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Category: Management

What is the purpose of a leadership program for supply chain professionals

Posted on by Imarticus Learning

A leadership program for supply chain professionals has been designed to provide opportunities to supply chain professionals to help them perform better and assume leadership positions for manufacturing and logistics businesses. It impacts a supply chain executive or manager positively and equips him/her with technical, functional and leadership skills to handle a variety of roles within the two industries mentioned above. The program’s purpose is to accelerate talent early on to help the business and provide career growth to the professional.

Purpose and significance of online leadership program for supply chain professionals

A leadership program will help you to develop the skills mentioned above in the following domains of the supply chain industry:  

  • Manufacturing
  • Purchasing
  • Warehousing
  • Inventory management
  • Demand planning
  • Transportation
  • Customer service

Supply chain management consists of complex organisational operations and it affects the full spectrum of business and helps create and develop industry-based products and services. When the supply chain professionals are trained effectively in leadership, then the organisations benefit in areas like sales, production, distribution and marketing.

It helps you, as a professional, to gain an outlook on the industry from the perspective of senior personnel in management or as an owner of a company. During the program, you will understand how to optimise operations and how to take decisions to improve the business. After the leadership training is concluded, the operations become quicker and the chances of committing errors are reduced.

A leadership program for supply chain professionals also trains you in the following: 

  • Building an effective business development plan
  • Strengthening the core competencies of the organisation

Every business is experiencing the boon of globalisation, resulting in the rise of MNCs. This is why supply chain logistics management has become excessively complicated. Since the business is spread across different economies, there are different markets, labour laws, tax systems and import/export regulations. Therefore, managing a business’s supply chain network in an MNC is all about handling multiple departments, partnering organisations and personnel, and departments.

On the other hand, in smaller companies and startups, supply chain managerial leaders in a company can handle all the logistics operations by themselves or with a comparatively small team. However, leadership skills are still required to manage it efficiently.

Additionally, managing relationships is one of the core responsibilities of supply chain managerial leaders who need to execute operations successfully with the help of liaising. Supply chain leaders help in integrating management and logistics. They constantly analyse market trends and use the required information and all the sources of big data. Then they deliver the decisions after the perusal of this data. This helps the organisation to scale up and grow.

These are some core reasons why business leadership skills are critical for candidates enrolled in the best supply chain management courses.    

Imarticus Learning offers the best online program for supply chain management leadership

Imarticus Learning offers a professional certification in supply chain management and analytics. This professional certification program provides the best supply chain management and analytics program, which helps a candidate develop top-notch leadership skills. The course has been designed jointly by CEC and IIT Roorkee. The faculty comprises industry leaders who provide students with a cutting-edge academic experience.

The analytics in the supply chain enables supply chain managers to make data-driven decisions at every level of the chain. And, professionals who have such insights are in high demand.

Moreover, this certification prepares you for several job roles in the industry. Some of these roles are supply planner, supply and operations planner, demand planner and data scientist.

Some other exemplary features of the Imarticus Learning Supply Chain course

The chief supply chain and operations officers online training by Imarticus Learning has some good features. They are as mentioned below:

  • Learn job-relevant skills

You will get prepared for a highly successful career in supply chain and operation by getting to know modern-day skills, tools and training in real-world projects, which will give you relevant experience on the way the industry functions.

  • Get the valuable IIT tag

You will receive the IIT tag for your supply chain management (SCM) course. Your analytical skills will be top-notch because you are trained by the best faculty and have certification endorsed by the top-ranked institute, IIT Roorkee. You also get to learn from the IIT faculty through live online sessions and discussions.

  • Receive mentoring from industry experts

The best thing about this course is that you get 1:1 mentoring sessions from industry proponents in supply chain management.

Parting thoughts

We have enlisted here all the benefits of chief supply chain and operations officers online training. If you want to know more about the course, then please feel free to contact Imarticus Learning.

The Ultimate Cheat Sheet On Data Analysis With Tableau

Posted on by Imarticus Learning

Tableau is one of the best data visualization tools out there. It’s flexible and easy to use, and it comes with a ton of built-in functions and features that make it very powerful.

best big data analytics course

Tableau is a popular data visualization tool that can be used to analyze and present data. It is used by people from all walks of life, from social media managers to data scientists, to create visually appealing and informative reports. It allows you to easily create dashboards for visual analysis, which you can use to share your findings with others in your organization. 

Data visualization with Tableau has three main components:

Data Connections

These allow you to connect Tableau to your data sources. Tableau supports connecting to the most popular databases and cloud storage providers like Google Sheets, Amazon Redshift, Azure SQL Database, etc.

