Contact Us
×

Category: Analytics

Analytics & Data Science Jobs in India 2022 — By AIM & Imarticus Learning

Posted on by Imarticus Learning

Analytics & Data Science Jobs in India 2022 — By AIM & Imarticus Learning

India’s booming data science sector is changing the scope of the Indian job market. As per the Analytics India Magazine and Imarticus Learning report, the number of open jobs in data science and data analytics grew by 30.1 per cent in April 2022.

India’s share in data science and analytics jobs worldwide has increased to 11.6 per cent from 9.4 per cent due to digital transformation across domains. 

Moreover, statistics show that the recent hiring numbers for data scientists, AI/ML engineers, and big data analytics indicate a maximum upward swing. Top data scientist open jobs fall under the salary range of 25 to 50 lakhs, making a career in data analytics more attractive.

Imarticus Learning and Analytics India Magazine have researched to provide more insight into India’s data science jobs landscape. The report has collected insights into the prevailing data science trends number of open jobs in the data science pre and post-pandemic. The sectors where data science and data analytics jobs are available, types of companies offering data science and machine learning jobs, and cities with vacancies for data scientists. 

Some key findings include required experience levels, educational backgrounds, data scientist salary, data analyst salary, and key data science roles. Statistics of the report will help the data science industry experts to know the trends of the sector, future opportunities, and how to select suitable candidates for the data science jobs.

The report is apt for recruiters, data science, and data analytics aspirants and stakeholders as it gives insights about open jobs in data science across cities, domains, and the salaries offered. Data science experts and companies can also get the required information from the research report. 

Let’s look at the latest data science and analytics trends

As per the AIM and Imarticus Learning report, India has seen a significant hike of 73.5 per cent of open jobs due to Covid-19 from March 2020 to April 2022. However, in the second wave in April – May 2021, data science and data analytics jobs have declined to 3.8 per cent. 

In the second week of February and April 2022, approx number of open jobs in data science and analytics is 180,468 and 179,470, respectively. In April 2022, renowned companies like Accenture, IBM India, Flipkart, JP Morgan, United Health Group, Wells Fargo, Capgemini, Dell International, eClerx Services, and Shell tops the chart in creating the maximum number of data analytics jobs.

AI/ML engineer, deep learning, big data analytics, statistician, data architect, NLP, data scientist, data engineer, computer vision, and data scientist profiles have the maximum number of openings. 

Here the question arises why does India’s share in the data science and analytics jobs increase?

  1. 32.5 per cent increased funding in analytics-based startups. Total financing in these startups is $1.1B, which is the reason for rising in the data scientist and data analytics jobs.
  2. Domestic companies hiked their investments in the data science and data analytics sector.
  3. Companies worldwide have moved their data and analytics work opportunities to India. KPO, BPO, and IT organizations top the charts here.
  4. Technology transformation in the captive centres also contributes to the rise the data science and analytics jobs.
  5. Attractive salaries in the field of data science and artificial intelligence

Data science job markets have touched new heights, and data scientist and analyst salaries have also seen an upward curve. The analytics jobs which fall under the salary bracket of 50 lakhs have increased to almost 20 times from 2021 to 2022.

The table below will explain the trend in data scientist and data analyst salaries.

Salary Range Jobs in 2021 Jobs in 2022
0 – 3 Lakhs 11722 18095
25 – 50 Lakhs 3585 18775
50 Lakhs 276 5472

The statistics above make the data scientist and data analyst career one of the most favourite jobs and the best career choice for the future.

Sector’s contribution to data science openings

Data is not something that you can ignore. On the contrary, it is critical in all the sectors. The new-age industries like retail and CPG contribute to the maximum number of data scientist and analyst jobs. The total number of jobs in these sectors in 2021 was 3,143, which rose to 2.5 times in 2022, making it 7,743.

BFSI jobs have seen an upward trend by increasing 19.9 per cents more jobs contribution. In addition, sectors like eCommerce and the internet, with 13,167 in 2022, also show a significant rise. Post covid, travel, and hospitality industries have come up with a 4.4 per cent share in the total number of advertised jobs in the data science and analytics sector. Our report excludes the contribution from the IT sector.

The table below will give a sneak peek into sector contributions to data science jobs.

 

Sectors Percentage  
Telecom 4.70%
BFSI 26.60%
eCommerce/Internet 18.80%
Energy & Utilities 15.20%
Retail & CPG 11%
Pharma & Healthcare 7.40%
Media & Entertainment 6.70%
Automobile 5.30%

Company type-wise share of data science jobs

Based on the AIM and Imarticus Learning report, MNC IT and KPO sectors are the highest data science and analytics job contributors with 139323 open jobs. However, the domestic firm has shown a remarkable increase of 336.4 per cent and a decline in domestic IT and KPO services providers with 4.7 per cent in 2022.

Top cities offering data science jobs

The top three cities offering data science and analyst jobs with better career opportunities are Bangalore with 28.5 per cent share, Hyderabad with 11 per cent, and Delhi NCR with a share of 19.1 per cent. These three cities saw a good hike in the data science and analytics position, but cities like Pune with 0.5pp, Chennai with 0.3pp, Kolkata with 0.1pp, and Ahemdabad with 0.4pp show a slight decrease in the available jobs.

