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Category: Analytics

Data Analytics Training Takes Center Stage: Structure and Placement

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Data Analytics Training Takes Center Stage: Structure and Placement

In recent times, especially after the boom in internet usage and the popularity of smartphones, the amount of data generated each year has increased significantly. Now, businesses are utilising this information to their advantage. They are using it for product development, marketing and whatnot.

However, to understand the raw data, one needs the help of a data However, to understand the raw data, one needs the help of a data analyst. And, owing to the demand for such professionals, various institutions are organising relevant courses to provide adequate training and help you become a data analyst.

Top 5 Trending Jobs In The Data Science Industry

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Top 5 Trending Jobs In The Data Science Industry

These days, data is the economic fuel. Almost every sector is leveraging data to boost business performance. Data science is the most appealing job profile, with several data science employment options in recent years. According to the US Bureau of Labor Statistics, data science skills will fuel a 28 percent increase in employment through 2026. There is a significant need for qualified data professionals, but there is also a scarcity of skilled data scientists and associated professions.

This post discusses data science career options and the best job profiles in the field. We have discussed the job descriptions and the abilities necessary for those occupations. Let’s get started.

Data Analyst

Data analysts are in charge of various duties, including data visualization and processing. They must run queries on the databases regularly. 

Optimization is a critical ability for a data analyst. This is because they must develop and tweak algorithms that you can utilize to extract data from the world’s largest databases without altering the data.

Their key responsibilities include the following:

  • Data collection
  • Preparation of data for analysis (sampling, cleaning, classification)
  • Look for patterns in data sets.
  • The use of data visualization to show results
  • Create hypotheses to increase specific business KPIs by changing other variables.

Data Engineer

These individuals collect and process data that data scientists and analysts later use. Data engineers oversee database infrastructures, automate retrieval and cleanup operations, and create maintenance algorithms. They make analyzing and interpreting data more effective, safe, and helpful. 

Their primary responsibilities are –

  • Data collection
  • Determine methods to increase data dependability, efficiency, and quality.
  • Use advanced analytics, machine learning, and statistical methodologies.
  • You should prepare data for predictive and prescriptive models.
  • Using data, discover hidden patterns.

Data Architect

A data architect creates and constructs platforms for big data processing to turn data into information that you can use to make business decisions. 

Database Administrator

A database administrator’s job description is reasonably self-explanatory. They are responsible for the correct operation of all of an enterprise’s databases and provide or revoke its services to its personnel based on their needs. They are in charge of database backups and recovery.

Data Scientist

Data scientists must understand business concerns and provide the best solutions through data analysis and processing. For example, they get expected to execute predictive analysis and sift through “unstructured/disorganized” data to provide actionable insights. They can also do so by recognizing trends and patterns that will assist businesses in making better judgments.

Discover a data science career with Imarticus Learning

This certificate program in data science and machine learning helps students get started in data science and machine learning. This curriculum, created in collaboration with iHUB DivyaSampark @IIT Roorkee, will teach students the principles and elements of data science and machine learning and arm them with the necessary skills to apply these ideas to real-world issues. 

Course Benefits For Learners:

  • This 5-month curriculum, created by renowned IIT faculty members, will teach students how to utilize Python to understand data mining and machine learning techniques.
  • Learners will be able to acquire a strong foundation in data science and specialize in machine learning using Python for data-driven decision-making with this data science curriculum. 
  • The data science online training will be live via online sessions with India’s best teachers.

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

4 Core Competencies to Discover the Next Level of Data Visualization in Python

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4 core competencies to discover the next level of data visualization in Python

Python is one of the most versatile programming languages in the world. You can use it in many industries, including data science and analytics. This blog post will discuss four core competencies that you need to reach the next level of data visualization with Python. With these skills, you will create stunning visualizations that will help you understand your data better!

According to the statistics report, “Python is one of the most widely utilized programming languages among developers worldwide in 2021.”

Here are the four core competencies to discover the next level of data visualization in Python:

Understand the data

Before you visualize a particular dataset, first understand that dataset using various statistical analysis techniques such as mean, median, and mode. It will help you identify outliers in your data that might affect your subsequent visualization results. If there are too many outliers, perform outlier removal before creating any chart or graph to get an accurate result.

Once you understand the data, it’s time to explore and visualize it. You can use various plotting libraries such as Matplotlib, Seaborn, and Bokeh for data visualization in Python. So choose the suitable library for the task at hand.