Visualizations 

This is where you create charts, graphs, and other visualizations based on your data connections. You can also create calculated fields that give you additional flexibility when creating visualizations. For example, if you want a bar chart but don’t have enough data points to create multiple bars (for example), creating a calculated field will let you do just that!

Dashboards

Dashboards are collections of visualizations that provide insights into key performance indicators (KPI). They can also include filters that limit what data is displayed.

Types of charts

Line Chart

A line chart is a great way of tracking trends over time. A line chart will be your best option if you have data that changes slowly over time (like sales numbers). Line charts can also be used to compare two sets of data over time. The lines themselves typically connect points that fall on the same date, making it easy to see changes over time.

Bar Chart

Bar charts are similar to line charts, but they show more than one variable at once—for example, showing sales by brand and product category. Bar charts are also good for comparing multiple sets of data at once. Suppose you have a list of items in different categories. In that case, using a bar chart will let you compare them side-by-side on one visual element instead of having separate visuals for each category or variable.

Scatter Chart

A scatter chart is a great option for comparing two different variables. It’s also a good choice when you have a large number of data points or when the data is fairly sparse, and you want to see clusters or trends in the data.  

A scatter plot has two axes: one for the x-coordinate and the other for the y-coordinate. The x-axis represents time or some other variable, while the y-axis represents other variables like revenue or profit. The values on both axes are usually represented by numbers or words as opposed to lines or shapes (such as bars). 

Scatter plots are useful because they allow you to see whether there is any correlation at all between your variables. They also allow you to see if there’s any pattern in how these variables change over time (this will be more apparent when multiple points are plotted on your scatter plot).

Combined Axis Chart

A combined axis chart is a useful tool for comparing two variables at once. It allows you to look at the values of both the variables on one graph with different scales for each axis. You can also use this type of chart to compare multiple sets of data (such as regions). 

A combined axis scatter chart combines both axes into one axis, allowing you to visualize three variables at once. It’s useful when you want to compare multiple variables over time or across different categories—for example, comparing sales by the department overtime or comparing sales by category in different markets.

Tree Chart

A tree chart is a good choice when you want to show hierarchical data, such as a company’s organizational structure or product line structure. Tree charts are also useful if your data set has multiple levels within each category, such as the different levels in an organization’s hierarchy or the different tiers of products produced by an organization.

Stacked Bar Chart 

Stacked bar charts are ideal for displaying how two factors interact with one another—for example, how much more money someone makes if they have a college degree compared with those who don’t have one. Stacked bar charts can also be used to show percentages or proportions over time. 

Imarticus learning understands the need of the hour and has curated a tableau certification course that covers all the industry-standard methodologies. Get in touch with us through our chat support, or drive to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Gurgaon and Delhi for tableau courses and tableau certification related queries.

Career Upskilling: How to learn data mining with python

Posted on by Imarticus Learning

With the introduction of an ever-growing need for businesses to gain intelligence about their competitors and customers, the field of data mining has been the next big thing. Data mining has proved itself a valuable tool that can get used in almost every industry. Data mining is fast becoming a buzzword in many industries, from real estate and marketing to finance. This post will show you how to teach yourself the basics of Python data mining.

Introduction to Data Mining with Python

Data mining is discovering patterns and knowledge from large amounts of data. It involves using statistics, machine learning, and artificial intelligence techniques to extract insights and make predictions from data.

Python is a popular programming language for data mining because it has many frameworks and libraries that make it easy to perform complex data analysis tasks. To start data mining in Python, you must have a basic understanding of programming concepts and some experience with the Python language. 

Prerequisites for Learning Data Mining with Python

To learn data mining with Python, you should have a basic knowledge of the following concepts:

  • Programming: Data mining requires a good understanding of programming concepts such as variables, data types, loops, and functions. Python is relatively easy to learn for beginners, but some experience with programming is necessary.
  • Statistics: Data mining involves analyzing large amounts of data, so a basic understanding of statistics is essential. You should know the mean, median, standard deviation, probability, and hypothesis testing.
  • Linear Algebra: Some data mining techniques, such as principal component analysis, require a basic understanding of linear algebra.
  • Machine Learning: Data mining is a branch of machine learning, so it’s helpful to have a good understanding of machine learning concepts such as supervised and unsupervised learning, decision trees, and neural networks.
  • Python: Familiarity with the Python programming language is necessary as all the libraries used in data mining are in Python.

How to Get Started Learning Data Mining with Python?