Core IT hub of India, Bangalore, offered 38,474 in 2021 and 51,149 in 2022, showing a growth of 32.9 per cent. Delhi had open jobs of 34,200 in 2022 and 7,861  in 2021. Mumbai’s gain of 40.2 per cent with 23,591 jobs in 2022 places it in the third position.

Hyderabad rules the chart by showing a 42.9 per cent hike in the number of posted jobs for data scientists and analytics. 

 Experience level

Seven to ten years of experienced professionals are in demand in data science and analytics. 46.4 per cent growth rate is seen in the available jobs for 7-10 years of experienced data scientists and analytics profiles. Job share for 0-2 years and less than one year experienced declined to 11.5 per cent and 8.9 per cent respectively.

Desired education qualification

Engineering graduates and MBA graduates are the first choice of companies for data scientist and analytics jobs. That is why more engineers are opting for a career in data analytics. The engineers are familiar with technology giving them the edge over non-technical professionals. 

The table below will give more insights into the qualification preference of the companies for data science jobs.

Streams Jobs
Engineering 56000
Non-engineering UG 35200
Engineering PG 25900
MBAs 17400
Non-MBAs 14400
PhD 14000
Others 16500

Distributions of Data Science and Machine Learning Jobs

Data engineer profiles contribute to 1/4 of the total data science jobs in the market. AI-related jobs have the highest share of deep learning roles. Data engineers’ profiles are more in demand than data scientists due to the need for digital transformation.

The highest number of jobs in this data science and AI sector is the business analyst role, which is 38,974. There are about 34,566 jobs for data engineer roles, 19,457 for data scientist profiles, 10,564 for deep learning profiles, 10,564, and 2,214 for AI/ML engineer roles.

The enclosed report will give more insights to the stakeholders and aspirants who want to opt for a career in data science. For more details, you can access the research report done by Analytics India Magazine and Imarticus Learning. 

Tableau V/S Excel: Who Will Win?

Posted on by Imarticus Learning

 Tableau V/S Excel: Who Will Win?

The debate has been on for so long that no one remembers when and where it all began. But the question has always remained the same—is it better to use tools such as Excel or Tableau for analysis?

 Some people say that Tableau can easily beat Excel in anything. Some say the contrary side. Tableau and Excel are two practical tools for creating, developing, storing, and analyzing data. Businesses use both, but they have different features and functions. This post will look at some of the fundamental differences between Excel and Tableau.

The Basic Differences between Excel and Tableau

Excel is a 20-year-old software program that works with numbers. Tableau, in contrast, was explicitly designed for data analysis and visualization. The two programs also have different use cases; Excel works well when you perform calculations and generate reports based on your data, but it may not be as flexible as Tableau if you need to create interactive dashboards and narratives. Tableau allows users to drag-and-drop fields into visualizations, meaning they can customize their output much more quickly than Excel.

Why use Tableau when you can use Excel?

Excel is the most popular and influential application, especially when it comes to data visualization. Excel has been helping people create and analyze data for more than three decades now, making it one of Microsoft’s best products.

 But, despite Excel’s dominance in tech circles, there are many reasons people are starting to use Tableau instead, at least for specific tasks. Users say that their companies save about 30 percent on their monthly business intelligence costs using Tableau instead of Excel. 

Why use Excel instead of Tableau?

Tableau and Excel are currently two of your best options for data visualization software. Both of these programs have their unique benefits and drawbacks. Excel is one of Microsoft’s most popular tools because it’s free and works with all files (including PDFs, XMLs, and HTML files). You can use Excel for various purposes, like creating documents or analyzing numbers. 

However, using Excel on its own is not very efficient when creating beautiful infographics or advanced data visualizations. Instead, you need to use an add-on program like Adobe Illustrator or Microsoft Powerpoint, which requires more time and money for less sophisticated results.

Both have pros and cons in the ongoing war between Microsoft Excel and Tableau. Some say that Tableau has taken the tech world by storm with its easy-to-use functionality, while others believe that Excel still has a few tricks.

Learn data analytics online with Imarticus Learning

This placement assured tableau course will educate students on applying data science in the real world and creating complex models that produce crucial business insights and forecasts.

Course Benefits for Learners:

  • Learners should be familiar with data analytics, machine learning principles, and the most popular data science tools and approaches.
  • Students participate in 25 real-world projects and case studies conducted by corporate partners to obtain a tableau certification.
  • Data visualization with the tableau program is among the most in-demand abilities in today’s market, so recent graduates and early-career employees should consider enrolling.

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

The Advantages Of Having An Industry Certification In Supply Chain Management

Posted on by Imarticus Learning

 The Advantages Of Having An Industry Certification In Supply Chain Management

Firms are increasingly embracing analytical standards to improve their decision-making capabilities and supply chain efficiency due to the complexity and increase of supply chain operations as a result of globalization. To compete in a competitive market climate and increase quality, a company’s supply chain managers must respond to disruptions quickly and effectively. A well-functioning supply chain ensures timely fulfillment of goods and services when catering to ever-changing client demands.

