<p><iframe width="560" height="315" src="https://www.youtube.com/embed/CexYyrtIAjw" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe></p>
<h2 id="can-you-tell-us-about-your-background-">Can you tell us about your background?</h2>
<p>My career began in 2010 in the Air Force working in the field of Security Forces, more commonly known as Military Police. I was involved in physically securing government facilities in South Korea and Japan,  and even got to guard Obama’s plane once! After leaving the Air Force, I worked in Telecommunications for a number of years as a help desk analyst before moving on to Cybersecurity in the banking domain.</p>
<p>Despite not working in a role that required data skills, I always tried to use them wherever I found myself working, occasionally to the annoyance of my boss, who told me “stick to your day job” 😂.  However, there were many times where being the team’s “data guy” was helpful in these roles, like generating informative Tableau reports for management, finding unused data and putting it to use, and identifying insights that were not fully realized before advanced analysis.  </p>
<p>More recently, I’ve gained a proper job as a data analyst on a data science team where I finally get to put these skills to use everyday. I found myself unemployed during the pandemic in November 2020 and saw this as a good chance to make a big career change to work with data full time. I went from cybersecurity analyst in banking to data analyst in the publishing industry.  DataCamp helped me gain skills that made me marketable enough to be able to make this career move and I plan to move to a data scientist role in the very near future!</p>
<p>I studied software development in school, but I’m a very big proponent of teaching myself the relevant skills I need online rather than throwing money at Higher Ed. I’ve found great value in free or affordable online resources like DataCamp. On the personal side, I enjoy participating in competitions on DrivenData.com and Kaggle, studying Japanese, playing guitar, and of course, knocking out modules on DataCamp.</p>
<h2 id="around-how-much-time-do-you-dedicate-to-learning-on-datacamp-">Around how much time do you dedicate to learning on DataCamp?</h2>
<p>About 2-3 hours a day.</p>
<h2 id="how-did-you-find-datacamp-and-why-did-you-choose-our-platform-over-other-online-learning-platforms-">How did you find DataCamp and why did you choose our platform over other online learning platforms?</h2>
<p>It’s been so long that I can&#39;t really remember how I found DataCamp. More than likely, I was just searching for data science learning resources. I do remember checking out DataQuest, and I didn’t go with them because their UI kind of hurt my brain. On DataCamp, everything is laid out in a very minimal and consistent way. It’s very easy to find what I’m looking for.</p>
<h2 id="how-has-datacamp-positioned-you-to-meet-your-professional-goals-">How has DataCamp positioned you to meet your professional goals?</h2>
<p>My new job mostly involves writing Python code. Code that wrangles, cleans, and gets data from point A to point B. Sometimes some SQL gets thrown in the mix, and DataCamp has provided 98% of all my real-world SQL knowledge and education that I couldn’t gain from my previous employment. DataCamp has certainly made my new job a breeze.</p>
<h2 id="what-are-the-skills-you-ve-learned-on-datacamp-that-have-proven-to-be-most-useful-">What are the skills you’ve learned on DataCamp that have proven to be most useful?</h2>
<p>Oh, that is a difficult one. I would say general machine learning skills. It took me a very long time to wrap my head around scikit-learn and how to do something as simple as using train_test_split(). It was very intimidating at first. After getting a lot  of guided repetition in, it all made sense overnight. I continue to learn new tips and tricks on the <a href="https://www.datacamp.com/tracks/machine-learning-fundamentals-with-python">Machine Learning Scientist with Python</a> career track that I continually apply to my real-world projects.  </p>
<p>A great example that I’m proud of is building a spam classifier for Bank of America’s Email Abuse team, within their Security Operations Center. Their job is to analyze suspicious emails that internal employees report to their team. They receive great volume of submissions and many of those are junk (or spam). To help automate the processing of these submissions, I built a Logistic Regression spam filter with an accuracy of 93%. Eventually, this was put into production and saved approximately 200 weekly analyst hours. This allowed their team to focus on more pressing tasks.</p>
<p>In my current job, I’ve recently had to build a complex data pipeline (in Python and SQL) that pulls data from an SFTP server, does intensive data cleaning  on it, joins that data on a table from a SQL Server database, then forwards the end result to Jira. DataCamp’s course <a href="http://datacamp.com/courses/writing-efficient-python-code">Writing Efficient Python Code</a> helped me make this script 10 times faster and the <a href="http://datacamp.com/tracks/sql-fundamentals">SQL Fundamentals</a> skill track really helped with the SQL portion of this script.</p>
<p>Currently, I’m working on the <a href="https://www.kaggle.com/c/nlp-getting-started/overview">Disaster Tweet Competion on Kaggle</a>. To assist with building my solution, I’m going through the <a href="https://datacamp.com/tracks/natural-language-processing-in-python">Natural Language Processing in Python</a> skill track for guidance while simultaneously applying these concepts to the Kaggle project.</p>
<h2 id="what-do-you-most-like-about-datacamp-">What do you most like about DataCamp?</h2>
<p>The relevancy, variety, and quality of courses. On relevancy: Many of the courses age well. After three years, I still look back on some of the older courses for help.</p>
<h2 id="do-you-have-any-advice-for-someone-just-starting-out-with-datacamp-">Do you have any advice for someone just starting out with DataCamp?</h2>
<p>Think of a data project that you’d like to do in real life, then identify what skills you need to do that project, then look on DataCamp for a course on that skill. Complete that course and then give that project a shot.</p>
<p>For new learners who don’t know where to start, begin with one of the career tracks that pique your initial interest. Then pivot to something else as you learn what is out there! 😊</p>
<p>I also recommend checking out DataCamp’s <a href="http://datacamp.com/webinars">webinars</a>, which have exposed me to many great minds in the field of data science.</p>
<p><em>Looking for a community of data enthusiasts for support in your learning journey? Join the <a href="https://support.datacamp.com/hc/en-us/articles/360001915993-The-DataCamp-Slack-Community-An-Overview">DataCamp Slack Community</a>, tell the world you’re a data enthusiast with a <a href="https://www.datacamp.com/community/blog/linkedin-covers">custom LinkedIn cover image</a>, and connect with Patrick <a href="https://www.linkedin.com/in/patrickkellyofficial/">on LinkedIn</a>.</em></p>


