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Category: Management

How learning a tableau course can enhance your career prospects

Posted on by Imarticus Learning

With the advancement of technology, data skills are in demand. Everything we do revolves around the analysis of people’s behavior and understanding the statistics behind their decisions. Tableau is a computerized program that improves this analysis by making data more simple and accessible. It converts big data into a small and understandable form, at the same time giving an insight into the small data. 

The Tableau course at Imarticus will build a career in business intelligence and data analytics. You can get answers fast and also develop an unforeseen insight into statistics.

Tableau Career Opportunities

Today, companies have an enormous inflow of data with implications in their business. Therefore business corporations across the globe need an interactive and easy-to-use tool that can examine the data while giving an insight into it. 

Tableau software helps these corporations to visualize, explore, examine, and share the data so that they can take timely action and spread their business.

Tableau Analytics should have analytical skills. They should be problem-solving, innovative, and detail-oriented. They should also be a team worker and know business intelligence tools and Query languages.

With the data analytics course with placement by Imarticus, you will become a Tableau professional. Our program covers all the fundamentals and topics for building a promising Tableau career. We will teach you everything from scratch so that your career moves to the peak level. After the completion of this course, you will have varied career options, such as: business analytics certification courseTableau consultant

  • Data analyst
  • Business analyst
  • Business intelligence analyst
  • Business intelligence developer
  • Business intelligence manager

As a Tableau developer, you will prepare visualization and presentation and conclude data to improve business excellence. Tableau visualization will assist you to create innovative solutions for business problems.  

Tableau professionals can work on business problems and provide technical solutions for them. The visualization of the data will help them in finding an innovative solution and they can also work with the storage tools. With the development and expansion of the organization, the inflow of business data will also increase. Tableau Analytics can also enhance the system of the organization to meet this increase in data.

Data visualization and business intelligence are the requirements for the success of business organizations. The growth of many organizations depends upon these. Thus, the future of a Tableau professional is promising and bright.

Data Analytics Certification

We know that data is the backbone of every organization. With the increase in data, its storage is also increasing. Therefore, data visualization tools like Tableau help us to visualize data and examine the results.

At Imarticus, we know the value of data science. With our Data Analytics and Machine Learning Course, you will learn the real-world application of data science. You can build significant models that will give insight into the business. You can also make predictions.

If you are looking for a career in data science and Analytics, our course will help you become a Tableau professional. We have a 100% track record of interview and placement after completing this course successfully.

Spark or Hadoop? Here’s the Answer to this Dilemma

Posted on by Imarticus Learning

Every year, an increasing number of distributed systems to manage data are introduced to the industry. Among them, Spark and Hadoop have emerged as the most successful ones. This article discusses these two systems and tries to find out which one is better.

What’s Hadoop?
Hadoop is a general-purpose form of distributed processing that consists of several components. The Hadoop Distributed File System (HDFS), YARN and MapReduce are some very important components of Hadoop. Even though this system is entirely built in Java, it is accessible through many other languages including Python. An SQL like interface which allows running queries on HDFS, Hive is another important feature of Hadoop.

What’s Spark?
Spark is a relatively new project developed in 2012. It enables us to process data in parallel across a cluster. The major difference with Hadoop is that it works in-memory. Spark can process data in RAM using a concept called RDD or Resilient Distributed Dataset. It also comes with several APIs. Even though the original interface was written in Scala, based on the heavy usage by data scientists, R and Python endpoints were also provided.

Now let’s take a look at these platforms in different perspectives such as performance, cost and machine learning.

Performance
It is found that spark can run 100 times faster in-memory and ten times faster on disk than Hadoop. Especially when it comes to machine learning applications such as Naive Bayes and K-means, Spark is much faster. Following are the crucial reasons behind the better performance of Spark.