Higher employee efficiency rates, lower prices, better profit margins, increased outputs, and so on are all advantages of supply chain management for the firm. As a result, firms are always on the lookout for people who have completed certifications in supply chain management and wish to pursue a supply chain management career. 

In this post, we’ll go over the benefits of getting an industry certification in supply chain management and one of the top supply chain management and analytics courses for a successful supply chain management career.

Advantages Of Completing An Industry-Certified Supply Chain Management Course

There are various advantages of completing an industry certification in supply chain management, a few of which have been listed below:

  1. International recognition

Top worldwide organizations and MNCs recognize a certification in supply chain management certified by industry experts and councils. It is easier to advance a supply chain management career and work for an international organization if certifications are recognized internationally.

  1. More job opportunities

Once the industry accepts the certification, it opens doors to various job roles in that field. In the case of supply chain management, you can easily apply to any of the following job roles:

  • Business Analyst
  • Planning Manager
  • Director of Logistics Management
  • Distribution Manager
  • Director of Supply Chain Management
  • Global Procurement Manager
  • Commodity Specialist
  • Purchase Head
  • Supply Chain Manager

  1. Better pay scale

Employees who complete additional supply chain certifications get more job opportunities and better pay. Most of the time, the salary of already working employees is increased after the certification. If the graduate is fresh, they have a better chance of getting a higher package than other selected candidates. According to Glassdoor, the average salary of a certified supply chain manager is around 12 lakh.

  1. Well-informed decisions

As the global supply chain gets increasingly complex, the requirement for well-researched judgments has become vital. An industry-certified supply chain management training can help you learn important topics and make better judgments. A well-informed decision will help the organization meet its objectives, such as enhanced profit margins, firm efficiency, and sales. Companies are continuously looking for people who have finished a certification in supply chain management and can see difficulties in decision-making and leveraging market data.

  1. Keep up with the newest market developments

You’ll learn to deal with newer market developments if you take an industry-specific supply chain management and analytics course. It’s a terrific chance to stay on top of supply chain developments and put them into practice. It’s also the perfect time to keep up with new technology in the industry and take the lead within your organization. You may keep a close eye on each new development and improve communication with vendors, consumers, and your company.

Professional Certification In Supply Chain Management & Analytics Course By IIT Roorkee

The Professional Certification in Supply Chain Management and Analytics is an industry-certified supply chain management program developed in collaboration with Imarticus Learning by IIT Roorkee, CEC, and industry professionals to provide individuals interested in pursuing a supply chain management career with cutting-edge experience and knowledge.

Supply chain management courseThe Professional Certification in Supply Chain Management and Analytics course helps professionals make more data-driven decisions at the operational, strategic, and tactical levels.

This industry-recognized program prepares you for high-demand supply chains management positions such as supply chains manager, procurement manager, and demand planner.

Following are the various highlights of the Professional Certification in Supply Chain Management and Analytics course by IIT Roorkee:

  • Students who complete the 6-month certification in supply chain management will be rewarded with a certification from IIT Roorkee.
  • It allows you to schedule one-on-one mentoring sessions with industry leaders and experts to clear all your doubts and questions related to this ever-growing industry.
  • The Professional Certification in Supply Chain Management and Analytics course is conducted online by IIT experienced faculty members and guest sessions by supply chain management experts.
  • It follows a rigorous industry-oriented curriculum that teaches students job-relevant topics and skills to secure a high-paying, in-demand job.

Conclusion

Supply chain management is a rapidly growing sector due to the epidemic’s disrupted supply chain and globalization. The Professional Certification in Supply Chain Management and Analytics course is a 6-month program that helps students keep up with the latest market trends, learn essential supply chain management skills from IIT Roorkee faculty, and participate in a 3-day campus visit to IIT Roorkee. It is industry certified and follows an industry-oriented curriculum, allowing you to work for any top organization.

Please contact us for any queries or visit any of our training campuses in Mumbai, Thane, Pune, Bengaluru, Delhi, Chennai, and Gurgaon. 

Intro To Tensorflow For Deep Learning Courses

Posted on by Imarticus Learning

Intro To Tensorflow For Deep Learning Courses

Deep learning uses artificial neural networks to teach computers how to learn from data. This approach differs from other types of machine learning – it is not just about finding patterns in data, but understanding the meaning behind those patterns.

Deep learning systems can be trained to perform image recognition, speech recognition, and text analysis tasks. They are increasingly being used for tasks such as automated driving, where they can help vehicles navigate safely through complex road conditions. 

The significance of deep learning is that it allows machines to learn without being explicitly programmed for every possible situation they may encounter. Deep learning is a subset of artificial intelligence (AI) that allows computers to learn without being explicitly programmed. It’s a powerful technology that has been used to develop computer vision, speech recognition, and natural language processing systems. 

Deep learning builds upon previous machine learning methods by using multiple layers of neural networks to learn patterns in data automatically. To achieve this, deep learning algorithms must be trained on a large volume of data with labeled examples. This will help them determine which features are relevant to making accurate predictions about the outcome. 