Visualize the data

The main goal of data visualization is to make it easier for the human brain to understand complex datasets. So when you are visualizing a dataset, always focus on how well your graphs or charts can convey the message that they are trying to portray. 

Data visualization is an art, and there are no hard-and-fast rules for creating perfect graphs or charts. But following some standard best practices can help you make more effective visualizations. Here are a few tips:

  • Use colors wisely
  • Keep your charts simple
  • Use legends and labels effectively

Analyze the data

After creating a few visualizations, it’s time to analyze that data. It is where your knowledge of statistics and data analysis comes in handy. Look for trends and patterns in the data and identify any underlying relationships.

Refine and improve

Once you analyze the data, it’s time to refine your visualizations. It might involve tweaking the colors, fonts, or layout of your graphs and charts. You might also need to change the type of visualization depending on the insights you have gained from your analysis.

Always be prepared to iterate on your data visualizations and keep refining them until you are happy with the results.

Now that you know the four core competencies, it’s time to put them into practice and discover the next level of data visualization in Python. 

Discover data analyst course with Imarticus Learning

This data visualization program is by industry specialists to help students master real-world Data Science applications from the ground up and construct challenging models to deliver relevant business insights and forecasts. With this program’s job interviews pportunities, students may take a considerable step forward in their careers. 

Course Benefits For learners:

  • Learn Python online with data analytics and machine learning fundamentals and the most in-demand data science tools and methodologies to become job-ready.
  • Study data science skills by participating in 25 in-class real-world projects and case studies from business partners.
  • Students may take a significant step ahead in their careers by enrolling in this data analyst course with a job assurance.

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

Supervised Learning: The Stepping Stone Of Artificial Intelligence

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Supervised Learning: The Stepping Stone Of Artificial Intelligence

Supervised learning is a form of machine learning that uses labeled examples to find patterns in unlabeled data. This is essential in developing artificial intelligence because it allows computer systems to learn from experience and also make predictions about unseen situations. 

What Is Supervised Learning?

It is a machine learning technique that uses labeled data to train an algorithm. Supervised learning predicts a target variable’s value using a set of predictor variables. 

For example, if we have a set of data that contains observations on people’s height and weight, we can use this information as input for our model so it can predict how tall or heavy each person will be at some point in time (e.g., twenty years from now). 

The main idea behind supervised learning is that we have some training examples (data points) along with labels indicating whether those observations belong together (e.g., Is this person tall?). These labels can come from another source besides humans; they could be numbers representing probabilities instead!

The Algorithms That Make Supervised Learning Possible

Supervised learning is a type of machine learning that uses labeled training data to learn.

In supervised learning, we have two algorithms: regression and classification. Regression models continuous variables, while classification models categorical variables. The algorithm will be able to make predictions about new unseen data based on the known training set and its knowledge about how specific patterns are related to each other. 

The Applications of Supervised Learning

Supervised learning uses labeled examples to train an algorithm. Supervised learning aims to create a predictive model where the labels are known and can use as inputs for the model.

Supervised learning is a potent tool. It makes predictions about future events, classifies data, and finds patterns in data. In particular, you can use supervised learning to detect correlations between variables and make predictions based on these correlations. 

For instance, if you want to predict whether a company will bankrupt based on its financial status, supervised learning could help you analyze historical financial records of previous companies that went bankrupt and make projections about what might happen next for your business model.

Learn Machine Learning and Artificial Intelligence Course with Imarticus Learning.

best data analytics certification course

Learn Supervised Learning by enrolling in the E & ICT Academy’s deep learning Artificial Intelligence certificate program. Learners will benefit from this IIT AI ML Course as they prepare for careers as data analysts, data scientists, machine learning engineers, and AI engineers.

 Course Benefits For Learners:

  • To gain real-world business experience and prepare for a fulfilling career in data science, students work on 25 real-world projects. 
  • Students can impress employers and showcase their skills with a certificate approved by the E & ICT Academy, IIT Guwahati, and an Imarticus Learning-endorsed credential. 
  • After completing this machine learning certification, students can find lucrative employment in the artificial intelligence and machine learning industries.

Contact us through the chat support system, or visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, Gurgaon, or Ahmedabad.

