<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1642531213/image2_erhzp7.png" /></center><br>

<p>DataCamp is proud to announce our partnership with Tableau to make world-class data science software and education widely available to the teachers and students of the world. Every teacher with both a DataCamp for Classrooms account and a Tableau for Teaching license <a target="_blank" href="https://forms.gle/QLzKuEpFDRTnPkU26">can apply</a> to gain free access to DataCamp’s interactive Tableau courses for themselves and their students. We see this as an important opportunity to bring STEM education fully into the 21st century with a partner just as dedicated as us to democratizing data science.</p>
<p>Data is being consumed at an astronomical rate but are all students given the same opportunity to see and understand data? Do instructors have the resources easily and readily accessible to prepare the next generation of students? The answer, sadly, is a resounding no.</p>
<p>“Tableau for Teaching is excited about the partnership with DataCamp,” says Jessica Lyons, Senior Manager of <a target="_blank" href="https://www.tableau.com/academic/teaching">Tableau for Teaching</a>. “The mission of arming students and instructors with the resources needed to create a data-literate world aligned perfectly with DataCamp’s goals."</p>
<p>The feeling is mutual. At DataCamp, we see Tableau as an ideal platform to get high school and college students excited about data. No other data visualization tool caters to novices and experts alike as deftly as Tableau does. Teachers armed with these resources will empower their students to better understand and analyze the data in their lives, preparing them for tomorrow’s data-driven industries. With just some basic knowledge of Excel/Spreadsheets and a good data set, young people can create powerful and inviting visualizations of the data that matters to them most.</p>
<h2>How do teachers apply?</h2>
<p>It’s a simple three-step process for qualified teachers to apply for Tableau access on DataCamp:</p>
<ol>
<li><a target="_blank" href="https://www.datacamp.com/groups/classrooms">Apply and get approved for DataCamp for Classrooms</a></li>
<li><a target="_blank" href="https://www.tableau.com/academic/teaching#form">Apply and get approved for Tableau for Teaching</a></li>
<li>Fill out the <a target="_blank" href="https://forms.gle/QLzKuEpFDRTnPkU26">official DataCamp + Tableau application form</a></li>
</ol>
<p>DataCamp and Tableau representatives will review all applicants within a week of the submission date to verify their status in both programs. Once verified, you&#39;ll receive a confirmation email once Tableau training has been added to your DataCamp group. All the users you invite into that DataCamp for Classrooms account will get immediate, free access to our Tableau courses.</p>
<h2>What do students and teachers get with DataCamp + Tableau?</h2>
<p>DataCamp for Classrooms offers free unlimited Professional licenses for you and your students to learn on DataCamp. That means access to over 350 courses in R, Python, SQL, Git, Scala, Spreadsheets, Excel, as well all of our projects, practice modules, the mobile app, and more. And teachers get a group dashboard with all the functionality they need to run a successful classroom: the ability to create teams, give assignments, and monitor progress. College/university teachers from around the world and high school teachers in the US and UK are eligible to apply.</p>
<p>By also becoming a recipient of Tableau for Teaching and <a target="_blank" href="https://forms.gle/QLzKuEpFDRTnPkU26">completing this form</a>, teachers will gain access to our six outstanding courses on Tableau, <a target="_blank" href="https://app.datacamp.com/learn/courses/introduction-to-tableau">including Introduction to Tableau</a>, <a target="_blank" href="https://app.datacamp.com/learn/courses/connecting-data-in-tableau">Connecting Data in Tableau</a>, and <a target="_blank" href="https://app.datacamp.com/learn/courses/analyzing-data-in-tableau">Analyzing Data in Tableau</a>—everything you and your students need to go from novices to experts. Just like all our other courses, they can run entirely in-browser (no additional software required), or users can download the datasets and run our exercises on their desktop-based Tableau clients. Previously reserved for Premium and Enterprise DataCamp customers, these in-demand courses will completely change how educators around the world teach students Tableau.</p>
<p>If you’re a teacher, apply to these revolutionary edtech programs today (students, please refer this offer to your STEM teachers)! This is the only way to learn to become a Tableau whiz at your own pace for free.</p>
<p>To apply for free Tableau courses through DataCamp for Classrooms, <a target="_blank" href="https://forms.gle/QLzKuEpFDRTnPkU26">click here</a>.</p>
<p>To apply for a free DataCamp for Classrooms account, <a target="_blank" href="https://www.datacamp.com/groups/classrooms">click here</a>.</p>
<p>To apply for a free Tableau for Teaching license, <a target="_blank" href="https://www.tableau.com/academic/teaching#form">click here</a>.</p>


https://www.datacamp.com/community/blog/datacamp-and-tableau-partner-to-teach-young-people-data-visualization

DataCamp has partnered with Tableau for Teaching to provide world-class courses on Tableau to teachers and students around the globe for free. Find out how you can help improve your students’ data literacy with DataCamp for Classrooms.