Deep learning has been around for about 30 years, but it has gained steam in recent years with the advent of tools like Google’s TensorFlow, an open-source framework for deep learning. Deep learning uses artificial neural networks, which are computer programs designed to mimic the way neurons in the brain fire and communicate with each other. The neural network can be trained using large sets of data, and once it has been trained, it can then be used to predict or classify new data.

Deep learning differs from traditional machine learning in that it allows computers to grasp new information by processing large amounts of data at once instead of using rules-based algorithms.

The significance of deep learning is hard to overstate. It’s already being applied in fields as diverse as medicine, transportation, and finance. It is expected to become more ubiquitous as researchers continue to figure out how it can be used to solve problems that have long proved difficult for humans alone.

Deep learning refers to algorithms that use one or more hidden layers of neurons between input data and output data. These algorithms are also known as “deep neural networks” (DNN). Deep learning has been very successful in some application areas, such as image recognition, speech recognition, natural language processing, and reinforcement learning. 

Now that we know what deep learning is, let us understand its implications with Tensorflow.

What is Tensorflow? 

TensorFlow is a library for machine learning and deep learning, providing a high-level API built on top of low-level routines that implement the actual neural network computations.

The high-level API allows us to express our model in a declarative style.

In TensorFlow, we can create models from scratch or use existing ones as building blocks. We can then train them with data, validate their behavior, and even deploy them to production seamlessly.

Tensorflow is open-source software developed by Google that implements the TensorFlow deep learning framework. Deep learning and TensorFlow are closely related because deep learning relies heavily on TensorFlow and its capabilities. Tensorflow was created to help developers build and train artificial neural networks that can learn how to identify objects or voices based on their visual characteristics or sound patterns.

The system is currently used in many of Google’s services, such as Google Translate and Google Photos. TensorFlow is also used by other companies, like Dropbox or Twitter.

It emphasizes automatic differentiation, which allows for defining complex models in a short time. TensorFlow supports CPU and GPU computation, making it a good choice for researchers who want to take advantage of the latest GPUs with CUDA support.

TensorFlow is a flexible and easy-to-use system that can run on a single computer or across multiple computers in a cluster. TensorFlow was originally developed to support distributed training of machine learning models, but it also has non-distributed applications such as data analysis and visualization.

So far, neural networks have proven very effective at solving problems in many fields, from computer vision and speech recognition to stock market predictions. Neural networks are designed to imitate how the human brain processes information and learns from the data we provide it.

To learn more about TensorFlow and its application in artificial intelligence and machine learning, enroll in the best course offered by Imarticus learning. Get the best course guidance and execution strategies to kickstart your data career. Contact us through chat support, or visit us at our offline stores in major cities across India.

Power up with a micro-credential in data analysis with a tableau course in 2022

Posted on by Imarticus Learning

Power up with a micro-credential in data analysis with a tableau course in 2022

Like W. Edwards Deming once said, “Without data, you’re just another person with an opinion.” Data is the future and the driving force of today. They say knowledge is power and data is knowledge. It is the information that reforms civilizations and fabricates unfathomable technology, propelling whoever uses the insights data extracts strategically into leading positions.

It is the fuel that is running the world today and building a scientifically maneuvered tomorrow. Data hold answers to the most complex disciplines and gives you the power to back your opinion with evidence-based analysis. In a world continually engaged in cutthroat competition, data is the only differentiator. The interpretation of data is a powerful instrument that steers every decision that is made today. 

What is data analysis?

Data analysis is a systematic approach governed by logical and statistical techniques that help in the extraction of insights via gathering, modeling, and inspecting data to pilot informed conclusions and factually accurate decisions. It helps you collect relevant information and identify the pain points to come up with viable solutions depending on your field of work. 

What is a micro-credential?

If you are someone who wants to upskill without devoting the time and cost it needs to commit to a full degree, then micro-credential is an option that will most definitely interest you. Devised to provide you with the resources be it theoretical or practical, micro-credentials cater to your specific requirements to advance your skills. Micro-credentials act as independent credentials adding to your academic merit. 

What is tableau

Tableau is an intuitive, visual analytics computerized program that helps in easing the process of analysis by converting big data into simpler and more accessible forms. It turns complex data into a smaller version that is easily comprehensible and gives accurate insights into the small data at the same time. 

With data at our fingertips, the influx of it has been high and businesses around the world need a system that is easier to operate while giving an interactive experience to the users. It has become instrumental in inspecting data all while giving a deep intuitive understanding of it. 

Why Tableau 

This visual tool has become an integral part of corporations and its easy-to-use design has propelled companies to expand their business using this software. Not only is it detail-oriented but also gives you an in-depth knowledge of the steps you need to take to augment your project. 

The success of corporations today depends on data visualization and examination. These prerequisites present your opportunities to practically apply your skills and create a promising career. As businesses expand, the inflow and need to explore and interpret larger numbers of data will increase. 

Tableau career prospects

Here are the diversified career options you can choose from after completing the course:

  • Data analyst
  • Business intelligence analyst
  • Tableau consultant
  • Business intelligence manager
  • Business analyst
  • Business intelligence developer

Why choose a micro-credential in data analysis with a tableau course 

From the complexities of linear regression to linear discriminant analysis, the tableau course covers all the essentials you need to transform you into an expert in this field. 