While running a selected part of a MapReduce task, Spark is not limited by the input-output concerns. It enables faster operation in applications.
The DAGs of spark permits optimization between each step. So, there would be performance tuning during the process which is not present in Hadoop.
However, in situations where the spark is running on YARN, the performance is found to be reduced. Also, sometimes it could lead to RAM overhead memory leaks. So, in a batch processing use-case, Hadoop is the more efficient system.

Costs
Since both Spark and Hadoop are open-source Apache projects, you can potentially use them with zero installation cost. However, there are other costs such as maintenance, hardware purchase and costs of supporting team. We know that the Hadoop requires more memory on disk and spark requires more RAM. In that sense, spark clusters are more expensive to set up. Also, since it is a new system, the experts of Spark would be rarer and more expensive.

Machine Learning Capabilities
Spark comes with a machine learning library, MLLib to use for the iterative machine learning applications. It includes regression and classification. Also, you can build machine learning pipelines with hyperparameter tuning using it.

Hadoop makes use of Mahout to process data. It has clustering, batch based collaborative filtering, and classification. Lately, it is being phased out in favor of Samsara. It is a Scala-backed DSL language and allows you to build your own algorithms.

Conclusion
It is sure that these two are the most prominent distributed systems available today for data processing. Between them, Hadoop is mainly recommended for disk-heavy operations while Spark is more flexible. However, the in-memory processing architecture Spark is more expensive than that of the Hadoop. So pointing out one as better than the other is not easy. It varies under different circumstances.

Beat the market: Learn Computer Vision in Python

Posted on by Imarticus Learning

Are you looking to learn a new skill that can give you an edge over your competition? If so, then you should consider learning computer vision with Python. This powerful programming language has become increasingly popular in recent years and is perfect for tackling complex computer vision tasks.

This blog post will discuss computer vision and learn it using Python. We will also provide a few resources to get you started!

According to the World Economic Forum, nearly half of all jobs will get replaced by automation within the next 20 years. To stay relevant in this speedily changing world, we must learn new skills that can help us adapt and succeed.

One such skill is computer vision which allows you to teach computers to see as humans do! It’s an excellent process to stand out from the crowd, and you can use it in various industries such as security, manufacturing, healthcare, and more.

What is computer vision?

It is a field of AI that trains machines to understand the content of digital images or videos. You can do it by using algorithms, machine learning techniques, and deep learning networks to identify objects in an image or video frame.

With Python programming language, it’s possible to create programs quickly without having profound knowledge about computer vision algorithms or models. 

Tips to get started with computer vision in Python

There are many different ways to get started with computer vision in Python.

OpenCV library:

The OpenCV library is a popular choice for working with computer vision in Python. It provides a wide range of functions that allow you to efficiently perform tasks such as object detection and feature extraction from images or video streams. 

Scikit-learn library:

The Scikit-learn library is another popular choice for working with computer vision in Python. It provides a range of algorithms for performing image classification, object detection, and regression analysis tasks. 

Keras library:

The Keras library is another popular choice for working with computer vision in Python. It provides a high-level neural networks API, making it easy to build and train deep learning models. 

Tensorflow library: 

The Tensorflow library is another popular choice for Python computer vision. Python’s high-level programming language provides an API for building and training neural networks.  

Matplotlib library: 

The Matplotlib library is another popular choice for working with computer vision in Python. It provides a high-level API for creating charts and graphs using the Matplotlib library is another popular choice for working with computer vision in Python.

 Discover AIML Course with Imarticus Learning

The Artificial Intelligence and Machine Learning certification collaborate with industry professionals to deliver the most satisfactory learning experience for aspiring AIML students.

best artificial intelligence courses by E&ICT Academy, IIT GuwahatiThis intensive Python certification will prepare the student for a data scientist, Data Analyst, Machine Learning Engineer, and AI Engineer.

Course Benefits For Learners:

  • This Supervised Learning course will help students improve their Artificial Intelligence basic abilities.
    Students can take advantage of our Expert Mentorship program to learn about AIML in a practical setting.     
  • Impress employers and demonstrate their AI talents with a Supervised Learning certification supported by India’s most famous academic collaborations. 
  • This course will help students gain access to attractive professional prospects in Artificial Intelligence and Machine Learning.