A Data Science Primer For Everyone

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A Data Science Primer For Everyone

A career in data science is extremely lucrative in the current market, as this field is gathering traction worldwide. As the demand for data analysis is increasing year on year, the need for well-trained professionals in this field is also increasing. As a result, leading institutions like IIT Roorkee are now offering courses that are delving into the depth of this field.

So, if you are planning to become a data scientist or enter this domain, completing this course will help you give a better understanding of the same.

Certificate Program in Data Science and Machine Learning offered by IIT Roorkee and iHUB Divya Sampark

If you are offered a chance to do a course in any of the IITs, you will certainly take it. Who in their right mind would miss out on an opportunity like this one?

analytics and data science jobs

So, you can now grab hold of such a chance with the Certificate Program in Data Science and Machine Learning from IIT Roorkee. The IIT data science certification course has been specifically designed to initiate students in the direction of data science and machine learning. This program has been developed in collaboration with iHUB DivyaSampark, which is an IIT Roorkee NGO enterprise started with the aid of the Government of India. Here, low-cost digital tech and allied services are developed and offered as solutions.

This program will help students to understand the basics of data science and ML while helping to apply them to real-life problems. Data mining and ML tools, including Python will help in generating insights that are data-driven and help organisations to grow.

The program is 5-months long and has been designed by highly praised members of the IIT faculty. The focus here is to train a student with relevant industry experience and required technological tools so that they can help businesses make the right decisions, both in terms of scale and revenue.

More on iHUB DivyaSampark at IIT Roorkee

iHUB DivyaSampark is a section 8 NGO company, which is mainly a hub for technology innovation situated on the IIT Roorkee campus. It was created under the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS), which the Department of Science and Technology has set up.

The company helps develop state-of-the-art tech solutions and trains manpower to use these technologies in the real world. The hub also encourages tech professionals to take up entrepreneurship to solve real-world problems like –

  • Making healthcare affordable
  • Developing industry 4.0
  • Make smart and sustainable cities

The ultimate goal of the hub is to develop an advanced ecosystem for modern technologies like AI and ML and allied technology.

Features of the IIT data science certification course

Designed for serving new and mid-level professionals

The program will allow students to develop a strong base in data science and ML using Python for making decisions that are backed by data. This program aims to create data science professionals who are industry-ready.

Data Science online training by industry experts

This is one of the best features of the program. The classes will be conducted live via online sessions with faculty from IIT Roorkee, IIT Ropar and IIT Guwahati. The faculty members are highly experienced in this industry.

Campus Immersion Program for making pitches and connecting with faculty and peers

You also get a chance to get in touch with the faculty and your peers in a campus immersion event at iHUB DivyaSampark at IIT Roorkee on the Greater Noida campus. You can also visit the startup incubation centre and showcase your startup ideas in the relevant sectors.

Startup funding program and mentorship

As a part of the Digital India support scheme, you will get this opportunity to present your business to industry leaders and get funding and mentorship. It is a great opportunity for students who wish to start and build their businesses.

Program coordination by Dr Balasubramanian, the country’s top ML faculty

Program coordination will be done by Dr Balasubramanian Raman, who has been awarded the distinction of being a top academician in the field of data science and ML. Dr Balasubramanian Raman is a Professor Emeritus at IIT Roorkee.

IITR Certification 

The program certificate will be issued collectively by iHUB DivyaSampark at IIT Roorkee. That means you will have a certification from an IIT, one of the country’s premier technological institutions. It will help you get an edge over others when you search for a job in the relevant field.

Now to help you build a career in data science, Imarticus Learning is enabling access to this prestigious Certificate Program in Data Science and Machine Learning from IIT Roorkee. Also, completing this course successfully will enable you for the placement assistance programme, helping you secure a job without any hassle.

Why You Should Earn A Supply Chain Analytics Certification

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Why You Should Earn A Supply Chain Analytics Certification

Supply Chain Analytics is an applied area of study under Supply Chain Management(SCM). It is the application of data to gain insight into massive amounts of data related to procurement, processing, and distribution. Supply Chain Analytics holds data supreme when making effective decisions about the organization. SCA uses a combination of relevant data in the form of graphs and charts. You can utilize cognitive technologies to make a more reasonable, learnable, and interactive approach.

Supply Chain Analytics uncovers patterns in data and generates insights using the same for making data-driven decisions. It is an essential part of SCM and is utilized by almost every field, from minor to more prominent companies. There are different types of SCA, including predictive, descriptive, cognitive, and prescriptive analytics. Overall, SCA assists an organization in its mental activities more quickly and efficiently.