  • Higher employability – As the world advances, data has become the oil that drives the corporate world into expansion. The demand for analysts to collect, clean, model and inspect data to give viable solutions in tandem with their augmentation plans has become a necessity. The program comes with guaranteed job interviews  opportunities apart from transforming you into an adept data analyst. Certification in data analytics course also helps you in upskilling and venturing into your own line of innovation.

  • Job-relevant skills – The course familiarizes you with theoretical as well as practical knowledge that ensures you develop job-relevant skills. Mentored and guided by industry experts and professionals, you get to participate in real-world case studies and projects.

  • Extensive support – The course focuses on the development of every single individual enrolled in the program and assists them every step of the way from preparing them for placements, workshops, mock interviews, and providing expert career guidance. 

Conclusion

Our micro-credential in data analysis with a tableau course covers the crux of the topic as well as its complexities of it so that you can provide real-time solutions to clients and establish a successful career in this profession. As someone proficient in developing tableau and extracting detailed cognizance from it, you can aid businesses excel and creating futuristic solutions for corporate problems. 

Ace your career with a machine learning course with placement in 2022

Posted on by Imarticus Learning

Ace your career with a machine learning course with placement in 2022

Machine learning no longer remains an emerging field of AI, it has become a critical gear driving corporations across the globe now. Machine learning across all industries has become an indispensable prerequisite. With demand for machine learning increasing with each passing day, now would be the time for you to take into consideration a career in this field. 

Machine learning and data science

Machine learning in correlation to data science has been dominating the industry for a while now. So, how does machine learning help you? Machine learning dissects complex big data automatically. Machine learning automates the procedure of the exploration and inspection of data and is capable of predicting unforeseen data-backed judgments in real-time sans manual labor.

The data inserted is processed within seconds without the need for human involvement. Machine learning aids the fabrication of data models in a mechanized way and is further developed to formulate real-time predictions. This is how and why machine learning is an instrumental aspect of data science. 

Best way to learn machine learning

Machine learning can be complex but with the assistance of subject specialists and industry leaders, you can master the skills required to transform you into an ML expert. 

  • Leading-edge ML & AI Curriculum – Go for a course that is designed to provide you with relevant resources and a curriculum that makes you industry-ready. With an increase in demand for AI and ML professionals, opt for a course that will future-proof your career in this field. Your certification plays a significant role in endorsing your skills and having a world-class certification that is recognized globally is an asset you need to elevate your career. 
  • Campus immersion – As they say – your peers and teachers play a crucial role in molding and influencing you. Choose a course that helps you explore beyond the known and participate in opportunities that help you learn from an expert faculty and innovative peers. Having real-time interaction is an integral segment of mastering your practical skills. 
  • Participate in real-life scenarios – Indulge, explore, examine and analyze the problems ML and AI Engineers face while pursuing this job. Get a deeper understanding of real-world problems and learn how to address them by mastering job-relevant skills and the guidance of industry specialists. Get familiar with AI and ML integrated data science and acquire a critical competitive edge in the corporate world. 
  • A portfolio that stuns – Choosing a suitable course and specializing in the subject is the first step to success but the only way it will be etched in stone is if you have an impressive portfolio to validate your proficiency. Select a course that allows you to explore multiple relevant projects and work on them to gain real-time expertise. A supportive faculty that ensures that you get to handpick datasets best suited to your interests, lets you create an impressive GitHub project portfolio, and is an added advantage in enhancing your resume. 

Best Machine Learning certification 

The best Machine Learning certification is the one that gives you an insight into the real-world job scenario and provides you with cutting-edge resources to enable you to develop skills to your maximum potential, guided and mentored by industry leaders and subject experts. 

IMarticus’s certification in AI & ML has been designed to encourage the highest quality of learning outcome in collaboration with E&ICT Academy, IIT Guwahati. It is an extensive program spread across a tenure of 9 months and will help you boost your career in the fields of Data Science, Data Analyst, Machine Learning Engineering, and AI Engineering. This certification course has been specifically curated to enhance your rudimentary skills in AI and leverage them into carving a lucrative career for yourself. 

  • Real-world projects
  • Expert guidance
  • Diverse projects
  • Job relevant skills
  • Certification from E&ICT Academy
  • Flexible learning experience

Conclusion

Stand out of the crowd with an experience crafted to provide you with top-quality education standards and transform you into the most coveted AI & ML specialist. 

How SQL and Python are Changing the Future of Data

Posted on by Imarticus Learning

How SQL and Python are Changing the Future of Data

Introduction

Machine learning and AI may be making headlines, but did you know that the most critical talent in the data science sector is over half a century old! SQL has remained an essential data-processing language despite its age. It’s hard to believe that a language that has been around for five decades is still relevant in today’s fast-paced data science industry. 

SQL is not the only thriving aspect of data science. Python is another high-level programming language that is thriving in data science. Nobody likes unorganized, unfinished, enormous data just lying around. Python shines the brightest here as Python can easily manage this unorganized, unfinished data. If you are interested in honing your skills in this department, consider enrolling with Imarticus Learning programs, as it can propel your learning of Python for data science. 