Procurement- Switch your focus from sourcing to supply chain management and analytics

Posted on by Imarticus Learning

The world of procurement has changed dramatically in the past decade. With an increasing shortage of skilled labor and a rising global economy, companies are experiencing growing pains trying to keep up with the demands for goods and services. 

One way to meet these challenges is by adopting new procurement methods to serve your organization’s needs better. This blog post discusses how to start focusing on supply chain management and analytics instead of just sourcing materials for production! 

What is supply chain management?

Supply chain management is the process of planning, organizing, and managing the flow of materials and goods from supplier to consumer. It includes forecasting demand, coordinating production schedules, managing inventory levels, and ensuring that products are delivered on time and in good condition. 

The reason to focus on supply chain management is that it allows you to optimize your entire production process. By understanding how the different parts of the supply chain interact, you can identify and address any inefficiencies. It will help you reduce costs, improve quality, and increase production speed. In addition, you can use supply chain analytics to make better decisions about where to allocate resources and how to respond to market fluctuations.

The benefits of focusing on supply chain management 

The main challenge in focusing on supply chain management is that it requires a lot of time and effort to set up and optimize. Getting everyone on board with the new approach can also be challenging. However, with careful planning and execution, the benefits of supply chain management will far outweigh the costs. 

Some of the benefits include:

  • Reduced manufacturing and inventory costs
  • Improved quality and speed of production
  • More accurate forecasting of demand
  • Easier identification and resolution of problems in the supply chain
  • Greater flexibility to respond to changes in the marketplace

How to start focusing on supply chain management?

Focusing on supply chain management is not easy, and it will take some time to design your system correctly. One way that you can start making this transition is by setting up a dedicated team within procurement. This team should create an overall strategy and work with other departments (such as engineering) to implement changes. You will also need to invest in the right tools and software to help you manage your supply chain.

The procurement world is changing, and those who don’t adapt will be left behind. By switching your focus from sourcing materials to managing the entire supply chain, you can improve efficiency, reduce costs, and stay ahead of the competition.

Explore Supply chain Management Career with Imarticus Learning.

The supply chain management course with analytics offers an experience beyond just classroom learning – our partnerships allow candidates interested in entering this hands-on field training from some of today’s top professionals!

Course Benefits For Learners:

  • We prepare students for a rewarding career in Supply Chain Analytics course by immersing themselves in six real-world projects that will provide them with a thorough understanding of the sector. 
  • Supply chain management course prepares students for competitive jobs such as Demand Planner or Data Scientist, which employers today have in high demand! 
  • By utilizing the power of Python, this course will help students become more data-centric and enhance Supply Chain decision-making.

What Are The New Advancements In Data Analytics?

Posted on by Imarticus Learning

Data analytics is a field which witnesses a continuous revolution. Since data is becoming increasingly valuable with each passing time, it has been treated with great care and concern. New tools, techniques, theories, and trends are always introduced in the data analytics sector to cope with the constant changes in the industries and societies. You can opt for a sought-after data analytics course to get a deeper understanding.

In this article, we will go through some of the latest data analytics opportunities which have come up in the industry.

The Intelligent Data Mesh

The intelligent data mesh has been termed the next revolution in healthcare and medical diagnostics systems in the coming years by the Gartner Top 10 Strategic Technology Trends in 2018.

The “Intelligent Data Mesh” has been described by Gartner as a meeting point of the physical and digital worlds where humans, machines, data, and services have been entwined together into a mesh.

The purpose is to gather the benefits offered by all these individual entities into a single unit to find solutions to complex issues thought to be insolvable until now.

One major industry expected to benefit most from this system is the healthcare industry where Intelligent Data Mesh is being hailed as a game-changer in enhancing patient care.

Blockchain

Blockchain continues to be an exciting technology even in 2018 and is expected to remain so for at least another decade. New advancements are being made almost daily regarding this technology as blockchain finds wider uses in various industries with time.