To get started learning data mining with Python, you can follow these steps:

  • Learn the basics of Python programming: If you are new to Python, start by learning the language basics. You can find many resources online, such as tutorials and documentation, to help you get started.
  • Review the basics of statistics and linear algebra: You’ll need a solid understanding of statistics and linear algebra to succeed in this career. You can find many online resources, such as tutorials, videos, and books, to help refresh your knowledge.
  • Learn about machine learning: Familiarize yourself with machine learning concepts and algorithms since data mining is a branch of machine learning.
  • Learn about the Python data mining libraries: Learn about the most popular Python libraries for data mining, such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, and Keras.
  • Get a dataset to work with: Find a dataset you can work with and start applying the concepts and techniques you’ve learned to analyze it.
  • Start with basic data mining techniques: Begin with simple data mining techniques such as data cleaning, feature extraction, and basic modeling.
  • Progress to more advanced techniques: As you gain more experience, you can move on to more advanced data mining techniques such as deep learning and ensemble methods.
  • Practice and Experiment: Try out different algorithms and techniques with different datasets to better understand.
  • Keep learning and stay up-to-date: The field of data mining is constantly evolving, so it’s crucial to stay up-to-date with new techniques, algorithms, and tools.

Learn Data Science and machine learning with Imarticus Learning. 

Want to take your machine-learning skills to the next level? The IIT Roorkee Certificate Program in Data Science and Machine Learning is here!

Start your journey with IIT Roorkee’s iHUB Divya Sampark! Our acclaimed faculty members will help you build on the fundamentals while teaching key concepts like mining tools and how to use insights that drive real-world solutions through Python programming. 

Course Benefits For Learners:

  • Learn from acclaimed IIT faculty in this machine learning certification course, and get a unique insight into India’s vibrant industry. 
  • Our data scientist careers will give you the edge you need to advance your career in the data science industry.
  • Learn the fundamentals of Artificial Intelligence, Data Science, and Machine Learning to develop skills that impact today and the future.
  • Give yourself a career advantage with our data science online training – where you will gain an understanding of cutting-edge technology that will open up extraordinary opportunities.

Importance of sales and operations planning for businesses

Posted on by Imarticus Learning

Sales and operations planning (S&OP) is a critical process for businesses of all sizes and industries. It involves aligning sales and production activities to ensure that the organization can meet customer demand while maintaining operational efficiency. S&OP helps businesses achieve their goals and provides a framework for making informed decisions and addressing challenges as they arise. 

In this blog, we will delve into the importance of S&OP for businesses, discussing its benefits and the key components that make it effective. Whether you are a small startup or a multinational corporation, understanding the role of S&OP can help you optimize your operations and drive success.

What is Sales and Operations Planning?

Sales and Operations Planning (S&OP) is the glue that holds a business together, seamlessly linking its sales, marketing, and operational efforts to drive success. It aligns an organization’s sales and production goals with its operational capabilities, ensuring customer demand is met while maximizing efficiency and profitability. 

Supply Chain analytics course

Think of S&OP as a high-level strategic roadmap that helps businesses make informed decisions, adjust to changes, and overcome challenges. With S&OP, companies can take control of their operations, align their teams, and drive growth in a coordinated and effective manner. Whether in manufacturing, retail, or any other industry, S&OP is an essential tool for success. Embrace this powerful process and watch your organization soar! 

Benefits of Sales and Operation Planning in Supply Chain

Sales and Operations Planning (S&OP) offers numerous benefits to businesses of all sizes and industries. 

Some of the most significant advantages include the following:

  • Improved alignment: S&OP helps bring all departments of an organization together, ensuring that everyone is working towards the same goals and using the same information.
  • Better decision-making: S&OP provides a comprehensive view of the business, allowing decision-makers to make informed choices based on accurate data.
  • Increased efficiency: By aligning production with sales demand, S&OP helps businesses avoid overproduction or stockouts, improving operational efficiency.
  • Better forecasting: S&OP helps businesses create more accurate demand forecasts, reducing the risk of stock shortages or excess inventory.
  • Enhanced profitability: S&OP can lead to significant cost savings and increased profits by optimizing operations, reducing waste, and avoiding stockouts.
  • Improved customer satisfaction: S&OP helps businesses build a positive reputation and retain customers by ensuring that products are available when customers want them.

S&OP provides a strong set of advantages that, taken together, can aid businesses in achieving their objectives and fostering success. Adopt S&OP and enjoy the benefits immediately if you want to advance your company.

Common Challenges in Implementing Sales and Operations Planning

Implementing Sales and Operations Planning (S&OP) is a complex process that requires planning and execution. 