How Python is changing the future of data

Python has a bright future as a large-scale, dependable, efficient, and ready-to-use technology. If you’re interested in data manipulation and visualization or machine learning and evaluation, this tool can do all of that and more. You can learn Python through various Python tutorials available on the internet. Imarticus Learning Programs is a major brand in the field of future technology-based professional education, devoted to sculpting the future workforce via innovative new age programs like Python for data science and analytics, artificial intelligence, and machine learning.

 Popularity of Python

The popularity of Python may be defined in a variety of ways. In addition to developers, Python is widely used for deployment management and web development, making it one of the most widely used computer languages in the world today. The Python language and its framework are also preferred by non-developers for data work when they first learn about it.

Python is becoming the first-choice programming language for prospective and current programmers who want to get “real employment.” Aside from online and mobile app development, the technology is also being utilized in data science. Python is extremely popular within the data science field. Since it is in high demand, you can find Python tutorials in Imarticus Learning Programs. Imarticus utilizes innovative technology and training methodologies to transmit information and a cutting-edge Learning Management System to merge online and live education.

Uses of Python

Python has a remarkable amount of adaptability. It is a versatile language that may be used for a variety of purposes. Data science’s ascent has led to Python is the number one programming language in the world. That brings us to AI. A language specifically designed for machine learning doesn’t exist, but Python’s strengths in this area make it the ideal option for most programmers who want to use ML. For Machine Learning, Python is one of the most widely used and finest languages.

 Python is unquestionable “the rage” these days. Python is a welcoming environment thanks to its widespread use and supportive community. It encourages developers to express themselves more concisely. Learning Python is quite simple, so you can get started right now. 

How SQL is changing the future of data

Before we jump to why SQL is the “rage” these days, let us understand what SQL is exactly. 

What is SQL?

An SQL query language is a specialized computer language intended to enable communication with databases. SQL is still used today for searching, updating, modifying, adding, and removing data in relational databases, even though it has changed quite a bit over the years. SQL is often used in conjunction with other computer languages, such as Python or R, in data science projects. SQL allows data scientists to extract specific data from an organization’s database. Using Python or R, users may then dig further into the data that their SQL query retrieved.

 What’s the point of learning SQL?

 The prevalence of SQL databases is undeniable.

 Most businesses depend significantly on their SQL databases. As a result, SQL abilities are expected to be in high demand for years to come.

 Nearly every job description that includes the word “data” calls for the use of SQL. SQL is the most commonly requested technical expertise for entry-level occupations such as data analysis (including Python, R, machine learning, and so on).

 SQL abilities (and some knowledge of spreadsheets) are sometimes the sole technical skills needed or assessed during the interview process for many data positions.

Conclusion 

Python and SQL have both taken data science by storm. The demand for these applications is not likely to stop anytime soon. If you are interested in learning Python or SQL, sign in for Imarticus Learning Programs. It is one of the best platforms for future data science experts out there. You can also contact us through chat support or drive to our training centers in Mumbai, Thane, Gurgaon, Pune, Chennai, Bengaluru, and Delhi. 

How An IIT-certified Supply Chain Management Course can jumpstart your career

Posted on by Imarticus Learning

How An IIT-certified Supply Chain Management Course can jumpstart your career

It’s the dream of millions of Indians to study at IIT and experience its legacy of excellence. Interestingly, today, one need not be an engineering graduate to do that. Innovation and technology have revolutionized almost every discipline, and one that is highly impacted is Supply Chain Management (SCM). By pursuing a cutting-edge online supply chain certification course offered by IIT Roorkee, ambitious professionals can build in-demand industry skills and fast-track their career growth to the next level. 

Evolution of the supply chain

The cloud has completely transformed the modern supply chain. The accelerated growth of eCommerce, higher consumer expectations, shift to data-driven decision-making, and challenges in procuring raw materials have collectively influenced how SCM is practiced. These shifts have led to a disproportionate jump in the number of SCM jobs available across sectors and to an expansion of roles across the industry. 

Today one can choose from an array of Supply Chain Management Careers. One can become a Supply Planning Analyst, Data Scientist, Demand Planner, Procurement Specialist, Data Analyst, Supply And Operations Planner,  Quality Assurance Manager, and Logistics Manager. 

Aspiring supply chain management professionals need to invest in training that empowers them to succeed in their chosen career path. 

Build the skills of the future 

A modern SCM course, backed by an IIT faculty, curriculum, and certification, equips professionals to build skills. They can also get a taste of hands-on learning as they work on real-world SCM projects. For example, understanding how to leverage analytics through technologies such as Python gives SCM professionals the tools to improve efficiency, apply real-time insights to their outcomes, and innovate the supply chain in line with their business goals. Data-centric professionals are more likely to make superior decisions and directly impact their work and the profitability of the business. 

An industry-focused program 

An industry-focused curriculum helps you get exposure to core SCM concepts. It also enables hands-on learning of SCM processes, tools, and techniques. You will get exposure to core subjects such as supply chain performance, drivers and metrics, how to design the supply chain, planning demand and supply, improving supply chain profitability, and driving sales and operations.