It will not be wrong to describe blockchain as one of the greatest data analytics opportunities. The concept of blockchain started with the idea of a decentralized digital currency which came to be known as Bitcoin in the market.

However, even though the controversy regarding the currency rose the concept of a decentralized and open-source peer-to-peer modeled technology for storing and analysing data. The concept of blockchain is now applied in a wide range of industries with its use predicted to keep rising soon.

Artificial Intelligence

Artificial intelligence is one such data analytics opportunity which is finding widespread adoption in all businesses and decision-making applications. As per Gartner 2018, as much as 41 percent of organizations have already adopted AI into some aspect of their functioning while the remaining 59 percent are striving hard to do the same.

There is considerable research going on at present to incorporate artificial intelligence into the field of data science too. With data becoming larger and more complex with each passing minute, management of such data is getting out of manual capacities very soon. Scholars have now turned to AI for storing, handling, manipulating and managing larger chunks of data in a safe environment.

Augmented Reality

Augmented Reality is an interesting new technology coming up in recent years. As a source which facilitates the interaction between machine and humans in a unique manner, AR has the potential to be a game-changer in the field of data sciences making it another top data analytics opportunity in the future.
best big data analytics course

AR can provide for the development of simpler UIs for the man-machine interaction when merged with AI allowing the users to store and interact with data in a completely new manner.

Imagine going to an island where all your data is stored in different treasure chests and you are provided with customised keys to access the chests with your data in it. These things may be possible in the future because of the use of AR in data analytics. 

Imarticus Learning offers select best data analytics courses that not only boosts your skillset but also your career as a whole. 

Frequently Asked Questions

What is a data analytics course?

Data analytics involves examining raw data to extract valuable and actionable insights. These insights, once gleaned, serve as the basis for informed and strategic business decisions, contributing to the enhancement of overall business intelligence.

Do data analysts require coding?

Certainly, coding is a fundamental requirement when undertaking an online Data Analytics Degree. While highly advanced programming skills may be optional, mastering the basics of R and Python is crucial. Additionally, a solid command of querying languages such as SQL is indispensable for a comprehensive understanding of data analytics.

Is Python a mandate for data analysts?

Possessing a thorough grasp of Python programming proves highly advantageous for data analysts. Employers commonly anticipate proficiency in utilizing Python libraries to streamline various data-related tasks. Consequently, acquiring skills in Python emerges as a prudent and strategic career decision for aspiring data analysts.

Why is blockchain important in logistics management?

Posted on by Imarticus Learning

Blockchain is a new technology that will play an important role in logistics management. By utilizing Blockchain, we can streamline the process and reduce paperwork, time, and costs associated with international trade.

 Blockchain will also make it easier to track the status of shipments as they move from one country to another. This blog post will go through the overview of Blockchain and the benefits of using Blockchain in logistics management.

What is Blockchain?

Blockchain is an automated record-keeping system that makes it possible to improve supply chain efficiency, reduce costs and increase transparency. You can use Blockchain to track shipments across borders by recording the origin, destination, location, timestamps, and other essential data points. 

By utilizing distributed ledger technology (DLT), Blockchain creates an immutable and transparent record of all transactions. It allows for improved trust and collaboration among supply chain partners.

Blockchain is still a new technology, but several companies are already exploring its potential in logistics management. Blockchain has a lot of prospects to revolutionize the logistics industry, and we can see more companies adopting this technology in the coming years.

The benefits of using Blockchain in logistics management are:

  • Increased transparency and trust between supply chain partners
  • Faster, more accurate data sharing across the supply chain
  • Reduced costs and improved efficiency due to reduced paperwork and faster processing times
  • Greater visibility of the entire supply chain, from supplier to customer.
  • Improved security against cyber threats.

How to implement Blockchain in your business?

To implement Blockchain in your business, you need to understand how it works. First, a user or machine creates a block with a unique cryptographic hash. This block contains data and a reference to the previous block.