Why is it essential?

Supply Chain Analytics can be used to benefit the organization in numerous ways. Let’s explore what the system offers in terms of Supply Chain Management.

  • Understand risks effectively

Supply Chain Analytics focuses on processing data and identifying its risks. It helps predict future threats and provides methods to avoid them. 

  • Limit costs and improve margins

By accessing data and implementing an integrated approach, you can enable the reduction of costs. Real-time tracking allows visibility as a feature that you can use to observe insights and operational efficacy.

  • Increase accuracy

When you can access data and analyze it according to systematic needs, you’re enabling a chain that honors predicting future demands. Doing so let you see what products need to be minimized according to their profit margin. It also assists you in understanding the client more effectively.

  • Monitor the supply chain

By using Supply Chain Analytics, you can see activities related to warehouses, partnerships, and customers. It helps you make a well-informed decision regarding the mentioned aspects.

  • Apply advanced analytics

By applying advanced analytics to your data, you can differentiate between structured and unstructured data, allowing organizations to devise optimal steps. Advanced analytics offers a real-time technology that provides tracking and supports new business strategies at the same time.

Career options in Supply Chain Industry

In terms of career options, you can choose from a range of fields. When working in planning, you have the opportunity to be a Buyer, Demand Planner, Master Planner, Production Planner, Inventory Analyst, Inventory Manager and Materials Manager.

If your niche is sourcing, you can go for titles like Category Manager, Commodity Manager, Procurement Specialist, Sourcing Manager and Purchasing Manager. If you want to be indulged in the production process, you can opt for titles like Operations Manager, Operations Director, Production Scheduler and Production Manager.

A career as Supply Chain Analyst can be a fulfilling position. If your primary inclination is toward delivering, you can go for the position of Logistics Coordinator, Logistics Manager, Operations Manager, and Transportation Analyst. In logistics, you will fetch the role of a Logistics Manager and Warehouse Manager.

If you wish to work in other roles of utmost importance, you can climb up to the Director of Supply Chain and Supply Chain Manager position. Additionally, you can be a consultant for firms seeking a candidate affluent in Supply Chain Analytics.

Conclusion

To implement the applied knowledge of Supply Chain Management, you must get your hands on a Supply Chain Analytics Certification course that will arm you with industry experience and a professional certificate in connection with the prestigious IIT, Roorkee. Supply Chain Management comes in many different fields, among which Supply Chain Analytics plays a vital part in determining the consequences of any action in the supply chain. You can pave your way into a future in Supply Chain Management by enrolling in a course that teaches you the basics and beyond of Supply Chain Analytics. 

A supply chain management online training course will instil hands-on learning alongside real-time projects on SCM. One of the many advantages of this course is that you get to learn from stalwarts and industry experts who take the time and effort to pass the knowledge to deserving candidates. Moreover, you can expect cut-throat competition in today’s industries, which can be overcome using techniques that pertain to positive outcomes for the organization. Furthermore, you can fill applications for high-demand jobs like  Operations and Supply Planner and Demand Planner once you have successfully completed the course. 

Think You Can’t Master AI? Learn Artificial Intelligence from Scratch

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Think You Can’t Master AI? Learn Artificial Intelligence from Scratch

There aren’t many fields in today’s world that are as interesting and entertaining as AI or artificial intelligence. Moreover, the segment is booming now and growing at a pace not understood before. Innovation and the introduction of new technologies are helping to fuel this fire, along with its widespread application in almost every walk of life. So, if you are wondering how to become an AI engineer, then you are at the right place; keep reading.

What is Artificial Intelligence?

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Before moving on to the topic of how to become an AI engineer, it is useful to learn more about the field itself. Artificial intelligence has been built to simulate the tasks that can be associated with human intelligence. AI solves real-life problems by using both supervised and unsupervised computer programs. The AI models use large data sets to learn how humans would behave while trying to complete a particular task, and then they would spend time learning, perfecting, and doing it without any human intervention.

The field of AI includes:

Applications of Artificial Intelligence

Most AI applications can be bifurcated as either strong or weak.