Some emerging subjects, such as handling uncertainties as well as leveraging technology to predict demand, are growing focus areas in the curriculum and the industry. Another important aspect is the entire placement process, which includes services such as resume building, job interview prep, and placement opportunities. This is especially important as you take the plunge into a whole new industry.  

The IIT Edge  

By opting for a superior 6-month SCM course, professionals can experience live sessions by IIT faculty, one of the best faculties in the world, and seasoned industry experts from the SCM field. You also get a unique opportunity to participate in a campus immersion module hosted at an IIT campus. Here you get to engage with peers and faculty and work on a capstone project under the guidance of professional mentors. At the end of the program, you get a certificate from the prestigious IIT. 

Work and learn! 

Today, you can pursue an online Supply Chain Certification Course, which allows you to work and learn simultaneously. You can access on-demand content via your smartphone or smart device from anywhere and learn as per your schedule. The byte-sized mix of video content, blogs, assignments, live sessions, and assessments make learning an engaging, interactive experience.

Another benefit of a modern SCM course is mentorship. A mentor, backed with years of hands-on  SCM experience and industry-savviness, doubles up as a motivational guide and thought partner throughout the program. Your mentor also has the potential to value-add to your network throughout your professional career. 

Grow your network

Professional success is a measure of your skills and talent and your ability to nurture successful relationships in the industry. As they say, your network is your net worth! An IIT-certified SCM course gives you access to seasoned faculty and industry leaders from IIT’s network. You also have the opportunity to engage with peers looking to pursue growth in the field of your interest. In the future, they will become part of your professional network, not to mention the wide spectrum of IIT alumni who are already well-placed in the industry.   

Fuel career growth

Today, the digital supply chain model, which leverages AI, delivery automation, and blockchain, is a dynamic field. An IIT-backed SCM course equips you with the tools, experience, and network to excel and make your mark in this field.

To know more about online programs that can fuel your career growth, connect with us through chat support or drive down to our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, and Delhi. 

The Past, Present And Future Of Hadoop

Posted on by Imarticus Learning

The Past, Present And Future Of Hadoop

Technologies that have become successful over a period of time go through innumerable cycles of discovery, invention, adoption, socialization, and constant improvement. Hadoop is no different from other technologies and it has followed the same path. 

Hadoop is an open-source software framework, which is mainly utilized for running applications and storing data on clusters of commodity hardware. With this framework, you will get huge storage for almost all kinds of data. Also, it provides massive processing power and the capacity of handling limitless simultaneous tasks or jobs. 

History of Hadoop

If you are interested and want to learn data science, then you have to know about the basics of Hadoop. We all know that when searched with a keyword, search engines provide us with relevant information. With the immense growth of the web, millions of pages were added every day. There was no other option than automating the process for displaying search results. 

This is where web crawlers were created. Many search-engine startups also emanated. One such project was called Nutch, which was an open-source web search engine. The idea of the project was to return search results quickly by distributing calculations and data across different systems so that multiple tasks could be completed simultaneously. 

At this same time, Google was also working on a similar kind of concept of processing and storing data in a distributed and automated manner so that proper search results can be returned faster. 

Nutch was the brainchild of Mike Cafarella and Doug Cutting. And, Cutting later joined Yahoo with his Nutch project. However, the Nutch project got divided. The distributed processing and computing part became Hadoop and the web crawler part remained Nutch. Yahoo then released Hadoop as an open-source project in 2008. 

Hadoop’s ecosystem of technologies and framework is maintained and managed by a non-profit Apache Software Foundation (ASF). This is a global community comprising software contributors and developers.

Hadoop is More of a Framework Than a Solution

It is needless to say that Hadoop’s technology brought a revolution in the world of data storage. Previously, it was expensive as well as difficult to store huge volumes of structured data. But, Hadoop took good care of this burden. Organizations and businesses found a cost-effective way of storing data with Hadoop. 

Hadoop clusters have been set up by many businesses so that they get better business insights or new information from the data. However, there is a slight hitch in this sector. Many businesses have tried to execute an analytics-based or business intelligence idea and they have been disappointed. 

For interactive queries, Hadoop proved to be very slow and this is a disappointment for many businesses. It is now understood that Hadoop is a framework and not a big data solution. For many businesses, Hadoop is too complicated. Basically, to handle Hadoop, a dedicated team is needed with programming knowledge and a level of configuration. 

Cloud-driven Evolution

The world of data warehousing is evolving fast and this means that Hadoop is evolving too. When Hadoop was created, then the public cloud did not exist. In fact, the IT landscape in which Hadoop had gained immense popularity has changed drastically over the years. Now, it is difficult to compare the previous landscape with the current IT landscape. 

Obviously, the way in which Hadoop was used has also changed. If you check instances like Azure’s HDInsight, AWS Elastic Map Reduce, and Google Cloud Platform’s DataProc, you will understand that the majority of public cloud infrastructure providers now integrate and actively maintain a managed Hadoop platform.  