Blocks are chained together, forming a blockchain, which allows for secure and transparent recording of transactions. Every machine on the network has a full copy of the Blockchain to ensure all members agree and that no one can add or remove blocks without consensus from other network participants. 

This way, it’s impossible for someone to tamper with information recorded on the Blockchain because they would have to change every record across each block on the network.

The future of Blockchain in logistics management is bright. Blockchain technology may change a lot of supply chains across all industries in ways unimaginable today. Blockchain increases the transparency and trust among logistics managers, suppliers, and customers. 

Discover Supply chain Management course with Imarticus Learning.

The logistics and supply chain management course offers an experience beyond just classroom learning – our partnerships allow candidates interested in entering this hands-on field training from some of today’s top professionals!

Supply Chain Analytics is the key to making data-driven strategic, operational, and tactical decisions. 

Course Benefits For Learners:

  • We prepare students for a rewarding career in Supply Chain Management and Analytics by immersing themselves in in-demand tools and projects, including six real-world projects that will provide them with a thorough understanding of the sector. 

     

  • Supply chain management online course prepares students for competitive jobs such as Demand Planner or Data Scientist, which employers today have in high demand! 
  • By utilizing the power of Python, this course will help students become more data-centric and enhance Supply Chain decision-making.

Understanding regularization in machine learning

Posted on by Imarticus Learning

A machine learning model is a set of algorithm expressions that understands and analyses mounds of data to make predictions. Why is it that sometimes a machine learning model does great on training data but not so well on unseen data? It happens because, at times, this model becomes an overfitted model or even an under-fitted one.

Data fitting is very crucial for the success of this model. In this model, we plot a series of data points and draw the best line towards the relationship between the variables. 

This model becomes an overfitting one when it gathers the details with the noise present in the data and tries to fit them on the curve. 

The underfitting model neither learns the relationship between variables nor classifies a new data point. At Imarticus, we help you learn machine learning with python so that you can avoid unnecessary noise patterns and random data points. This program makes you an Analytics so you can prepare an optimal model. 

Meaning and Function of Regularization in Machine Learning

When a model becomes overfitted or under fitted, it fails to solve its purpose. Therefore, at Imarticus, we teach you the most crucial technique of optimal machine learning. In this program, we coach you to become an Analytics by learning the procedures to add additional information to the existing model. 

In the regularisation technique, you increase the model’s flexibility by keeping the same number of variables but at the same time reducing the magnitude of independent variables. This technique gives flexibility to the model and also maintains its generalization.

Regularization Techniques

The regularization techniques prevent machine learning algorithms from overfitting. It is possible to avoid overfitting in the existing model by adding a penalizing term in the cost function that gives a higher penalty to the complex curves. Regularization reduces the model variance without any substantial increase in bias. Python classes also help in this technique.

To become an Analytics, you have to understand these two main types of regularizations:

  • Ridge Regression
  • Lasso Regression

Ridge Regression:

In this type of regularization, we introduce a small amount of Ridge regression penalty bias for a better long-term prediction. It solves the problems when the parameters are more than the samples. It decreases the complexity of the model without reducing the number of variables. Though this regression will shrink the coefficients to the least dominant predictors, it will never make them zero.

Lasso Regression:

In this regularization technique, we reduce the complexity of the model. The penalty weight includes the absolute weight in the Least Absolute and Selection Operator. The coefficient estimate equals zero, and it provides the feature selection. 

But, if predictors are more than the data points, this model will pick non-zero predictors. This model also selects the highly collinear variables randomly. 

Data Analytics Certification 

The certification in AIML will train you as an Analytics. It will help you understand how regularization works. After completing the certification program at Imarticus, you will know to shrink or regularise the estimates to zero. You can also enhance the model that can accurately calculate the data.

Why Senior Leaders Must Take Lead For Cybersecurity Across Businesses?