  1. Narrow or Weak AI: The automated computer systems recognise patterns in large sets of data, and then after observing and learning them, they accomplish the respective task. Examples of narrow or weak AI include recommender systems in Netflix and YouTube or any other streaming platform, smart speakers or Chess bots. This system can adapt to inputs, but they are unable to perform something that is out of its given parameters. However, they have wide usage in many microservices and several macro services.
  2. Strong AI: It is also called Artificial General Intelligence, and it finds a lot of applications in the field of robotics. This AI is reserved for the longer term and is mostly in the stage of infancy. This part of AI is mostly used to create control and prediction models.

Why Learn Artificial Intelligence?

Why should you learn artificial intelligence? AI is one of the most exciting fields in the Computer Science stream. Moreover, it is also at the fore of discovering solutions to real-world problems that are making our lives hard-pressed. This system is learning and offering solutions in almost every walk of human life.

So, the demand for capable professionals is on the rise and will continue to rise in the coming days. So, being well-versed in this field will help you get employed in some of the leading organisations in the world.

What Does an AI Engineer Do?

An AI engineer does a lot of things as their responsibilities and roles vary based on the industry they are employed in. But speaking generally, AI engineers are capable of developing systems or apps which help to quicken the decision-making process and enhance it by considering all the factors and turning it into an efficient protocol-driven method.

AI engineering is, in its entirety, a complex task which can: 

  • Achieve the objectives it has been assigned 
  • Use logic for solving problems and performing an analysis of the probability of achieving success and incorporate that into the machine learning model
  • Direct and monitor projects that are being developed by analysing systems
  • Comprehension and application of best practices in data mining, processing of data recognition of speech and robotics 

How to Become an AI Engineer?

If you wish to become an AI engineer, then it would be advisable to start by developing a background in Python programming and having a strong grasp of the basics. While you are studying Python, you need to master libraries like Matplotlib, Jupyter, Pandas, Numpy, and Scikit. Make sure you have performed some neural network programming projects of your own.

At the same time, you should also strengthen your mathematical abilities, as AI and ML require mathematical aptitude as well as awareness regarding some mathematical concepts. Therefore, you should choose pre-engineering or non-medical after the 10th class.

Additionally, you need to build your skills in data structure and algorithms and relational database technologies like SQL and NoSQL. There are certain other in-depth applications as well.

After clearing 10th and 12th-grade studies, focus entirely on getting admission in a graduate program that offers Data Science, Artificial Intelligence or Machine Learning as a major. Or you could opt for it after graduation as well as take it up as a PG course. After that, you can spend time building AI and ML projects to gain practical experience in industrial-level projects.

The IIT AI ML course

Imarticus Learning has created a course exclusively for Artificial Intelligence and Machine Learning enthusiasts in partnership with E and ICT (Electronic and Information Communication Technology) Academy at IIT Guwahati. This certification course in artificial intelligence and machine learning is taught by world-class faculties of the IIT, helping you get better exposure.

To sum up, if you wish to learn artificial intelligence from scratch, it is not a challenge anymore. There are courses available online, like the one from Imarticus Learning and ample study material that will help you better understand the concepts and resolve any confusion you have. Also, with ample job opportunities, you can easily find employment to gain relevant work experience. 

Course | Data Visualisation with R Course (Includes Job Placement)

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Course | Data Visualisation with R Course (Includes Job Placement)

R programming is one of the in-demand computer languages in the field of data analytics and data science. So, it comes as no surprise that many data analyst aspirant prefers to enrol on an R programming course in place of a Python programming course. That is because it is certainly a better option for data visualisation. The graphs and statistics are more elaborate than Python and are more intuitive.

Moreover, when compared to Python, it is also easy to master this computer language, and the learning curve is not too steep either. Other than that, most of the features in both programming languages are similar to a large extent.

What does the R Programming course consist of? 

If you are taking up a data visualisation course, then make sure you take up a course in R programming as well. What you will get to learn in this course is primarily the Grammar of Graphics. It is an extensive system which is used for building graphs and elaborately describing them. After you learn to make graphs in the R programming course, it progresses to the library and the stuff that comes under this subset of data visualisation.

First of all, you are taught how the package for data visualisation in R and ggplot2 is applied to generate box plots, basic bar charts, line plots, histograms, pie charts and scatter plots. These different types of graphical plotting will also help you master further customisation. The R programming course also teaches other techniques for visualising the data apart from generating charts and plots. You will also be taught about annotations and labelling in these graphs.

Additionally, there is a package called leaflet, which helps you to generate map plots and is one of the most powerful data visualisation packages in R as it can display data at various levels for better visualisation. It also helps plot data based on its geolocation, so it is highly useful for the meteorological department, where various weather-based data are displayed.