Nowadays, the cloud-based Hadoop platform is commonly used for machine learning, batch processing, and ETL jobs. When a business moves to the cloud, it means that you can use Hadoop immediately and on demand. This happens because the total setup is complicated but it is already taken care of. 

There is no doubt that Hadoop has gained with its move to the cloud. But at the same time, Hadoop is not the only option now for secure, cheap, and robust data storage. Competition has increased drastically in the data-storage industry. There is no second thought that Hadoop is not the epicentre of the data universe. 

Future of Hadoop

It is pretty difficult to say that Hadoop is losing its place in the data market. This is because the framework comes with certain benefits, which are difficult to ignore. Hadoop is an excellent on-premise solution and the demand for such solutions is really high. Moreover, this demand will not go down soon in the coming years. 

Conclusion

Honing your skills in Hadoop or data science will help in making a great career. For a successful data scientist career, it is recommended to take up a course from a well-reputed institute like Imarticus Learning. With such a certification, more job opportunities will open up in the data science industry. 

5 SQL Tricks Every Data Scientist Must Know

Posted on by Imarticus Learning

5 SQL Tricks Every Data Scientist Must Know

The world of data science is changing the way we work, communicate, and live. Data scientists are at the forefront of this change, helping unlock new insights and improve our lives. But in order to do so, they need to understand SQL—the standard language for managing data in relational databases. 

Data science courses offered by Imarticus learning include SQL, Data Visualization with Power BI, Python, and many others. Let us look at the tips and tricks to get you to speed up.

  1. Use wildcard characters for ranges of values

If you want to find all the numbers between 1 and 10—for example—you can just type “1-10” into your query and get results instantly. You can also use “*” as a wildcard character for any value (e.g., “*a?” would return results with aaaa or aaa).

  1. Use LIKE and WITH to find specific patterns in strings

If you’re looking for a particular pattern within a string—like if someone’s name is “John Smith”—you can use LIKE to find those exact characters in your query: WHERE FIRST_NAME = ‘John’ AND LAST_NAME = ‘Smith’.

Use the LIKE operator to find all rows that match a pattern of characters or numbers. For example, if you want to find all the customers whose names start with “J,” use “Name” LIKE ‘J%’.

WITH statement. The WITH statement allows you to define a temporary table for your query so that you can use the results without repeating yourself.

For example, imagine you have data on all the colleges in the US that’s stored in one table called “college,” and they’re all represented by their state abbreviation (e.g., “WA” is Washington). Let’s say you want to know what percentage of incoming freshmen at each college paid full tuition (the answer will probably be 100%). You could try writing this query:

SELECT CAST(cnty AS FLOAT) AS percent_full_tuition FROM college

But you’ll get an error because CAST() only works with numbers. Instead, you can wrap up our query in a WITH statement like:

WITH college_data AS ( SELECT CAST(cnty AS FLOAT) AS percent_full_tuition FROM college )

  1. Sorting data

Data sorting is a key process in the data analysis process. It allows you to put your data into a specific order to easily find and analyze the information you need. One of the most basic ways to sort data is using an ORDER BY clause.

In SQL, you can use the ORDER BY clause to sort your query results according to any column or columns present in your query. To do this, simply add an ORDER BY clause that specifies how you want your query results sorted:

SELECT * FROM tbl_name ORDER BY col1 ASC;

This will sort your results by column col1 in ascending order (A-Z). If we wanted it sorted in descending order (Z-A), we would use DESC instead:

SELECT * FROM tbl_name ORDER BY col1 DESC;

The above query would return all records from table tbl_name with col1 values first, then col2 values, etc., until all records have been returned and displayed on the screen.

  1. Using Arrays

Each value within an array has its own unique index number that determines its position with other values within the array.

For example, if we had an array containing three values: John Doe, Jane Smith, and Joe Brown—and each value had its own index number (1, 2, 3), then our array would look like this: [John Doe] [Jane Smith] [Joe Brown].

The advantage of using arrays over traditional data structures, such as strings or objects, is that arrays allow you to store multiple values together without worrying about their order or relationship with one another. 

Arrays are a common data structure in SQL. An array is a collection of items with the same type and share the same name but may have different values. Arrays are useful because they allow you to store related information together without having to create separate tables for each item or value.

You can manipulate arrays in many ways using SQL syntax, including accessing elements within an array using subscripts or using functions that operate on an entire array (like SUM()).

  1. Derived table

A derived table lets you pull out just the parts of your query that are interesting to you, without worrying about what else might be in there. For example, say you have a bunch of users’ names and their favorite colors:

SELECT name FROM users_table WHERE age > 18;

This query would give us a whole list of users’ names, but we don’t really care about the rest—we just want to know what people like as their favorite color! We could do this with another query:

SELECT name FROM users_table WHERE age > 18;

SELECT favorite_color FROM users_table WHERE age > 18;

This would give us back just one column instead of two (which is why it’s called a “derived” table).

Looking to get a deep and better understanding of SQL, then get in touch with us at Imarticus Learning by visiting our offline centers in major cities throughout India or through chat support. If you are a fresh graduate or have just started your career, Imarticus can offer an extensive data science certification program that ventures through each aspect necessary for data scientists.