is designed to give recent graduates and professionals a head start on their careers. You will gain industry knowledge and the practical skills necessary to succeed in this ultra-competitive job market – all while benefiting from guaranteed job assurance upon completion of your program! With 25 real-world projects crafted by experts geared explicitly towards today’s businesses, get ready to make waves as one of tomorrow’s tech superstars starting now with Imarticus Learning.

Course USPs:

  • Build a strong foundation of Excel for data analysis
  • Summarise data with pivot tables and charts
  • Build a solid foundation for programming
  • Practice coding skills with 20+ coding questions
  • Build a strong SQL foundation for data querying
  • Create datasets for data analysis
  • Run data analysis process using Python libraries

Is a postgraduate program in data science worth the hype?

Posted on by Imarticus Learning

There is no doubt that data science is one of the most popular and in-demand fields today. 

And with the ever-growing amount of data being generated daily, the demand for qualified data scientists will only continue to increase.

A postgraduate program in data science can be an excellent investment for your future. The field of data science is constantly evolving, and having the latest skills and techniques can help you find more attractive job opportunities. And with the internet age, you can learn data science online right from home.

So, if you’re considering a data scientist career, a postgraduate program in data science is definitely worth the hype! 

In this blog, we’ll look at a few reasons why that’s the case

  • In-Demand Field

Data science is one of the most in-demand fields today. Companies are always looking for ways to improve their business operations and make better decisions. 

With the rapid growth of data-driven industries, there is a constant need for experts who can analyze and interpret large data sets.

Data science combines computer science, statistics, and mathematics skills to extract knowledge and insights from data using various techniques. They then use their findings to build predictive models and make business recommendations.

Data scientists use their skills to solve real-world marketing, finance, healthcare, and more problems.

  • Competitive Salary

A postgraduate program in data science can provide you with a competitive salary. With the right skills and experience, you can easily earn well enough.

In general, data science is a very lucrative career choice. The average industry salary for data analytics and machine learning roles is between Rs 5-25 Lacs. With the right skills and experience, you can easily earn well enough to support yourself and your family.

  • Make You Skilled

A postgraduate program in data science can help you build a successful career by equipping you with the latest tools and techniques to tackle real-world problems effectively.

The program will enable you to identify and solve complex business problems by applying data-driven methods. You will also learn to communicate your findings to decision-makers effectively.

Working on real-world projects will allow you to gain practical experience that will be invaluable in your future career. In addition to the practical experience, you will also gain a deep understanding of data science concepts. This will help you develop new skills and knowledge to apply to your future career.

  • Specialisation

A postgraduate program in data science will allow you to specialise in a particular area of data science. It will make you more valuable to potential employers, as you’ll be able to offer them a more specific skill set.

Many types of data science programs are available, so choosing one right for you is essential. Consider your career goals and the kind of data you want to work with before deciding.

You can become a data scientist, machine learning engineer, business analyst, AI engineer, web and social media analyst, ML consultant, etc. There are many possibilities for you to explore.

  • Networking

Networking is an important part of succeeding in any field, and data science is no exception. With the right approach, you can easily make connections that can help you advance your career.

In addition to networking, postgraduate programs in data science can also help you learn from some of the best minds in the field. You’ll have access to lectures and seminars from world-renowned data scientists, and you’ll be able to learn from their experiences. This can help you develop the skills you need to succeed in your career.

  • Certification

The certification from a prestigious institute will put a stamp of authority beside your name and give you credibility. Your employers will feel more confident in working with you.

Conclusion

Data science is a rapidly growing field, and there will be plenty of opportunities for you to advance your career. With the right skills and experience, you can easily become a leader in the field.

You can learn data science online if you’re looking to pursue a data scientist career. Imarticus Learning offers a data science course with placement. It’s designed for students who want to learn data science from the ground up, and it includes complete access to our online learning platform, so you can start putting your skills to use immediately. You can visit one of their centers to learn more about the program.

If you’re considering a postgraduate program in data science, hesitate no more! The time to take the next step is now.