DataCamp and Tableau Partner to Teach Young People Data Visualization

<p>A third of organizations polled in the CIPD’s <a target="_blank" href="https://www.cipd.co.uk/knowledge/strategy/development/learning-skills-work#gref">learning and skills at work report</a> saw their training budgets slashed in 2021. Smaller budgets, coupled with more people working from home than ever before, meant that team managers and L&amp;D professionals had to do more with less. This resulted in a drastic shift to digital training. Analysis by the CIPD has shown that organizations that embraced this change are reaping the rewards, with an improved culture and increased demand for learning from their workforce.</p>
<p>But it wasn’t all positive. The report also revealed that 77% of team managers and L&amp;D professionals had no way of assessing the impact of their learning program. The most commonly self-reported method for evaluating training programs was “participant satisfaction surveys”—subjective reporting that’s difficult to link to ROI and your organization’s business goals.</p><br>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1640192579/Marketing/Blog/L_D_reporting_-_DataCamp.jpg" />CIPD: <a target="_blank" href="https://www.cipd.co.uk/knowledge/strategy/development/learning-skills-work#gref">Barriers to the evaluation of learning and development program and initiatives (%)</a></center>

<br><p>As shown in the image above, there were many barriers to better reporting—competing priorities and a lack of time being top of that list. At DataCamp, we believe it should be simple to report on the business impact of your learning program. That’s why all <a target="_blank" href="https://www.datacamp.com/groups/business">DataCamp for Business groups</a> now have more ways than ever before to access insights you can share with stakeholders quickly.</p>
<h1 id="how-to-level-up-your-reporting-in-2022-">How to level up your reporting in 2022:</h1>
<h2 id="1-create-professional-one-click-reports-with-custom-reports">1. Create professional one-click reports with Custom Reports</h2>
<p>We get it. Reporting on the impact of your learning programs takes time. That’s why we created Custom Reports. They’re pre-made reports that DataCamp admins can use to demonstrate your learning ROI and reveal measurable insights, including everything from a weekly status report to your most engaged learners or most popular courses—with new reports added all the time.</p>
<p>Create professional reports from our pre-made templates
Get detailed insights into your learning program
Schedule regular, automated reports, so you never miss a deadline</p>
<p>Ready to improve your reporting? <a target="_blank" href="https://support.datacamp.com/hc/en-us/articles/4412251811223-DataCamp-Custom-Reports-An-Overview">Learn how to get started on our help center</a>.</p>
<br><center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1640192361/Marketing/Blog/DataCamp-for-Business-Reporting-with-Custom-Reports.gif" /></center>

<h2 id="2-plug-and-play-connect-your-learning-data-to-tableau-and-power-bi">2. Plug and play—connect your learning data to Tableau and Power BI</h2>
<p>With our 2021 update to Data Connector, you can now create reports and dashboards directly in Tableau or Power BI using DataCamp’s built-in Athena connection. The Athena plug-in makes it easier to view, query, and visualize learning insights directly in your platform of choice.</p>
<p>Ready to analyze and visualize your data in Tableau or Power BI? Invite your engineering team to <a target="_blank" href="https://enterprise-docs.datacamp.com/data-connector/using-the-data-connector/analyzing-data">follow these steps</a>.</p>
<br><center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1640192282/Marketing/Blog/DataCamp-for-Business-Reporting-with-Data-Connector.gif" /></center>

<h2 id="3-build-custom-reports-in-python-or-r-with-workspace">3. Build custom reports in Python or R with Workspace</h2>
<p>If your organization has enabled the Workspace editor, you can build your reports from scratch in Python or R, or choose from one of our ready-to-use Python Custom Reports.</p>
<ul>
<li>Analyze your organization’s learning data from the comfort of your browser</li>
<li>Share your insights while staying in control of who gets to see them</li>
<li>Comment directly on your Workspace reports, just like in Google Docs</li>
</ul>
<p>Want to build your own Custom Reports? <a target="_blank" href="https://app.datacamp.com/workspace/">Learn more</a>.</p>
<br><center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1640192284/Marketing/Blog/DataCamp-for-Business-Reporting-with-workspace.gif" /></center>

<br><p>Let’s make 2022 the year that you go beyond employee satisfaction surveys and level up how you report on the difference you’re making to your workforce. <a target="_blank" href="https://www.datacamp.com/groups/business">Learn more about DataCamp for Business</a> or if you’re an existing customer, log in to try these new features.</p>
<h2 id="you-might-also-like-">You might also like:</h2>
<h4 id="white-paper-what-300-l-d-leaders-have-learned-about-building-data-fluency">White Paper: What 300+ L&amp;D Leaders Have Learned About Building Data Fluency</h4>
<p>Two of the most important actions required to deliver organization-wide data literacy are strong executive support and demonstrating value across multiple teams.</p>
<h5 id="-download-the-white-paper-https-www-datacamp-com-resources-whitepapers-what-300-l-and-d-leaders-have-learned-about-data-fluency-"><a target="_blank" href="https://www.datacamp.com/resources/whitepapers/what-300-l-and-d-leaders-have-learned-about-data-fluency">Download the white paper</a></h5>
<h4 id="customer-success-story-autodesk-bold-">Customer Success Story: Autodesk<bold></h4>
<p>Find out how this Fortune 1000 software company stayed ahead of the competition.</p>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1640194048/Marketing/Blog/Autodesk_and_DataCamp_-_customer_success_story.png" /></center>

<h5 id="-read-the-case-study-on-datacamp-https-www-datacamp-com-resources-case-studies-autodesk-case-study-"><a target="_blank" href="https://www.datacamp.com/resources/case-studies/autodesk-case-study">Read the case study on DataCamp</a>.</h5>


https://www.datacamp.com/community/blog/3-ways-to-level-up-your-team-reporting-in-2022

77% of learning professionals don’t know how to assess the impact of learning programs. That’s why, in 2022, DataCamp is making it easier for admins to report on the difference you’re making, using Custom Reports and our new Power BI and Tableau connectors. 

DataCamp is making it easier for admins to report on the difference you’re making, using Custom Reports and our new Power BI and Tableau connectors. 