Posted on by Imarticus Learning

With the increase in technological advancement, being up to date with all the trends in technology is important for businesses to stay in the fast-paced race of today’s market. Along with upgrading systems, businesses need to pay very careful attention to their cyberspace which means enhancing cybersecurity.

Cybersecurity is extremely important to protect vital information and assets belonging to a particular business. This would require company leaders and senior executives to strategize and protect the company from the now frequently happening data breaches as well as cyber-attacks.

Cybersecurity Training CourseIn order to drive more informed investing procedures and resourcing methods along with increased efficiency and resilience, it is looked on to senior company officials to make good strategic decisions and protect the company from any threats. When we say senior executives it includes C-suite officials as well as policy-makers.

It is not a secret anymore but a well-known fact that in the digital frame that the world is functioning in today, cybersecurity should be among the top priorities for any and all businesses. However, a number of issues of both organizational as well as structural nature pose as obstacles for the establishment of cybersecurity models that are driven by business and that focus on risk management.

Hence, only a continued support shown by officials in the upper and top management positions of any organization would allow the decrease in cyber risks and increase in progress and growth.

What Would Incorporating Cybersecurity Mean for Senior Leaders?

In every organization or company, there are people at the top that are held accountable for making important decisions which would set the course and direction for the company to follow in. Their duties also involve holding ground on priorities, maintaining and influencing the company as well as preventing risks. They are thus basically responsible for the healthy functioning of the organization, company, business or establishment.

As mentioned above cybersecurity, in this fast-changing and fast-moving business environment, is the main concern for all organizations. Thus decisions taken regarding cybersecurity are left to the decision-makers of the company. Their duties now would include:

● Managing and decreasing cyber-related risks to the business while setting up effective methods of governance
● Making cybersecurity programs a priority and focusing on resourcing
● Managing and protecting vital information that holds the business together when it comes to planning
● Encouraging cybersecurity from within

This is all very important in order to promote organizational growth through the protection of digital assets and delicate data information. Executives at the top thus need to gain a better understanding of cybersecurity and this can be easily done through cybersecurity training which would help them understand what exactly can be a risk to their organization.

This understanding would in turn help in making rational decisions in a timely manner. It would also promote resourcefulness and strategic thinking.

A cybersecurity training course would thus also help further the artificial intelligence and machine learning career of aspirants by equipping them with all the necessary skills and information that they would need.

Supply chain management courses on the rise catalyzing blockchain to leverage potential

Posted on by Imarticus Learning

Implementing blockchain technology is a new and promising way to present opportunities to improve the supply chain and related management process of any company. Notably, blockchain is a distributed database that is specifically used for the electronic storage of information that cannot be changed or deleted.

In the supply chain, the implementation of blockchain technology indeed gives it an added boost in order to improve the traceability and transparency in the supply chain as well as to reduce unnecessary administrative costs. 

Blockchain has gained global popularity. Many startups and corporations are also considering venturing into the use of this technology outside the industry of financial services. An example is Provenance, which is a startup specializing in supply chain transparency and finished a 6-month pilot project for keeping a track of the reliable tuna sourcing in Indonesia through blockchain. 

How has blockchain been integrated into the supply chain management system?

Blockchain in the supply chain is still under the experimental stage. And so far, it has helped participants record important relevant information like price, location, certification, date, and quality to efficiently run the supply chain management system. The availability of such information within the blockchain system increases the traceability of the material in the supply chain and reduces the chance of losses. It further enhances the organization’s position as a leader in reliable manufacturing. 

Top blockchain in supply chain management courses online

Blockchain will most likely dominate the supply chain industry due to it streamlining the processes involved. This will create a demand for more blockchain developers in the supply management industry. If you are looking for some reliable courses, then here are a few:

Blockchain in supply chain management: In this course, you will learn the ways in which blockchain technology is being implemented in supply chain management to efficiently deliver secure and transparent supply chains. You will be given in-depth knowledge of what blockchain is and how it has been implemented in supply chain management (SCM). You will additionally get to explore actual business use cases where blockchain is applied in SCM. You will be taught the necessary steps for implementing blockchain in your supply chain. 