Finally, in an R programming course, you will learn how to build creative, intuitive and interactive dashboards using packages like R Shiny that can help to alter the appearance of your data app, which has been built in R.

Where can you enrol for data visualisation with an R course?

Although data visualisation courses are extremely popular and numerous institutes offer them, students should choose one based on their needs. A student should pick up a course that helps them to learn some useful techniques and give them hands-on experience through practical training in the labs and trying out various techniques in R. It will aid them in building various graphical models of data.

Many top technology companies are offering data analysis courses from their stables. But there is no data analytics course with placement. Moreover, the focus in these courses is rarely on R, which can be quite frustrating as a student cannot get an all-round perspective of the data analytics course.

In this regard, a solution can be the data analysis course offered by Imarticus Learning. It focuses on both Python and R and gives both programming languages equal weightage. You will be given both a basic run-in and advanced guidance on plotting various statistics and graphs with the help of R. You will get both classroom training and live online training. This coursework will give you enough exposure and help you succeed as a data scientist.

But before you enrol in this course, please ensure that you have some programming knowledge beforehand because this is an advanced course. Many websites and online academies have free R programming courses. In these courses, you learn about various packages like ggplot2, dplyr, mlr3, knitr and tidyverse. Once you have a good base in programming, especially in R, you can pick up various other requirements for the data visualisation course. You could also take up an internship role to get more practical exposure.

To sum up, finding an R programming course that offers theoretical and practical exposure is crucial. It helps you to get an in-depth understanding of the same and avoid facing troubles while implementing the same in the real world. So, find a course of your preference and secure placement in this popular field of data science. 

Introduction To Data Analytics: Technologies, Jobs and Careers

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Introduction To Data Analytics: Technologies, Jobs and Careers

Nowadays, Data Analytics has become a sort of a buzzword in the data science industry. Just have a look at any of the job websites, and you will see that there are many vacancies in data science. Even Harvard University has labelled it as one of the hottest job fields in the USA, and India is also a part of the same trend.

So, what is the reason behind this craze for data analytics and data science jobs? Let’s have a look.   

What is Data Analytics, and what does a data analyst do?

Data Analytics is a subset of Data science. It is where raw data is cleaned, analysed, interpreted and displayed using several approaches with the help of business intelligence tools. These data analysis tools transform raw data into interpretable information that aids in making successful decisions.

But how is the data presented? Raw data is converted into meaningful information, statistics and explanations with the help of tools and techniques. There are multiple tools that data analysts use for generating all the interpretations of data.

At the same time, there is some programming expertise that a data analyst requires. For example, they could learn either of the two programming languages, R and Python, to process the data. For storing this data, they could use SQL. But the entire tech tools a data analyst needs are mentioned in the next section. So, just continue to read the topic till the end.

Technologies employed by Data Analysts

Several tech tools and programming languages can make the life of a data analyst easier. As already mentioned, data analysts have to process raw data and use it to generate various graphical representations. For that, they need to –

  • Identify the data they require
  • Collect raw data from the specific source they have identified
  • Clean the data and remove the inconsistencies
  • Analyse the data
  • Interpret the results

To perform these functions, data analysts use several tools. First of all, let us delve deeper into the programming languages that come in handy.

  • Python
  • R
  • SQL
  • Hadoop for big data

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The best thing about these programming languages is that there are multiple online resources to master these programming languages. You will find millions of tutorials to learn Python online.

Apart from the programming languages, you need to master some of the tools that are mentioned below:

  • Google Sheets
  • Microsoft Excel
  • Tableau
  • SAS(Statistical Analytical System)
  • Microsoft Power BI
  • Jupyter Notebooks

Mastering these tools and programming languages is quite important because they help you by making your job easier. You get to learn all these in a good data analytics certification course, and you can get in touch with us at Imarticus Learning.

Jobs for Data Scientists

Data science jobs stretch across various sectors. It has always been used for business, in both sales and marketing. Not only that, it is also handy for retail so that the inventory can be managed. Apart from business, it is used in medical infrastructure, operation research, finance and allied sectors. It is also being used in the entertainment field for various data-based jobs, especially for calculating the TRP of various shows.

Now it is also being used in education, law, security, automobile industry, energy sector supply chain, social media and in various fields of research. Data analysis has crept into almost every industry as it is finding a lot of applications in various fields.