3 ways to level up your team reporting in 2022

<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1641824947/DataCamp-subtitles-hello-world_gotbkm.png" /></center><br>

<p>It’s now easier to learn in your native language, with video subtitles available in 16 languages—including Arabic, Indonesian, Polish, Thai, Turkish, and Vietnamese.</p>
<p>All videos are also available with English, Spanish, French, Chinese (simplified), Portuguese, German, Korean, Japanese, Russian, and Italian subtitles.</p>
<h2 id="how-to-turn-on-video-subtitles-in-datacamp-">How to turn on video subtitles in DataCamp:</h2>
<p>To use these new subtitles, click on the closed captions (CC) icon when watching any video and select your preferred audio or subtitle options.</p>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1641824947/DataCamp-video-subtitles-_msggpy.png" /></center><br>

<p>Please continue to let us know <a target="_blank" href="https://support.datacamp.com/hc/en-us/requests/new?ticket_form_id=360000029413">how we can improve product features</a> like our translations and recommend which languages we should consider adding next. We would love to hear your <a target="_blank" href="https://support.datacamp.com/hc/en-us/requests/new?ticket_form_id=360000029453">feedback on our courses as well</a>! Together, we can make DataCamp a place where people from all walks of life can learn the language of data.</p>
<h2 id="you-might-also-like-">You might also like:</h2>
<h4>Customer Success Story: DataBird</h4>
<p>DataCamp helps a French bootcamp address the country&#39;s demand for data skills.</p>
<ul>
    <li><a target="_blank" href="https://www.datacamp.com/resources/case-studies/databird-case-study">Read the case study on DataCamp</a></li>
</ul>
<h4>Telling Effective Data Stories with Data, Narrative, and Visuals</h4>
<p>Brent Dykes discussed how data, narrative, and visuals can drive effective data stories in a recent webinar. Learn his best practices in this article.</p>
<ul>
<li><a target="_blank" href="https://www.datacamp.com/community/blog/telling-effective-data-stories-with-data-narrative-and-visuals">Read the best practices</a></li>
</ul>


https://www.datacamp.com/community/blog/six-new-subtitle-languages-added-to-datacamp

Learn in your native language! All DataCamp videos are now available in 16 languages, including Thai, Arabic, Turkish, Vietnamese, Polish, and Indonesian subtitles.