Some common challenges in implementing S&OP include:

  • Resistance to change: Getting buy-in from all departments and team members can be challenging, especially if they resist change.
  • Lack of data quality: S&OP relies on accurate and up-to-date data, so ensuring the quality of this data can be a challenge.
  • Inadequate technology: S&OP requires a robust and flexible technology platform, so upgrading or implementing new systems can take time and effort.
  • Difficulty in aligning teams: S&OP requires close collaboration between sales, marketing, and operations, so aligning these teams can be challenging.
  • Difficulty in forecasting: Accurately forecasting demand can be challenging, especially if there is limited historical data or significant market volatility.
  • Resistance to cross-functional collaboration: S&OP requires cross-functional collaboration, so getting different departments to work together can take time and effort.

Despite these challenges, implementing S&OP can lead to significant benefits, including improved alignment, better decision-making, and increased efficiency. It is crucial to involve all stakeholders, create a clear plan, and choose the right technology and resources to overcome these challenges. With the right approach, businesses can successfully implement S&OP and achieve their goals.

Explore the IIT Roorkee supply chain management course with Imarticus Learning.

Professionals looking to maximize their expertise in Supply Chain And Logistics Management should consider certification to equip leaders with the necessary tools to drive tactical, operational, and strategic decisions. 

 Course Benefits For Learners:

  • By fusing a traditional supply chain management course with analytics, you can get ready to help develop more innovative and tactical global supply chains.
  • With the help of IIT’s supply chain program, you can advance your career and become a supply chain analyst. Utilize this chance to start your career as a data scientist!
  • Students who study Python develop a data-centric mindset, which will improve their decision-making in the supply chain.

Boost your employability with an IIT artificial intelligence and machine learning course

Posted on by Imarticus Learning

The world of work is changing. Many tasks that humans previously performed are now being carried out by machines thanks to the development of artificial intelligence (AI) and machine learning (ML).

This presents both a challenge and an opportunity for workers around the world. Those who can learn the skills needed to work with AI and ML will be in high demand. If you want to boost your employability in today’s economy, consider enrolling in an IIT artificial intelligence and machine learning course!

Artificial Intelligence and Machine Learning

It is an interdisciplinary field that is increasing. Thus, there is a great demand for experts in this field. The promise of real human-to-machine communication is one of the benefits of artificial intelligence (AI). When machines become intelligent, they can comprehend requests, link information, and reach conclusions.

IITs are India’s premier engineering institutes and offer some of the best courses in AI and ML. An IIT course will help you develop the skills needed to become an expert in this field. IITs offer a variety of courses in AI and ML, ranging from introductory courses to advanced research programs. No matter your level of expertise, there is an IIT course that is right for you.

How can an IIT artificial intelligence and machine learning course boost your employability?

 

If you’re looking to boost your employability, an IIT AI and machine learning course could be the perfect solution.

Here will discuss why:

#01. Machine learning is an in-demand skill

Machine learning is the hottest skill in today’s job market. Employers are increasingly looking for candidates with machine learning skills, and the demand for these skills will only continue to grow.

#02. Stay Ahead of the Competition

IITs are at the forefront of machine learning research and development. You’ll get access to the latest and greatest machine learning technology by taking a course at one of these institutes.

This will give you a leg up on the competition and make you more attractive to potential employers.

#03. Get Hands-on Training

When you take an IIT course in machine learning, you’ll get access to some of the best instructors in the world. 

If you’re looking to boost your employability, then an IIT course in machine learning is a great way to do it. With the help of these courses, you can stay ahead of the competition, get hands-on training, and make yourself more attractive to potential employers.

Discover IIT artificial intelligence and machine learning course with Imarticus Learning.

Enroll in the machine learning and artificial intelligence course program at the E & ICT Academy to learn about machine learning online training.

 Course Benefits For Learners:

  • Students work on 25 real-world projects to develop real-world business experience and prepare for a rewarding data science career.
  • With a certificate recognized by the E & ICT Academy, IIT Guwahati, and a credential supported by Imarticus Learning, students can attract employers’ attention and demonstrate their skills.
  • Students who complete this IIT AI course can land lucrative jobs in the machine learning and artificial intelligence sectors.

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

How much time will it take to learn data analysis with Tableau?

Posted on by Imarticus Learning

Data Science and Analysis are among the most highly-demanded branches of computational advancement. It wouldn’t be wrong to say that these fields are driving most of the progress we have seen in recent times. 

If data has been referred to as the new oil, then data science and analysis are the oil rigs pumping oil 24x7x365 and driving the world towards a better tomorrow. However, if you want to learn data science or analysis today, you must also know Tableau. 