 

Certified supply chain professional and blockchain training: Blockchain is a disruptive technology that has been deployed in a multitude of domains to optimize countless processes. Since there is a rising demand for blockchain professionals in the supply chain industry, a special certification is a proof that you are more competent and are sure to have an advantage over others.

This course is designed to guide anyone in creating solutions that can have an impact in every possible facet of the supply chain. It is professional training that deals with providing you with the necessary knowledge of how blockchain can be utilized for increasing revenue, decreasing costs, and improving other factors like quality and production.

 

Needless to say, there is a rising demand for blockchain developers and experts. And in the coming years, it has the potential to provide prospects to individuals just starting off. A supply chain management career is one of the best fields to venture into and is highly promising with a good amount of job satisfaction. Therefore, if you want a supply chain certification to kickstart your career in the domain, then you can opt for a good supply chain analytics course.

Adopting a data-driven approach to supply chain certification courses

Posted on by Imarticus Learning

Supply chain analytics is an integral part of SCM (supply chain management) which is entirely data-driven. It primarily depends on gaining insights and values from the huge amounts of data related to various supply chains management elements like procurement, processing, and distribution of commodities. 

Further, supply chain analytics is involved in the collection and compilation of relevant data from across various applications, third-party sources, infrastructure, and upcoming technologies. This improves the quality of tactical and strategic decision-making in supply chain management. You can get better at it by enrolling in a comprehensive supply chain certification course. 

Besides, supply chain analytics also aids in the synchronization of planning and execution by enhancing real-time visibility into these methods and the impact they have on customers. Increased visibility leads to the increase in flexibility in a supply chain network that eventually helps decision-makers to efficiently evaluate tradeoffs amongst customer service and the cost.

How is supply chain analytics related to supply chain management?

Supply chain analytics plays an integral part in supply chain management because it has the ability to think about and make data-driven decisions on the basis of the summary of trusted and relevant data. Since supply chains generate huge amounts of data, supply chain analytics decipher the data to make sense of it and uncover insights and patterns. This is how supply chain management is dependent on supply chain analysis. 

Courses related to supply chain analytics

We can already conclude that a supply chain cannot exist without supply chain analysis. If you are enthusiastic about supply chain management as well as data analysis, then here are some courses that will give you a better insight into the data-driven approach to supply chain management. 

Supply chain analytics certification: This course is meant for individuals who want to learn about how to integrate supply chain management with data analytics. It will help you discover, determine and solve problems in various sectors of a supply chain. Additionally, you will develop data analytics skills and learn how to use tools for improving supply chain performance.

 

Big data analysis and machine learning: This certification will give you added leverage as you will be taught how to use most of the data science tools and techniques that are in demand to make yourself ready for the job market. You will develop important and valuable skills in Python, data analytics, SQL, data visualization with Tableau, and machine learning.

Real industry problems with real industry projects: A business analyst’s role is to prescribe the ultimate solution to any problem and this analytics course emphasises teaching and building up this quality. This course will teach you how to take data and models and connect them to real-world scenarios requiring decision-making in the supply chain and other areas like finance, manufacturing, and human resource management.

Predictive analytics for demand forecasting: Data is the basic raw material that is highly dependent on predictive analysis for understanding it and effectively utilizing it. This specialization helps learners recognize the primary components of predictive analysis which include monitoring big data at any given moment.

It also teaches the importance of Tableau that provides particular views of minuscule events or connects information to the recent forecasts and trends in order to ensure efficient allocation of resources and improve effectiveness.

Supply chain management is a job role that also requires the efficient handling of large amounts of data sometimes. Professional certification in supply chain management or any top-tier supply chain certification will help in acquiring the necessary skills to fit the bill.

It ought to equip you with the knowledge and skillsets that you will require in your journey into supply chain management. You can opt for good courses offering certification in supply chain management online with Imarticus Learning.

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