https://www.datacamp.com/community/blog/patrick

Q&A with Patrick Kelly, Professional Data Wrangler

Learner Spotlight: My Journey from Cybersecurity Professional to Data Analyst [Testimonial] | DataCamp

Learner Spotlight: My Journey From  Cybersecurity Professional to Data Analyst [Testimonial]

<p><center><a href="https://www.datacamp.com/jobs/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1612189119/Adnan_spotlight_lhubxv.png" /></a><br></p>
<h2 id="tell-us-about-your-path-to-joining-datacamp-">Tell us about your path to joining DataCamp.</h2>
<p>During my MBA program at INSEAD, I was looking for a quick way to pick up the SQL skills I needed for one of my economics courses. DataCamp’s ease of use impressed me, so I looked through INSEAD’s alumni directory to see if I could connect with someone at the company. That’s how I came across Jelle, DataCamp’s VP of Finance. After a quick coffee chat about DataCamp’s mission and its people, I was hooked. I found a Product Marketing role right up my alley and applied.</p>
<h2 id="what-did-you-like-dislike-about-the-onboarding-process-at-datacamp-">What did you like about the onboarding process at DataCamp?</h2>
<p>What particularly stood out to me were:</p>
<ul>
<li>My manager: I loved how hands-on my manager, Caroline Harris, was throughout the process. She took out an entire week to make sure another new hire and I were up to speed with all things DataCamp. This really helped in helping me hit the ground running.</li>
<li>The people: My onboarding at DataCamp revealed a collaborative and understanding nature across all employees. From coffee chats to the most menial questions, there&#39;s always someone to help.</li>
<li>The transparency: I know a lot of companies like to say they&#39;re transparent, but DataCamp truly is. From CEO meeting notes to sensitive financial metrics, every employee has access to these tools. This has built an environment of trust that has been key to getting me ramped up quickly. I plan to also speak with the founders to understand their perspectives on why they started the company.</li>
</ul>