Six new subtitle languages added to DataCamp

<h1 id="introduction">Introduction</h1>
<p>In 2012, <a target="_blank" href="https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century">Harvard Business Review named data scientist as the sexiest job of the 21st century</a>. Ten years later, despite the emergence of AutoML platforms, (e.g., AWS Redshift ML and Google Cloud AutoML) and the pandemic-era slowdowns, data scientist remains one of the most wanted roles around. In fact, the data scientist ranks the highest paid role in the tech industry <a target="_blank" href="https://www.hiringlab.org/2018/03/15/data-science-job-postings-growing-quickly/">with an average yearly salary of $150,000</a>.</p>
<p>Although their specific responsibilities may vary from industry to industry and from company to company, most data scientists share the mission to help organizations create value from data. They do this by exploring patterns and trends in a large amount of data, communicating results to a broad range of stakeholders, and building and maintaining models to enable automated decision-making. Hence, becoming a data scientist requires a unique, diversified skill set covering statistics, coding, business sense, and communication—all to be demonstrated through a series of interview questions and take-home challenges.</p>
<p>With this blog post, we would like to share a few tips, from the perspectives of both an applicant and an interviewer, to help you stand out in a data scientist interview and get your dream offer.  </p>
<h1 id="tip-1-get-familiar-with-the-role-and-the-company">Tip #1: Get Familiar with the Role and the Company</h1>
<p>As mentioned above, “data scientist” is a vague term that can refer to any roles that revolve around data. Two data scientists from different companies or different industries may find themselves engaged in completely different types of tasks. Hence, it is essential to read through the responsibilities section in the job description, or ask the interviewer, “What would a day in this role look like? Would this role spend most of the time exploring and visualizing data, or building models?” <b>The more specifics you learn about this role, the sooner you will learn whether this role matches your profile and interests. This helps you target the positions that are a better fit and increases your chance of landing the job you truly want.</b></p>
<p>You could find useful tips on how to improve personal branding and profile matching on career websites like indeed and linkedin. If you are looking for career advice tailored for data science and analytics, <a target="_blank" href="https://www.datacamp.com/careerservices">the career services of Datacamp</a> would be very helpful - here you can find personalized sessions from career coaches who are specialized in this area.   </p>
<p>Once you have targeted the right role for you, the next step is to show the company your passion for their business. This can be a little tricky for those who are just starting off as a data scientist or those who want to switch industries, as you may not have much experience in solving business questions in the industry that you’re applying for.</p>
<p><b>One thing we find really helpful is to work on projects that are relevant to the target industries and mention them in the resume and interview processes.</b> For example, if you’d never received training in finance but wanted to apply for a data scientist role at an investment bank, working on a guided project like this one <a target="_blank" href="https://www.datacamp.com/projects/738">Modeling the Volatility of US Bond Yields</a> on DataCamp can help you learn what kinds of business questions a data scientist working in finance is expected to solve.</p>
<p>Kaggle is also a good platform where you can find a lot of interesting competition and datasets. By working on these projects and talking about them during the interviews, you will not only build basic knowledge of that industry but also show the company that you are so interested in their business that you are spending your spare time exploring their use cases.</p>
<h1 id="tip-2-let-your-technical-expertise-shine-through-the-take-home-challenges">Tip #2: Let Your Technical Expertise Shine Through the Take-home Challenges</h1>
<p>Usually, the hiring process of data scientists involves a take-home challenge where candidates are given one or multiple datasets, and a few business questions to solve. Although the submission requirements may vary, the candidates are usually expected to share the code, models, and analysis output.</p>
<p><b>Many candidates see this as a great opportunity to showcase their technical skills.</b> R and Python are the main data science languages and both have their own must-have packages for data wrangling, statistical modeling, and machine learning e.g., pandas, sklearn and statsmodels for python, as well as tidyr, dplyr and caret for R. If you are new to data science, it is recommended to take a few career track courses like these on DataCamp: <a target="_blank" href="https://www.datacamp.com/tracks/data-scientist-with-python">Data Scientist with Python</a> and <a target="_blank" href="https://www.datacamp.com/tracks/data-scientist-with-r">Data Scientist with R.</a> In addition to an extensive range of courses, Datacamp also provides a workspace where one can practice with pre-written code templates and pre-configured datasets for those who are looking to gain some hands-on experience to close the learning-doing gap.</p>
<p>What can sometimes be underestimated is the role of data storytelling. <b>Good data scientists are also effective storytellers who can communicate their model outputs well enough to convince stakeholders and thus drive real changes.</b> As the saying goes, “a picture is worth a thousand words”. Therefore, make sure you include intuitive data visualization in your analysis report to help interviewers understand how you uncover the patterns in the data, as well as show how your model can create value. In addition to common packages such as matplotlib (Python), seaborn (Python) and ggplot2 (R), <a target="_blank" href="https://plotly.com/graphing-libraries/">plotly</a> is a graphing library worth trying if you want to build a web-based, interactive dashboard. This course on DataCamp could be helpful: <a target="_blank" href="https://www.datacamp.com/courses/introduction-to-data-visualization-with-plotly-in-python">Introduction to Data Visualization with Plotly in Python.</a></p>
<p><b>Alternatively, you may try no-code BI tools such as Tableau, Power BI, and Google Data Studio.</b> These tools give you two advantages. On one hand, they are popular visualization tools that are used by most non-tech stakeholders such as data analysts and product managers. Hence, mastering these tools shows that you can easily integrate with the data analytics stacks that the company uses. On the other hand, they provide more customization than Python or R packages do, which allow you to easily build a slide-style, interactive analysis report. If you are new to these tools, this <a target="_blank" href="https://www.datacamp.com/courses/introduction-to-tableau">Introduction to Tableau</a> course on DataCamp is a good starting point.</p>
<p><b>Last but not least, the delivery of your code also matters.</b> Unless otherwise specified, it is always a good idea to build your solution on Git and have all dependencies readily incorporated into your code. Nothing creates more frustration for interviewers than when they receive a zip file and try to run the code, yet only see error messages like “package XYZ can not be found”. Meanwhile, make sure your code comes with clean, proper documentation which makes it easy for people to follow your train of thought.</p>
<h1 id="tip-3-keep-in-mind-the-data-product-lifecycle-when-sharing-your-previous-project-experience">Tip #3: Keep in Mind the Data Product Lifecycle when Sharing Your Previous Project Experience</h1>
<p>Most of the time, candidates applying for a data science job are expected to share their previous project experience. A common pitfall is to spend too much time describing the technical effort e.g., how they clean data and fine-tune (hyper)parameters. This might lead to overloading your interviewers with the information they may not fully understand, and at the same detracts from the limited time they have to discover your business acumen and stakeholder management skills.</p>
<p>Hence, I would recommend that when preparing for the interview question about your previous projects, <b>make sure your answer follows the <a target="_blank" href="https://www.themuse.com/advice/star-interview-method">STAR framework and covers all stages</a>of the data product lifecycle, even if you are not directly involved in all of these areas</b>:</p>
<ul>
<li>Business goals and questions: What business problem(s) does your project try to solve? What goal(s) or KPI(s) does your project contribute to?</li>
<li>Data collection: What challenge(s) did you have in gathering the data and how did you tackle them?</li>
<li>Exploratory data analysis: How did you present your analysis result to non-tech stakeholders? What questions or criticisms did they raise and how did you respond to them?</li>
<li>Modeling and logic: Why did you choose the model(s) you finally implemented (discuss both technical and non-technical motivation)? What are the key limitations of your approach?</li>
<li>Testing and deployment: How did you test and deploy your model(s)?</li>
<li>Monitoring: What metrics did you choose to evaluate the model performance? What learnings did you have and how did you improve the model based on your learnings?</li>
</ul>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1641472767/image1_a1nwx4.png" /></center>
<center>Figure 1. Data Product Lifecycle</center>


<p>Moreover, don’t forget to highlight the different roles that were involved (e.g., product managers, data analysts, data engineers, QAs, and business operation managers), their responsibilities, and how you interacted with them. Hearing this, your interviewers are likely to be impressed with both your business sense and teamwork.</p>
<h1 id="conclusions">Conclusions</h1>
<p>With this blog post, we looked at the recent growth in the demand for data scientists. We then discussed a few tips which can help you crack data scientist interview questions—both technical and non-technical. If you aspire to land a data scientist job in the future, you may be interested in trying out these tips or building your way toward your dream offer by starting with an <a href="https://www.datacamp.com/courses">accredited data scientist course.</a></p>


https://www.datacamp.com/community/blog/blog-applying-for-data-science-jobs

Learn how to apply for the jobs you desire and set your self apart.  Learn what makes you stand out and what steps to take stand out from crowd. 