But is Tableau easy? How much time will it take to learn data analysis with Tableau? Let’s find out.

What is Tableau, and what is its significance in Data Science and Analysis?

Tableau is one of the inevitable courses in Data science and analysis. Many data science and analysis aspirants wish to learn Tableau but often have misconceptions. They think learning Tableau requires technical training of some sort. So the learning curve might be steep. 

But there is no truth to this. Tableau is not technical at all. Its difficulty level might be equal to that of Excel. You need two to six months at the most to master it.

Basic Tableau is not difficult at all. First of all, let us bust one myth. You don’t require any background in computer programming to master it. Although data analysis might require you to learn a bit of Python, that’s all it is. Tableau does not require you to learn any programming language whatsoever. 

It helps you to represent the data pictorially. Grasping Tableau requires you to understand how its interface works. Once you figure that out, you are good to go. If you have some basic understanding or have used it beforehand, you might also get a head start and complete the course easily. Only three months are required at maximum to master it.

However, starting from scratch, you might need to understand the basics and all the stuff you see on Tableau’s UI. Then you might need six months to learn every bit of the data visualisation tool.

As already mentioned above, Tableau helps us to visualise data. You need to feed in data as a CSV sheet, and you will be able to get a visual output out of it. This way, you can understand what all perspectives can be generated from the data. 

Using these data visualisations, you can make precise solutions driven by the data. There are also some elements of business intelligence along with analytical tools. Tableau has mind-blowing software that can convert raw data into a dashboard you can access. 

Data gets simpler after depicting it visually, and it is then human professionals interpret. They better understand the KPIs (key performance indicators) and provide a better solution to a problem. Those opting for a PG in Data Analytics must choose a course that teaches them Tableau.

The other advantages are that Tableau performs the data analysis extremely quickly, almost in real-time. Visualising data is also stunning, making you easily understand all the data projections and statistics. It eases the understanding process for data analysts and other professionals. Since Tableau doesn’t require any technical background, the data visualisation can be understood by every person in the company, regardless of their professional background.

Other great features of Tableau provide a great advantage to Data analysts as they get more power in their hands. You get options like data blending, which allows you to display data from other sources and perform a comparative analysis. With the help of the data blending feature, you can find out how well you perform against your competitors.

Then there is a collaborative feature of Tableau. You can use a collaboration kit to use the data for reference and comment on it. Since Tableau does not allow and save work in one workbook, you might have to use several collaborators to make the data interactive and more useful for comprehension.

Tableau also allows users to manipulate live data sets. This way, a data analyst can save time on data wrangling and extract much information from the given dataset. The output generated from the raw data is more accessible and understandable. So Tableau is a useful tool for data scientists and analysts.

So, to become a data analyst, you must learn and master Tableau. You must also check whether this is a Data analytics course with placement. Doing a job is the best way to master a skill. But it is going to take some time. That is why you need to enrol in the PG Data Analytics course offered by Imarticus, where everything mentioned above will be taken care of. So, don’t wait; enrol now. 

Frequently Asked Questions

What do you mean by data analytics with tableau?

Tableau is a comprehensive data analytics platform designed for the entire data workflow. Tableau facilitates a seamless process from data preparation and analysis to collaborative efforts and sharing insights. Its strength lies in empowering users with self-service visual analysis capabilities. It enables them to pose new inquiries about well-governed big data and effortlessly disseminate their discoveries throughout the organisation.

What is tableau used for?

Tableau serves as a versatile platform, enabling users to craft a variety of visual elements such as charts, graphs, maps, dashboards, and stories for visualising and analysing data. This functionality is instrumental in aiding business decision-making processes. Renowned for its distinctive and compelling features, Tableau has emerged as a leading tool in business intelligence (BI).

Data analytics is a high paying job?

Indeed, data analysts typically receive competitive compensation. Over the past decade, salaries for data analyst roles have notably increased and remain attractive in today’s job market. As of early 2024, Zippia reports that the average annual salary for a data analyst in the U.S. is approximately $74,000, reflecting the ongoing demand and favourable remuneration for professionals in this field.

Learning Analytics? Discover The Value Of Learning Analytics With A Supply Chain Management Course

Posted on by Imarticus Learning

Supply Chain Management courses are one of the most important aspects of learning about business. They teach you how to manage resources effectively and keep your business running smoothly. 

From 2020 to 2030, the global supply chain market can grow at a CAGR of 10.7%. Accordingly, the market will be worth $52632.37 million by 2030 instead of $18699.45 million in 2020. 