<h2 id="what-do-you-like-to-do-in-your-spare-time-">What do you like to do in your spare time?</h2>
<p>I am a firm believer that a healthy body equates to a healthy mind. You can usually find me trying out the latest in fitness trends and experimenting with my diet. With all things lockdown, my latest activity has been biking. The empty London streets have been perfect for my new hobby 😃.</p>
<p>I&#39;m also an avid traveler! In the twelve months prior to Covid, I had the opportunity to visit 14 countries. I love exploring new places and learning about different cultures from my own. I’m looking forward to some travels once it’s safe to do so.</p>
<h2 id="what-s-something-interesting-you-ve-learned-recently-">What’s something interesting you’ve learned recently?</h2>
<p>You can build solid relationships virtually. I&#39;ve always been skeptical of working from home, especially starting a new job in a remote environment. My experiences at DataCamp have proved me wrong. With colleagues all over the globe, I see that everyone realizes the importance of not just work but also building social capital. Each meeting always has a social element about it—whether it’s celebrating a personal win, introducing a baby or even a pet. These initiatives help bring teams together and create a positive working environment.</p>
<h2 id="how-do-you-feel-about-datacamp-s-evolution-and-positioning-in-the-market-">How do you feel about DataCamp’s evolution and positioning in the market?</h2>
<p>First off, and I may be biased here, but I truly believe DataCamp has the best data learning platform on the market. I’d recently completed DataCamp’s <a href="https://www.datacamp.com/courses/introduction-to-sql">Introduction to SQL</a> course before coming on board, which equipped me with the tools I needed for my school project.</p>
<p>The <a href="https://www.datacamp.com/community/blog/new-brand">recent rebrand</a> has been a breath of fresh air. It’s brought a new lease to all of our content which has been great.</p>
<p>There&#39;s a lot more that needs to get done, but I&#39;m confident that DataCamp has the right product, and more importantly, the right people to succeed.</p>
<h2 id="what-would-you-tell-others-who-are-considering-working-for-datacamp-">What would you tell others who are considering working for DataCamp?</h2>
<p>Get in touch and talk to a DataCamper. Get to know the company personally and see if it&#39;s the right fit for you. We&#39;re making a tangible impact on people&#39;s lives while having fun doing it!</p>
<h2 id="what-s-the-weirdest-job-you-ve-ever-had-">What’s the weirdest job you’ve ever had?</h2>
<p>The summer during college, I was part of our alumni fundraising team. This job was commission-based, so I learned early on that outbound sales is not easy. I’ve had a lot of empathy for Sales teams thanks to that experience!</p>
<h2 id="anything-else-you-d-like-to-share-with-our-learners-">Anything else you’d like to share with our learners?</h2>
<p>DataCamp was founded on the epicenter of active learning by doing. Our unique, hands-on methodology of Assess-Learn-Practice-Apply makes us truly the best place to upskill in data fluency. In this increasingly data-oriented world, you don’t have to be on a data scientist track to benefit from what we offer.</p>
<p><em>Would you like to join Adnan at DataCamp? We’re currently hiring in New York; London; Leuven, Belgium; and remote locations. Check out our <a href="https://www.datacamp.com/jobs/">open roles</a>.</em></p>


https://www.datacamp.com/community/blog/adnan

Q&A with Adnan Ali Aamir, Product Marketing Manager at DataCamp

New Hire Spotlight: Ramping Up at DataCamp in a Remote Work Environment

<p>Click the image below to download our infographic on open source in data science. For a deeper dive on open-source technologies in data science, <a href="https://www.datacamp.com/resources/whitepapers/our-guide-to-open-source-in-data-science">explore our exclusive guide</a>.</p>
<p><center><a href="https://s3.amazonaws.com/assets.datacamp.com/email/other/Our+Guide+to+Open+Source+in+Data+Science.pdf"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1613754768/Our_Guide_to_Open_Source_in_Data_Science_kpfnbp.pdf" /></a></p>
<p><center><a href="https://www.datacamp.com/business/demo"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1603718763/banner_style_2_m573ef.png" /></a></p>


https://www.datacamp.com/community/blog/oss-infographic

Our infographic explains how the open-source revolution has transformed data science and maps out how to become fluent in data manipulation, data visualization,  machine learning, reporting and communicating data, and natural language processing.