Tips to set your self apart and get the data science role of your desire

applying-for-data-science-jobs

Applying for data science jobs and how to set yourself apart 

<p>AN ANALYSIS OF TOP 7 TRENDING DATA SCIENCE CAREERS TO PURSUE</p>
<p>Examining the incredibly popular field that is data science</p>
<p>Data processing, analysis, and visualizations were done using R and its corresponding packages. Notebook and pertinent files used can be found <a target="_blank" href="https://app.datacamp.com/workspace/w/03312344-a7b0-47cf-b97d-06125fabcbd8/edit">here</a>.</p>
<p>According to the Merriam-Webster dictionary, data is factual information used as a basis for reasoning, discussion, or calculation. By this definition, data is basically any piece of collected information that can be used and further processed and analyzed to gain insights. It is commonly associated with computers as data is normally produced and stored in a computer, yet data has been around much longer than we might imagine.</p>
<h1 id="history-of-data">History of Data</h1>
<p>The earliest example of humans storing and analyzing data dates back to 18000 BCE, when it was discovered that prehistoric humans were using tally sticks, as a means of carrying out rudimentary calculations. These Paleolithic tribespeople marked notches on sticks and bones to keep track of their activities, such as trading and monitoring supplies. By 2400 BCE, the abacus, a device used in performing calculations, was invented in Babylon.</p>
<p>Throughout history, constant development of data collection, processing, and analysis was seen through numerous writings in stone tablets, clay, papyrus, wood, and paper scrolls. Eventually, as more forms of data were discovered, the need for processing, collecting, storing, and analyzing it also evolved.</p>
<p>As human society became more advanced, so did its requirement for processing data. In the 1800s, the census started taking place in the United States. The number of data points in the census grew exponentially to the point that the U.S. Census Bureau estimated that it would take years or even decades to collect and analyze all the data in the census. This was largely problematic since compiling and analyzing the current census data would only be completed when the next census was about to start or had already started. Fortunately, a young engineer and inventor named Herman Hollerith developed the Hollerith Tabulating Machine–an electromechanical tabulating machine which reduced the time needed to collect and analyze census data from years, to just mere months. Because of this, Hollerith is regarded as the father of modern automatic computation and would later become known for founding IBM.</p>
<p>Fast forward to the 1900s, and the invention of the computer. With the advent of a more powerful computing machine comes a more sophisticated requirement for data storage. Fritz Pfleumer, a German-Austrian engineer, invented a method of storing information magnetically on tape. Some principles of his invention are still being used today for digital data storage. In this era, the term “business intelligence” gained popularity as the need for emerging software, and systems for analyzing commercial and operational performance, quickly rose.</p>
<p>The revolution of data truly changed when Tim Berners-Lee created the World Wide Web, also known as the Internet, in 1989. This led to automated information sharing between people all over the world. This means that today more data is being shared, created, and stored, leading to new ways for collecting, using, and analyzing data.</p>
<h1 id="transition-to-big-data-">Transition to “Big Data”</h1>
<p>Due to the incredible amount of internet growth in the 1990s and the steady development of personal computers and computing devices in general, the number of devices online (and consequently the amount of data created) grew quickly.</p>
<p>While the idea of Big Data had been around even before the 1990s, it was only in 2005 when Roger Mougalas officially gave it a label. He described it as “a large set of data that is almost impossible to manage and process using traditional business intelligence tools.”</p>
<p>Big Data is a term used to describe the large volume of data–both structured and unstructured–that overwhelms organizations on a day-to-day basis. It encompasses the volume of information, the velocity or speed at which it is created and collected, and the variety or scope of the data points being covered.</p>
<p>Given the size and complexity of Big Data, the process of collecting, organizing, and analyzing it to discover patterns and other useful information has become part of helping a lot of organizations to make their business decisions. In turn this has given rise to data science–an interdisciplinary field which uses scientific methods, processes, algorithms, and systems from a large volume of data, to uncover patterns and enable business leaders to draw informed insights.</p>
<h1 id="what-is-data-science-">What is Data Science?</h1>
<p>According to IBM, data science is a multidisciplinary approach to extracting actionable insights from the large and ever-increasing volumes of data collected and created by today’s organizations. The field typically requires computer science and pure science skills as data scientists apply scientific methods in their approach, and use predictive analytics and artificial intelligence to extract insights from the data.</p>
<p>Nowadays, “data science” is often used by businesses and organizations as a catch-all term for the process of handling large amounts of data, whether it is preparing, cleaning, analyzing, or visualizing the data to reveal patterns. These are just some of the data science careers one can pursue:</p>
<ol>
<li><b>Data Scientist:</b><br>
<p>Data scientists need to be able to apply mathematics, statistics, and the scientific method; use multiple tools and techniques for cleaning and preparing data; perform predictive analytics and artificial intelligence; and explain how these results can be used to provide data-driven solutions to business problems. They require much more technical skills than data analysts. For starters, you may take data science-oriented courses like these on DataCamp: <a target="_blank" href="https://www.datacamp.com/courses/intro-to-python-for-data-science">Introduction to Python for Data Science</a> and <a target="_blank" href="https://www.datacamp.com/courses/free-introduction-to-r">Introduction to R</a>.</p>
</li>
<li><b>Data Analyst:</b><br>
<p>Data analysts collect, process, and perform statistical data analyses to arrive at meaningful conclusions for organizations. They transform and manipulate large data sets into usable forms, such as reports or presentations. They also aid in the decision-making process by looking into important patterns, and gleaning insights from the data which they can then effectively communicate to organizational leaders to aid in business decisions. These courses on DataCamp may help you kick-start your data analyst career: <a target="_blank" href="https://www.datacamp.com/courses/introduction-to-sql">Introduction to SQL</a> and <a target="_blank" href="https://www.datacamp.com/courses/exploratory-data-analysis-in-sql">Exploratory Data Analysis in SQL</a>.</p>
</li>
<li><b>Data Engineer:</b><br>
<p>Data engineers are responsible for preparation, processing, and managing gathered and stored data for analytical or operational uses. Like the traditional engineers, data engineers build and maintain data “pipelines” which connect data from one system to another, making information accessible for data scientists. Because of this, data engineers are required to understand several programming languages used in data science such as Python, R, and SQL. Topics related to data engineering like these are available on DataCamp: <a target="_blank" href="https://www.datacamp.com/courses/introduction-to-data-engineering">Introduction to Data Engineering</a> and <a target="_blank" href="https://www.datacamp.com/courses/data-engineering-for-everyone">Data Engineering for Everyone</a>.</p>
</li>
<li><b>Data Architect:</b><br>
<p>Data architects mainly design and create blueprints for data management systems that data engineers then build. Analogous to the traditional architects, data architects are the “visionaries” as they are responsible for visualizing and designing an organization’s data management framework. In addition, data architects improve the performance of existing systems, making sure they are accessible to database administrators and analysts. You may take courses related to data architecture like these that are available on DataCamp: <a target="_blank" href="https://www.datacamp.com/courses/aws-cloud-concepts">AWS Cloud Concepts</a> and <a target="_blank" href="https://www.datacamp.com/courses/database-design">Database Design</a></p>
</li>
<li><b>Business Intelligence (BI) Developer:</b><br>
<p>BI developers are specialized engineers who use software tools to transform data into useful insights that help business decisions. They are responsible for simplifying technical information for everyone else in the company to easily understand. In short, they create and run reports containing data they find using business intelligence tools, and transform the information into more layman terms. Courses on using tools related to business intelligence such as Microsoft Power BI and Tableau are available on DataCamp such as these: <a target="_blank" href="https://www.datacamp.com/courses/introduction-to-power-bi">Introduction to Power BI</a> and <a target="_blank" href="https://www.datacamp.com/courses/analyzing-data-in-tableau">Analyzing Data in Tableau</a></p>
</li>
<li><b>Statistician:</b><br>
<p>Given that statistics is one of the main foundations of data science, many statisticians can easily transition into the data science field. Statisticians are mainly responsible for the collection and handling of data. They decide what data they need and how to collect it. Additionally, they design experiments, analyze and interpret the data, and report conclusions. You may check-out these introductory courses to statistics on DataCamp: <a target="_blank" href="https://www.datacamp.com/courses/introduction-to-statistical-modeling-in-r">Introduction to Statistical Modeling in R</a> and <a target="_blank" href="https://www.datacamp.com/courses/introduction-to-statistics-in-spreadsheets">Introduction to Statistics in Spreadsheets</a>.</p>
</li>
<li><b>Machine Learning Engineer:</b><br>
<p>Machine learning engineers are another group of specialized engineers who are focused on researching, building, and designing artificial intelligence (AI) and machine learning (ML) systems to automate predictive models. Basically, they develop algorithms that use input data and leverage statistical models to predict an output, while continuously updating outputs as new data becomes available. DataCamp has numerous courses related to machine learning which you may find useful such as these: <a target="_blank" href="https://www.datacamp.com/courses/machine-learning-for-everyone">Machine Learning for Everyone</a> and <a target="_blank" href="https://www.datacamp.com/courses/machine-learning-with-caret-in-r">Machine Learning with caret in R.</a></p>
</li>
</ol>
<p>A quick job search online can give you an idea as to which of the data science career paths listed above is the most in demand. The graph below shows the job openings per career path according to <a target="_blank" href="https://www.indeed.com/jobs?q=data%20scientist&amp;vjk=ecfd94ad120e8423">Indeed USA</a> as of December 8, 2021.</p>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1641468289/image1_hntxle.png" /></center>