However, did you know that Learning Analytics can help unlock even more benefits from your course? This blog post will discuss the value of Learning Analytics and how it can help improve your Supply Chain Management education!

What is Learning Analytics?

Learning Analytics is a term used to describe collecting, managing, and analyzing data related to student achievement and learning. It helps educators identify student performance patterns over time and adjust accordingly.

 

With Learning Analytics, researchers can unlock a new world of possibilities for understanding teaching and learning. Data infrastructures now allow us to provide learners with instant knowledge through tailored feedback that helps drive better performance – enriching their experience beyond measure. 

At the same time, educators gain invaluable insights that are only possible once persistent data is available regarding instruction methods for individual student progress. 

In short, this innovative field offers powerful advantages no matter where you stand on the educational spectrum!

Why is learning analytics valuable for your supply chain?

The use of learning analytics can be precious for a company’s supply chain. By tracking and analyzing the data associated with how employees learn and use new information, businesses can identify areas where they can improve the flow of knowledge and information within the organization. 

Additionally, analysts can help determine which employees may need additional training to keep up with the latest changes in the field. Learning analytics can help make a company’s supply chain more efficient and effective.

The Value Of Learning Analytics With A Supply Chain Management Course:

  • Improved Knowledge Retention:

Learning analytics can help improve knowledge retention by identifying employees struggling to learn and retain new information. Organizations can develop specialized training programs in this way to guarantee that everyone is aware of new procedures and is on the same page.

  • Improved Performance:

Learning analytics can also help improve employees’ performance and ability to handle new tasks. By tracking students’ progress in a course, analysts can identify which areas need more attention or additional training for tremendous success.

  • Streamline Processes:

You can also use analytics to help streamline processes within the organization by identifying how employees are utilizing new information and applying the knowledge. This can help to improve efficiency by eliminating redundant or unnecessary steps from processes.

  • Improved Decision-Making:

Learning analytics can also provide organizations with valuable insights regarding decision-making. Supply chain managers can better understand how their decisions could affect business operations by uncovering patterns in employee behavior.

By leveraging learning analytics, businesses can unlock a wealth of potential benefits for their Supply Chain Management course.

Learning analytics can be an invaluable tool for businesses looking to improve the effectiveness of their Supply Chain Management course. By leveraging data and insights from learning analytics, supply chain managers can better understand their processes and make more informed decisions about optimizing them. Supply Chain Management courses have the potential to unlock a wealth of value for organizations. 

Explore IIT Roorkee supply chain management course with Imarticus Learning

Professionals looking to maximize their expertise in Supply Chain And Logistics Management should consider certification to equip leaders with the tools they need to drive tactical, operational, and strategic decisions. 

Course Benefits For Learners:

  • Prepare yourself to contribute to creating more tactical and innovative global supply chains by integrating traditional supply chain management course with analytics.
  • Get ahead in the job market and become a Supply Chain Analyst with IIT’s supply chain program. Take advantage of this opportunity to launch your career as an expert Demand Planner or Data Scientist!
  • Python teaches students to be data-centric, which will help them make better supply chain decisions.

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

How Data Analyst course can help you enhance your data analysis skills

Posted on by Imarticus Learning

A data analyst is a role within the field of data science that is responsible for collecting, cleaning, organizing, and analyzing large amounts of data. They create reports and visualizations that help businesses make decisions based on the data and help organizations understand how to best use their data to maximize profits and efficiency.

However, a data analyst needs to be adept in data analysis skills, statistical expertise, data visualisation, and Python. A Data Analyst course can help you enhance your data analysis skills by providing you with a comprehensive overview of the fundamentals of data analysis. You will learn how to collect, manipulate, and analyze data, as well as how to manipulate, analyze, and present it. 

What if you have the ability to interpret data and communicate your findings to others? 

Let us get started!

Skills required to be a successful Data Analyst

Machine Learning- Having a working understanding of machine learning might help you stand out during the recruitment process.

According to Statista research, a lot of investment is now being made in artificial intelligence and predictive analytics. While some may specifically work on machine learning projects, being at least somewhat familiar with the related tools and ideas may give you an edge over others. 

Cleansing of Data– It’s one of the crucial steps in developing a machine-learning model is sorting the data received from various sources and completing it correctly. It typically consumes a significant amount of any Data Analyst’s day.

Given a clean dataset, even basic algorithms may generate surprising insights. On the other side, inadequate data might lead to misleading patterns and mislead a business. Practical data cleansing skills are a requirement for Data Analyst certification, hence there needs to be a way around this.

