Data science as an emerging and rewarding career stream
The digital advancement in everything has brought a change in the world. And imagine the data that has to be used and managed.
Here comes the role of data science. Data science can be explained as an interdisciplinary stream involving mathematics, science, and art. To be particular, data science comes under the IT sector as it helps in the technological part of any organization. Along with good communication skills, data scientists should be competent in quantitative reasoning, data analysis, statistics, and computer programming.
With the need for time and industries, Data science has emerged as a rewarding career with attractive salaries and fancy rewards and incentives. Here it is imperative to mention that a data scientist's job is considered the sexiest job in the running decade, and it is just the starting of this promising field. As the organizations are concerned about the data they have to take care of, or the information holding the entire value of their businesses, the demand for a data scientist will be huge.
Job roles in Data Science
The data science job descriptions you'll discover here are intended to provide you with a basic idea of the most crucial jobs you'll want on your technology team. Keep in mind that there may be some variations based on your configuration and strategic focus.
Some organizations require you to acquire all of the abilities of all of these occupations, but as your company expands, you may discover that specific people focus on their talents to address the first and most issues related to data science and specialize in one of the tasks below.
- Business Analyst
- Database Administrator
- Data Analyst
- Big Data Engineer/Data Architect
- ML Engineer
- Business Intelligence (BI) Developer
- Business Intelligence Analyst
- Data Scientist
- Computer Vision (CV) Engineer
- MLOps Engineer
- Natural Langauge Processing (NLP) Engineer
What do statistics say about Data Science?
Back in 2017, LinkedIn announced that Data science is the fastest-growing career. Another leading recruitment company named Glassdoor stated Data-science as the highest paying job in the United States. Data scientists have been getting 650% growth on average in the USA since 2012. The charm of this career does not end here. There is an expected employment growth of 31.4 % for data scientists. This data came from a The Bureau of Labor. According to executive recruiters Smith Hanley Associates, 2021 was a banner year for data scientist hires, and this trend is expected to be continued in 2022 and then in 2023, and so on. According to PayScale, the average yearly salary of an Azure data scientist in the United States is US$95,102. Pay can rise to $110,000 per year with experience and skills. An average Azure data scientist in India earns around INR 1,180,000 at first, but with experience and seniority, this income can rise to INR 2,000,000.
Benefits of hiring Data scientists in the organization
The good side of hiring Data scientists is not hidden. This position has become necessary for any company. A well-trained and experienced data scientist helps any organization in
- Structuring and managing the raw data into a usable form
- Helps in raising revenue level
- Aids in reducing cost
- Better customer experience and hence better reputation of organization
- Helps in increasing business agility
- Collection and storage of data
- Build models by using coding and other programming techniques.
- Provide solutions to various problems in business
- Work in collaboration with other departments in order to prepare data sets and databases
- Involved in the betterment of business by providing valuable insights after analyzing datasets.
If you want to enter the tech world, data science is one of the good options that can be explored further, and as expected, you will not be disappointed. A data scientist uses many tools, products, softwares, or applications to complete their job responsibilities. Azure is the one platform that is gaining popularity as it fulfills all the requirements of data scientists. They include Azure Blob Storage, several types of Azure virtual machines, and other machine learning platforms.
What are Azure data scientists?
The definition of Azure Data scientists is broad to be understood. If you aspire to enter this stream of the IT industry, you are supposed to have sound knowledge of data science and machine learning to implement and employ machine learning workloads on the Azure platform. In other words, if you have knowledge or experience in the Microsoft Azure machine learning program, you fit the role of Azure Data scientist. To be precise, the Azure Data scientists’ team works on identifying critical data assets that can be further used for the betterment and benefits of the company.
The Subject matter experts who can plan and establish a functional environment for data science operations on Microsoft Azure are known as Microsoft Certified Azure Data Scientist Associates. They can conduct data experiments, train prediction models, and manage, optimize, and deploy machine learning models. The certification is for people who can deploy and execute machine learning projects on Azure using cognitive computing techniques.
Is it worthwhile to get a Data Science certificate from Microsoft?
Yes, certainly. The Data Science certificate from Microsoft is worthwhile. The "Microsoft Certified: Azure Data Scientist Associate" certificate comes among the top 15 Data Science credentials. This certification assesses applicants' knowledge in machine learning, artificial intelligence, predictive analytics, natural language processing, and computer vision. To pass this certification, which costs USD 165 to register, you must master abilities such as managing identities and governance, designing and managing virtual networks, deploying and managing resources, and implementing and managing storage. Enroll in industry-grade Data Science Courses to discover the subtleties of Data Science.
How do I become an Azure data scientist?
If you have already made up your mind to become an Azure Data scientist, here is the process you have to go through. Microsoft provides different relevant certificates that fall under three categories, which are:
All these three have their significance. You must follow the accurate path to reach your destination sooner. Before jumping into the certification exams, there are some prerequisites you must be aware of.
Basic knowledge of fundamentals of data science, various tools, and general relevant terms.
The ability of data analysis, data mining, data visualization, data modeling, and other cognitive skills
Knowledge of essential programming languages includes Java, Python, SQL, and R, along with expertise in C++, Tableau, Perl, MATLAB, and Reporting Tool Software.
Deep learning, along with creativity and open-mindedness, is essential to identify the trends in the data and establish connections.
Data scientists should also be competent in mathematics on linear algebra, statistical modeling, algorithm identification, etc.