<p>Data architect appears to be the most in demand data science career path, due to their importance in creating data management systems which the other data science professionals then use. Next on the list is machine learning engineer, given the importance of utilizing artificial intelligence to predict outcomes in a lot of tech companies.</p>
<p>The least in demand are statisticians, mainly because a lot of the traditional statisticians are now becoming data scientists. This trend is expected to continue given how easy it is for statisticians to move from pure statistics to data science as they already possess the fundamental knowledge needed to become a fully-fledged data scientist.</p>
<h1 id="data-science-is-not-slowing-down">Data science is not slowing down</h1>
<p>The field of data science rose to immense popularity in the 2010s, especially when “Data Scientist” was touted by Harvard Business Review as the “sexiest job of the 21st century.” It became so popular that the title “Data Scientist” became a ubiquitous and trendy expression. While the term “sexiest job” does sound ridiculous at first, it mostly refers to how data scientists are not only in demand, but are also expensive to hire and difficult to retain.</p>
<p>While there is no question that data science is extremely popular nowadays, the better question is, will it remain this popular in the future? Based on employment projections, that does seem to be the case. Data from the 2020-2030 Employment Projections of the <a target="_blank" href="https://www.bls.gov/emp/tables/emp-by-detailed-occupation.htm">U.S. Bureau of Labor Statistics</a> shows that data science careers, which include statistics, data science, and other mathematical and science based occupations such as data engineering, will exhibit a very high growth rate in terms of percent change from 2020 to 2030. Statisticians ranked 14th overall, while data scientists and other mathematical science occupations ranked 31st overall out of 790 jobs included in the data.</p>
<p>While the shares of statisticians and data scientists from the total labor force are small compared to other occupations, those numbers are expected to increase in following years as the data science career path becomes more and more popular. The figure below shows how statisticians, data scientists, and other mathematical science occupations stack up against other jobs with high projected growth.</p>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1641468289/image3_bwn60b.png" /></center>