Information Display– Data visualisation is the ability to display data results using graphics or other images. This has a single, straightforward objective: It makes it simpler to understand data-driven insights, even for people who haven’t had professional training in data analysis. Data analysts may help decision-makers in a company who might not have advanced analytical abilities by using data visualisation to help them spot trends and rapidly understand complex ideas.

With this ability, the Data Analyst can better understand the state of the organisation, communicate insightful information with team leaders, and even positively affect corporate decision-making.

Communication skills and critical thinking abilities– When you think critically, you can analyse facts, identify trends, and derive useful information and concepts. You have to work harder and make a conscious decision to think and communicate effectively. You should be able to explain your findings to others. If you are unable to communicate the patterns you see to non-technical folks, you have failed.

You should be able to converse with your educated colleagues about highly technical subjects and give succinct, high-level explanations in a way that helps rather than confuses decision-makers who are business-focused. In that case, your skills are to be developed.

Programming in statistics– Statistical programming languages like R and Python enable you to do complicated studies in ways that Excel cannot. If you know how to write programmes in these languages, you can clean, analyse, and visualise large data sets more efficiently.

Learning at least one of the two open-source languages is a good idea. Some debate exists about whether language is best for data analysis. Either language may be used to fulfil comparable data science tasks. R was developed for analytics, although Python is the more popular of the two and often simpler to learn.

Best Data Analytics Course

The availability of data-driven and technologically based tools in today’s environment has made Data Analysts’ duties simple yet varied. They are now expected to possess knowledge of the software that may be used in their daily work to improve production and support the expansion of the business. 

Anyone who wishes to work in this field should choose the greatest curriculum that can raise their overall level. There are now many data analysis courses available to encourage students to enrol in certificate programmes, improve their skills, and position themselves as more marketable candidates for jobs in this field. Imarticus offers one of the top data analytics courses. 

Their PGA course Postgraduate Program in Data Science and Analytics provides a job interview guarantee along with building up the skills needed to be successful in this domain. It aims to strengthen the basic foundation of coding and programming skills like SQL, Python, and Excel. In case, you are looking for a well-rounded analytics course, this is the one for you!

Your data analytics course might come with a Job Interview but does it offer these things?

Posted on by Imarticus Learning

Technology has revolutionized the field of data analytics. Technology has drastically changed how businesses and individuals use data to make decisions, from collecting data to analysing it. As a result, companies have recognized that having access to accurate and timely insights is vital for success in today’s competitive market. This is why pursuing a career in data analytics in 2023 could be so beneficial – you will possess highly sought-after skills by many organizations.

Data analytics allows you to gain insight into customer behaviours and preferences, helping you identify patterns and trends that can inform strategy or increase profitability. You will also be able to create reports from large volumes of structured and unstructured data, enabling decision-makers within an organization to plan for the future.

Data analytics also provides a unique opportunity to develop skills that apply to various industries, such as healthcare, finance, and retail. You can become an invaluable asset to any organisation with the right combination of technical knowledge and business acumen. Plus, the demand for data analysts is increasing – the Bureau of Labor Statistics projects that job growth in the field will increase by 28% between 2019 and 2029. This means there will be plenty of opportunities available even five years from now

Considering all of these benefits, it’s no wonder why pursuing a career in data analytics in 2023 could be so lucrative. You’ll have access to cutting-edge technology, gain valuable industry experience, and receive a competitive salary. So if you’re looking for a career path that can take you far, data analytics may be the perfect fit.

What skills does a Data Analyst need to outshine in the field?

Data Analysts need a wide range of technical and analytical skills to be successful in the field. Technical skills include knowledge of statistical software packages such as SAS, SPSS and R, database management systems like Microsoft SQL Server or Oracle, programming languages such as Python or Java, and data visualization tools like Tableau.

Analytical skills are also key for Data Analysts. These involve interpreting data effectively, identifying trends and anomalies, developing logical conclusions from quantitative information, and communicating findings easily. In addition to being technically proficient, Data Analysts should have strong problem-solving abilities, be detail oriented and possess excellent communication skills to collaborate with other team members effectively. Finally, Data Analysts should be able to work independently, prioritize tasks and manage multiple projects simultaneously.

What do you learn during a Data Analytics course and training?

A data analytics course with job interview guarantee and training will introduce various data-driven concepts, techniques, and tools. These include descriptive statistics, hypothesis testing, predictive modelling, machine learning algorithms, big data analytics and visualization.

Students in data analyst training will learn how to use industry-standard software tools like Microsoft Excel and Tableau for cleaning, preparing, analysing and visualizing data. In addition to practical skills in collecting and working with large amounts of raw data from multiple sources, students should expect to understand the underlying theories behind decision-making, problem-solving and risk assessment using statistical analysis.