But which are the most popular roles that are also enjoying a huge career and salary growth? Some of these roles are mentioned below:

  • Medical and health care analyst
  • Market research analyst
  • Business analyst
  • Business intelligence analyst
  • Operations research analyst
  • Intelligence analyst

These jobs are the top roles across various industries and job sectors. You will find multiple listings of these roles in all the leading job portals. Some of the beginner roles start above the ₹5,00,000 pay bracket. However, if you have completed a good data analytics certification course, then you will be able to command a good salary from your employing organisation.

The overall career of a Data Analyst

Choosing data analysis as a career path is a great decision, especially in the current market. After bagging a beginner role, try to gain more technical skills. Then you move to the position of a data scientist.

But there is a clear bifurcation of the career paths. For example, if your interest largely lies in statistics and data analysis, then try out business intelligence and analysis. But if you love the tech side, pick data science and data engineering as your career.

To conclude, the opportunities for data science jobs in the current scenario are increasing every year and are slated to grow even further in the coming years. So, being prepared with the necessary knowledge and technical know-how will greatly boost your career. In this regard, you can always look at the Post Graduate Program in Data Analytics and Machine Learning from Imarticus Learning to enhance your skill set. 

Learn Hadoop Online: A Brief Summary of Apache Hadoop

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Learn Hadoop Online: A Brief Summary of Apache Hadoop 

Introduction To Apache Hadoop

A type of open-source software based on a Java programming framework, a Hadoop system is programmed to address any hurdle it faces. Using a skilled framework distributes unclear and large amounts of data in multiple programming systems.

Apache Hadoop provides increased effectiveness and efficiency with high productivity. Though it is a single server, it extends to various networks further connected to machines.

Components

Apache Hadoop has several components which play a critical role in bringing out the responsibilities of Hadoop. They are as follows:

  • Library deals with all the complications and discrepancies at the top layer of an application.
  • The Hadoop Distributed File System is the Storage unit that helps process stored data in various chunks and is efficiently transmitted with the help of cluster nodes. 
  • MapReduce is the processing unit. 
  • Yet Another Resource Navigator (YARN) is the resource management unit. 

Role of Apache Hadoop In Big Data

In the era of digitization, all information has to be stored digitally, and it is a huge challenge to control and manage all the data. It thereby creates a need to develop a system that can control, manage and handle an overabundance of such data. Thanks to Apache Hadoop, one can store and manage big data. Various roles played by it are:

  • It stores data at a lower cost: 

Apache Hadoop is designed in such a way that it can store data at much lower costs as compared to other systems available.

  • Velocity and variety: 

Apache Hadoop processes data and gives information to enterprises on time. It uses different techniques and tools to structure the data into valuable outcomes.

  • Provides security to big data: 

Apache Hadoop is also used to detect cyber attacks on the system as it uses different tools and techniques. It is also helpful in recognizing the attackers that try to attack and want to gain access.

Advantages of Apache Hadoop

Some of the advantages of Apache Hadoop are mentioned below.

  • Flexibility: In Apache Hadoop, data can be stored in semi-structured and unstructured formats. It also enables enterprises to access new data sources easily.
  • Scalable: Traditional systems have limited data storage capacity. On the other hand, Hadoop is highly scalable as it is distributed and stored across several servers.
  • Resilient: This system is fault resilient as it stores data in several nodes, and there is another copy to use in the event of a contingency.
  • Fast: The storage method used by Hadoop is rooted in a distributed file system that manages clustered data. The tools used for processing data are often located on the server where data is placed, resulting in faster data processing. 

Discover Data Analytics and Machine Learning Certification With Imarticus Learning 

Our Data Analytics Courses will help students:

  •  Learn job-relevant skills with the most in-demand data science tools and techniques. 
  • Master data science skills through 25 in-class, real-world projects and case studies from industry partners.
  • Learn with a curriculum that focuses on outcomes and a pragmatic learning style, including SQL programming, big data, Hadoop, data visualization with Tableau, etc. 
  • Obtain guaranteed interview opportunities and get hired.

Conclusion 

Ideal for recent graduates and early career professionals, this elite Data Analytics and Machine Learning Course will help you take your data analytics and science career to heights you have never imagined! 

For any queries, please do not hesitate to Contact Us or drive to one of our training centers in Mumbai, Pune, Thane, Chennai, Bangalore, Delhi, and Gurgaon.