<h1 id="a-really-expensive-field">A really expensive field</h1>
<p>One major reason why data science is popular is because it is one of the highest paying jobs in the world. The figure below shows the range of salaries for 10 different occupations–including data scientists and data analysts–in New York City. The data was obtained from <a target="_blank" href="https://teleport.org/cities/new-york/salaries/">Teleport</a>, a website which aggregates data on living conditions (e.g., salaries) in different cities.</p>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1641468289/image2_qhdjq6.png" /></center>

<p>According to Teleport, data scientists had the 4th highest annual median salary in New York City at \$114,105, just behind C Level Executives and healthcare workers. In fact, in some other cities like Manila, data scientists rank as high as 2nd highest, just behind C Level Executives. This speaks volume as to how lucrative this job is. Data analyst jobs, whilst not as lucrative as data science positions, are still not to be slighted. At an annual median salary of $61,818, data analysts still earn around the average household income in New York City.</p>
<h1 id="ever-growing-in-the-job-market">Ever growing in the job market</h1>
<p>Another major reason why data science is popular is because of how organizations these days integrate the principles of data science in their day-to-day operations. The graph below shows the top 10 industries that involve data science in their work. The sample data of 8,000 data science oriented companies are extracted from <a target="_blank" href="https://www.diffbot.com/products/extract/testdrive/?token=210ced42a6e6d0cc4ac7f15885a94233.">Diffbot</a>, the world’s largest knowledge graph.</p>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1641468289/image4_spyov2.png" /></center>

<p>It comes to no surprise that Software Companies–including tech companies like Google, Apple, and Uber–came out on top. After all, the exceptional growth of big data was caused by the creation of the internet, which is closely tied to software and technology. Data science really is about processing a lot of information using various tools and technology.</p>
<p>Next on the list are financial services companies, which has been brought about by the rise of fintech companies. A portmanteau of “finance” and “technology,” fintech companies integrate technology and innovation in their services and offerings to improve their delivery to customers and disrupt traditional financial services. Since it involves handling a vast amount of data such as customer information, financial services companies saw the potential of data science tools to help streamline and optimize their processes and improve their services.</p>
<h1 id="in-conclusion-is-it-worth-pursuing-a-career-in-data-science-">In conclusion, is it worth pursuing a career in data science?</h1>
<p>With everything that has been explained above, the answer is a definite yes! As to which specific data science career path you should pursue, this depends primarily on your individual strengths and general interests. What is important is that any of the careers mentioned above are sure to be worthwhile.</p>
<p>A career path which is very lucrative and appears to show no signs of slowing down in terms of popularity, data science will continue to shape and influence how businesses and organizations operate for many years to come.</p>


https://www.datacamp.com/community/blog/blog-data-science-careers-to-pursue

Explore your options in the world of data science, the various options available with different types of roles. Get an idea how to start preparing yourself for each of the roles.

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An Analysis of the Top 7 Trending Data Science Careers to Pursue 

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Explore the importance of a data science degree. How to judge which is a good one and whether it is worth it. What are the alternatives?

Explore the opportunities with the degree and beyond the degree.  

A data science degree -  how important is it in 2022

A data science degree- how important is it in 2022

https://www.datacamp.com/community/blog/tips-to-build-your-data-scientist-resume

Learn how to stand out with your resume and the dos and don'ts for an impressive resume. How to clear the ATS systems and get to interview. Learn how best to present your resume as a fresher, as an associate or a senior. 

Learn how to land a job with an impressive data scientist resume for fresher, junior and senior roles.

Tips to build your data scientist resume

<p>As we close out this last chapter of 2021, DataCamp wants to do everything it can to put free, world-class data science education in the hands of disadvantaged people who need it the most. That’s why we’re extending the application deadline for the Q1 2022 DataCamp Donates Partner Cohort by a full week. The new deadline is January 31, 2022 at 11:59 ET. <a target="_blank" href="http://www.datacamp.com/donates/apply">Apply on behalf of your nonprofit organization</a> to gain one year of free Professional DataCamp for your entire community! Just take a look at some of the many success stories we get from <a target="_blank" href="http://www.datacamp.com/donates">DataCamp Donates</a> learners every week:</p>
<br><center><a target="_blank" href="https://datacamp.com/donates"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1640287208/DCD_logo_navy_bg_banner_prxwzi.png" /></a></center>
<br><p>“I was given a free license to use DataCamp through GDSC IBA with the purpose of learning skills that are currently in high demand all over the world. After one month of completing Python and SQL courses on DataCamp, I secured a job as a Data Analyst at Growthhopper. I am grateful to DataCamp for providing this opportunity!”</p><br>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1640284768/image2_bwiwlq.jpg" /></center><br>
<p>~ Shehroze Shahid, Student, Karachi, Pakistan</p>

<br><p>“I was shocked at how good DataCamp was for learning data science and programming. I found DataCamp to be an extremely great forum for learning as you get to actually try out the concepts you learn throughout the track. Regardless of how many data science blogs or books you read, nothing beats the learning value of actually having to program solutions and complete projects. DataCamp blew away my expectations and helped me land a job as a Grey Market Data Analyst at Nike.”</p><br>

<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1640284769/image3_oa4jeh.png" /></center><br>
<p>--Montana Bilger, US Army veteran, BreakLine learner, Vanvouver, WA</p>