Getting a certificate in Azure Data science can work wonders to bag a rewarding job. The most convenient and beneficial certificate for beginners is Azure Data scientist associate. To get this certificate, you have to qualify for the DP-100 exam. The best starting point is with DP-100: Designing and Implementing a Data Science Solution on Azure. Besides the exam mentioned above, you can also take the DP-200 and DP-201 certification tests to improve your expertise as an Azure data engineer.
The DP-100 exam assesses a candidate's potential as an Azure data scientist and measures their ability to complete various technical tasks that all data scientists must complete. The best way to qualify for exam DP-100 exam on Azure is to examine your candidature based on four significant domains with the following weightage:
- Manage Azure machine learning resources (25-30 percent)
- Experiment and develop models (20-25 percent)
- Develop and implement machine learning solutions (35-40 percent)
- Use machine learning responsibly (5-10 percent)
You can peruse with this credential, if you are someone who wants to get settled as a data scientist and have a background in IT, computer science, math, physics or any other relevant stream.
About the Exam
Microsoft calls the "DP-100 Test" the Microsoft Certified: Azure Data Scientist Associate exam. This is available online and may be accessed from anywhere on the planet. Candidates must register and schedule the exam for a price of USD 165 in order to take it. This charge varies depending on the country, and you must pay INR 4,800 if you are from India.
During the exam, you will have to solve 40 to 60 questions to be answered within 2 hours. Although there is no fixed format for the questions, all the questions will be objective with formats like a case study, short answers, multiple-choice, mark review, drag and drop, and other objective formats.
Multiple choice questions or multiple correct answers can be featured in the exam. To qualify for the exam, you have to score at least 700 out of 1000 on a scale of 100 to 1000.
How can you pass the exam?
If you have prior experience with Microsoft Azure or professional training, this exam will feel like a piece of cake for you. Attempting proxy exams can ensure your success in the exam.
If you do not get qualifying marks on the first attempt, you can write the exam after 24 hours. If you fail the second attempt, too, you will have to wait for at least 14 days to write the exam a third time. If you fail the first time, you can retake the test after 24 hours. In total, you will be able to attempt 5 times per year as per the guidelines of Microsoft.
Here are some facts that should be kept in mind to ensure success.
- In the exam, there will be 2 non-skippable practical questions. They can be either lab-related or case study-related questions.
- You are suggested to prepare well before the exam as the exam is proctored.
- Microsoft's exam pattern is updated twice a year, so you should rely on the most updated version from the official website.
- You are suggested to focus on theory as well as lab-related practical questions.
- Theory questions are listed on Microsoft's official website; review them thoroughly. Prepare every module with focus. The theory can be done in 1-3 weeks, depending on your efficiency.
- The modules such as Build and Operate machine Learning Solutions and Azure Machine Learning carries the highest weightage.
- Microsoft also provides an official instructor-led paid course to help you qualify for the exam DP-100.
- Revision is a must to prevent getting confused during the exam.
Other Azure Data Science Certificates by Microsoft Other than Azure Data Science Associate, Microsoft also provides some other certifications that can be gained according to your need.
Microsoft Certified: Azure Data Fundamentals
The Microsoft Azure Data Fundamentals exam is designed to assist candidates in preparing for the Microsoft Certification Azure Data Fundamentals. The primary goal of this credential is to assist students in gaining practical experience and a thorough grasp of Azure's data processing services. It assesses if the individual can describe core data concepts and how to work on Azure activities.
The cost for the exam is somewhere between INR 750 to INR 12000. To get this certificate, you have to qualify for DP-900. The exam outline includes modules such as the concept of relational and non-relational data and various kinds of data-related activities that can be either transactional or analytical. If you have this certificate, you can be Database Administrator, Data Analyst, Data Engineer, or Developer in any leading company.
Microsoft Certified: Azure Data Engineer Associate
Those who want to get jobs such as data engineers can get this certificate to ensure their success in getting a high-paying job. The Microsoft certified Azure Data Engineer Associates are known for their expertise in data processing languages such as Python, SQL, Scala, and others. During the learning phase for this certificate, the learners will be able to learn the data-related activities such as data integration, data transformation, and consolidation of the data from the system into structure form to make models and analytical solutions can be explored.
The main objective of this certificate is to make the aspirants aware of architectural data patterns and simultaneously process the same. The registration for the exam will cost INR 12,354. The exam you are supposed to qualify for to attain this certificate is DP-203.
Is Azure good for data science?
Across the globe, 500+ leading companies are using Azure services, and they like it. Azure has already had a significant impact in all kinds of industries. The services and tools provided by Azure are helping IT professionals. Undoubtedly, Azure is also a favorite platform for data scientists. The salient features of Azure that make it worthwhile and unique from other competitive platforms include Azure machine learning studio, Azure machine learning services, and Azure data science virtual machine.
MS Azure can be used in various ways in a data science pipeline. The most obvious choice is to use AzureML, and it is most preferred among others because of its overlapping functionality. A data scientist can create complicated machine learning experiments using this toll of Azure without writing a single program (by simply dragging and dropping different modules on the experiment canvas). It is a method of visualizing and executing learning algorithms. You can also utilize R, Python, and SQL for data manipulation and feature engineering. Azure ML is a massive library of pre-trained machine learning algorithms.
Jupiter notebook (formerly known as IPython) was just added to AzureML. As a result, you can easily add your statistics and write Python code in a notepad to obtain the same feel as Anaconda while retaining the elasticity of the Cloud. In simple words, Azure is the most convenient and easy-to-operate data science solution platform.
There are a wide variety of available data science solutions in the cloud. The differentiating factor between these services includes algorithms, features, pricing, and programming languages.