Finally, PG in Data Analytics typically covers the principles of effective presentation design so that you can effectively communicate your data-driven insights to stakeholders and project teams. With the skills from a data analytics course, you will be able to identify patterns in data and make informed decisions that improve businesses and organizations.

Learn and grow with Imarticus Learning:

Advance your career in data science and analytics with Imarticus Learning, now offering a job interview guarantee program. Our comprehensive curriculum is packed with applicable content to prepare you for success – from fundamentals through complex concepts, we have you covered! And even if it’s been a while since school or programming isn’t your thing – don’t worry; we’ve got an introductory foundation module to get everyone up to speed quickly so that no one will be left behind. Don’t hesitate any longer—take the plunge into this emerging field today and employ tangible skills that are sure to make a positive impact on businesses around the globe!

Course USPs:

  • Job Interview Guarantee
  • Job-specific Curriculum
  • Live Learning Module
  • Real World Projects
  • Dedicated Career Services
  • KPMG India OE Organised Hackathons

For further details, contact the Live Chat Support system or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Hyderabad, Delhi, Gurgaon, and Ahmedabad.

5 Simple Tips To Improving Your Career As a Data Scientist

Posted on by Imarticus Learning

In today’s world, most types of organised businesses use huge amounts of data to understand and analyse the needs or preferences of their prospective customers. This helps companies offer their existing clients a smooth experience with their products and services. Data science plays a vital role in this direction and provides businesses with the right tool for their activities. Notably, the number of people opting for a data scientist career these days is growing by leaps and bounds. 

Process and its Application in Business

The process of data science starts with the collection of raw data from several sources. Then, the data is prepared, i.e., filtered by eliminating unwanted content, as per the needs of the business. And then, analysis of the data starts followed by data modelling and later actual visualisation in the real system. Data science helps both online and offline businesses by capturing more and more recent data, which shall add value to the business in the long run. For example, an OTT platform service provider gathers real-time data on the choices and preferences of their clients to suggest to them the content they would be interested in. This means they help their clients get their choice’s content at their fingertips.  

This process is known as the recommendation process. The more inputs the service provider receives from a particular client, the more accurately the system may suggest him or her correct content. The better the recommendation mechanism of the service or a product, the better the satisfaction of the client. This is the reason why recently all organisations are following the process of client feedback for their products and services.

data science course

It is the job of data scientists to work out the available data and derive perfect algorithms for the system to kick-start artificial intelligence. Thus, machine learning comes hand in hand with data science and is an integral part of the total knowledge that a data scientist should possess. Considering this, the study of data science and machine learning courses in India is gaining momentum day by day.     

Tips to Improve Your Career as a Data Scientist 

The simple tips that will help to improve your career as a data scientist are as follows – 

  • Starting a career in data science is equivalent to breaking into software engineering for someone, who does not exactly have the same background but the basic intelligence, passion and skills to crack the processes. It may be safely mentioned that a candidate may be from any background i.e. science, humanities or commerce and may still pursue a career in data science. However, it may be noted that the candidate must possess good reasoning skills and a steady aptitude to learn quickly and efficiently.
  • Even a prospective candidate without prior programming language knowledge can be a very good data scientist in future provided the candidate follows the subject on the right platform. The candidate must enrol himself or herself in an eminent institute, having a huge experience in mentoring on the subject.
  • It may be noted in this context that though the study of data science involves enormous learning procedures, one should not be too much stuck in theory but rely on practice when he or she has completed the course. It is more of a practical or hands-on job and hence, preparing and running a model is more important than anything else.
  • A budding data scientist must have excellent mentors. We must remember that this is a newly evolving field and hence, getting oneself updated with the latest domain knowledge will be extremely helpful to one’s career. This is exactly where the role of good institutions comes to play.
  • The prospective candidate should choose the correct industry, in which the candidate has an inherent interest. It may be in SCM (supply chain management) or even finance. The course to be chosen should also be guided by keeping the basic interest of the candidate in mind. Good institutions have career counselling coaches who can understand the ability and interests of a particular candidate and may guide the candidate accordingly.

Conclusion 

A career as a data scientist is highly rewarding for a prospective candidate provided he/she has a grasp of the subject precisely and applies the knowledge in the industry domain according to his/her interest. The pay package of a data scientist depends on the skills and knowledge the candidate has mastered and the number of successful project models that have been delivered. The IIT Roorkee data science and machine learning course at Imarticus is an online training programme for five months. This course will guide you on how to become a successful data scientist and help you to achieve your dream. 

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