<p>Just before Thanksgiving, we were delighted to welcome DataCamp Donates leaders and learners into our office in the Empire State Building to meet the DataCamp Leadership Team. “We were delighted to meet face to face with learners and leaders from Per Scholas and Women in Data —two of our most valued DataCamp Donates partners,” said Catalina Schveniger, Chief People Officer at DataCamp. “Learning that three of our guests were about to start brand new jobs, in part thanks to the skills they gained through DataCamp Donates, was extremely gratifying.”</p>

<p>“Learning more about databases and spreadsheets helps me in my new position as a Manager at Per Scholas,” said Helena Hill from New York, who attended the event. She went on to describe how her newfound knowledge affects her everyday life, even outside of work: “DataCamp has made me a far more intelligent consumer of information. I am far more aware of how easy it is to manipulate and misrepresent data in charts, for example, sometimes unintentionally. ” Tiernan Walsh, Senior Director of Business Solutions at Per Scholas, received over 60 applications for Helena&#39;s position and attributed her success to the knowledge she gained using DataCamp.</p>

<br><center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1640284769/image4_ew5gdi.jpg" />(From left to right) Rachel Provost (Women in Data), Nathaniel Taylor-Leach (Director of Social Impact, DataCamp), Helena Hill, Terrence X. Daniels, and Tiernan Walsh (Per Scholas)</center>

<h2 id="3-months-20-partners-2-500-lives">3 Months. 20 Partners. 2,500+ Lives</h2>
<p>Q4 was another stellar quarter for DataCamp Donates. We added 20 organizations from 17 countries. That translates to over 2,500 disadvantaged people DataCamp is helping to find better jobs in data science. To date, DataCamp Donates has given away over 28,000 subscriptions in just over a year—and we’re just getting started!!</p>
<p>Here are all the new and returning organizations we were proud to make DataCamp Donates Partners this last quarter:</p>
<div class="output_wrapper"><table>
<tbody>
<tr>
<td><a target="_blank" href="http://www.coamanila.com/orgpage/17?fbclid=IwAR3hgmBgvTwhWN_9Lcgy2j957u2oI3SHoQEPpJGr14AoN-rX_dqA782qfDE">Ateneo Statistics Circle</a></td>
<td><a target="_blank" href="https://www.datasciencenigeria.org/">Data Science Nigeria</a></td>
</tr>
<tr>
<td><a target="_blank" href="https://www.deeplearning.ai/">DeepLearning.AI</a></td>
<td><a target="_blank" href="https://developersinvogue.org/">Developers in Vogue</a></td>
</tr>
<tr>
<td><a target="_blank" href="https://www.energianaccion.org/">Energianaccion</a></td>
<td><a target="_blank" href="https://www.friendshipshelter.org/">Friendship Shelter</a></td>
</tr>
<tr>
<td><a target="_blank" href="https://gdg.community.dev/gdg-london/">GDG London</a></td>
<td><a target="_blank" href="https://gdsc.community.dev/university-of-the-philippines-diliman/">GDSC UP Diliman</a></td>
</tr>
<tr>
<td><a target="_blank" href="https://gdsc.community.dev/institute-of-business-administration-karachi/">GDSC IBA</a></td>
<td><a target="_blank" href="https://gdsc.community.dev/pamantasan-ng-lungsod-ng-maynila/?fbclid=IwAR2V0n-M63TJUaMbn2Se-dXana_uQytO9Xd8iuQSxb3F0lFhecTpnJHGMSQ">GDSC PLM</a></td>
</tr>
<tr>
<td><a target="_blank" href="https://gdsc.community.dev/sindh-madressatul-islam-university/">GDSC Sindh Madresstual Islam University</a></td>
<td><a target="_blank" href="https://globalhacks.net/">Global Hacks</a></td>
</tr>
<tr>
<td><a target="_blank" href="https://iec-enp.com/">Industrial Engineers Club</a></td>
<td><a target="_blank" href="http://www.internationalconsultingnetwork.org/">International Consulting Network (ICON)</a></td>
</tr>
<tr>
<td><a target="_blank" href="https://justicereskill.com/">Justice Reskill</a></td>
<td><a target="_blank" href="https://justicereskill.com/">MSAC MLSA UET Peshawar</a></td>
</tr>
<tr>
<td><a target="_blank" href="http://plazi.org/">Plazi</a></td>
<td><a target="_blank" href="http://www.shrdc.org.my/">Selangor Human Resource Development Centre</a></td>
</tr>
<tr>
<td><a target="_blank" href="https://teachforthephilippines.com/">Teach for the Phillippines</a></td>
<td><a target="_blank" href="https://yakera.org/">Yakera</a></td>
</tr>
</tbody>
</table></div>
<h2 id="become-a-dcd-partner-become-a-local-hero">Become a DCD Partner, become a local hero</h2>
<p>The only thing stopping you from providing a free year of DataCamp for your local community of aspiring data professionals is, well, you! If your organization provides professional development, job placement, or other social services, it is an ideal candidate to become a DataCamp Donates Partner. We also welcome applications from data science or coding community organizations as well as scientific research nonprofits.</p>
<p><a target="_blank" href="http://www.datacamp.com/donates/apply">Apply on behalf of an organization</a> to become a DataCamp Donates Partner by January 31, 2022. . Applications for Q2 2022 will open on February 14, 2022. We look forward to supporting you in 2022!</p>
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https://www.datacamp.com/community/blog/last-chance-in-2021-to-apply-for-datacamp-donates

Learn about all the new DataCamp Donates partners supporting disadvantaged communities around the world and how your organization can become our next partner!

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