Open Source in Data Science [Infographic] | DataCamp

Open Source in Data Science [Infographic]

<p><center><a href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1603718763/banner_style_1_cruuf7.png" /></a><br></p>
<h2 id="the-state-of-open-source-in-data-science">The state of open source in data science</h2>
<p>Open-source datasets and software have become a staple of data science. In recent years, innovative startups have open-sourced tools to enable data teams to do better work with data, such as <a href="https://github.com/apache/airflow">Airbnb’s Airflow workflow management platform</a> and <a href="https://github.com/amundsen-io/amundsen">Lyft’s data discovery engine</a>.</p>
<p>Publicly available datasets provide valuable training data for the latest machine learning algorithms. Open-source packages in Python and R enable data scientists to streamline their workflows. Data scientists can build frameworks that reduce the barrier to entry for working with data across the organization. The list goes on.</p>
<p><a href="https://www.datacamp.com/resources/whitepapers/our-guide-to-open-source-in-data-science">Open source</a> is catalyzing the development of data-driven and data-generating technologies, heralding a fourth industrial revolution (<a href="https://www.salesforce.com/blog/what-is-the-fourth-industrial-revolution-4ir/">Salesforce</a>). There are now more bytes of data than there are stars in the observable universe, and the amount of data in the world continues to double every two years, and organizations are increasingly using open source tools to make the most of this data.</p>
<h2 id="the-advantages-of-open-source-for-data-science">The advantages of open source for data science</h2>
<p>Just as the open-source revolution has led to a transformation of software development, so too has it been driving the development and democratization of data science and artificial intelligence. Open source has become a critical enabler of enterprise data science solutions, with the majority of data scientists using open-source tools (<a href="https://www.kaggle.com/kaggle-survey-2020">Kaggle</a>).</p>
<h3 id="open-source-is-more-secure">Open source is more secure</h3>
<p>Indeed, the world now largely runs on open-source solutions, whether we’re referring to Linux-powered data centers, Apache web servers, or web apps programmed in Java. The thriving communities that have grown around these solutions means they’re widely supported, which is good news not just from a support perspective, but also when it comes to security, updates, and optimizations.</p>
<p>Since open source promotes a community-based approach to data science and software development, popular projects get valuable input from hundreds or even thousands of industry experts. This means potential security vulnerabilities are identified and remediated more quickly, quality is guaranteed by widespread consensus, and new opportunities are more easily identified.</p>
<h3 id="open-source-provides-flexibility">Open source provides flexibility</h3>
<p>One of the key differentiators between proprietary and open-source software is flexibility and customization. Ultimately, proprietary software is controlled and managed by its developers, whereas open-source software has much more flexible licensing. This enables organizations to customize software for the workflows and provides them more control over the tools and solutions they develop (<a href="https://www.inc.com/john-boitnott/4-reasons-why-open-source-is-hands-down-best-for-business.html">Inc</a>). Moreover, open-source software is interoperable, meaning that it can work with a variety of data formats, and is designed for cloud and cloud-native technologies. Finally, open-source software enables organizations to avoid vendor lock-in and allows them to test and try software before committing to a solution (<a href="https://www.infoworld.com/article/3205889/is-open-source-good-for-business.html#:~:text=By%20its%20very%20nature%2C%20open,Freedom%20of%20choice.">InfoWorld</a>).</p>
<h2 id="open-source-promotes-employee-acquisition-and-retention">Open source promotes employee acquisition and retention</h2>
<p>One of the key aspects of the open-source revolution is how it intersects with talent acquisition and retention. Whereas skills pertaining to proprietary technologies lack mobility since they are only relevant in a specific closed environment, contributing to open-source projects makes it easier for organizations to attract and retain suitable talent. Open-source tools are already the standard in academic and industry circles, promoting skills-sharing and development across the board.</p>
<h2 id="upskill-your-teams-in-open-source-data-science">Upskill your teams in open-source data science</h2>
<p>While the benefits of open-source in data science are without doubt, learning the necessary skills still takes time and effort. Upskilling your team on popular open-source data science tools and packages is essential for future-proofing your business and for promoting a culture of continuous innovation, learning, and improvement.</p>
<p>The essential aspect of making the most of data, is to ensure that your team is equipped to analyze it efficiently and act upon it with smarter, more timely decision-making.</p>
<p><a href="https://www.datacamp.com/resources/whitepapers/our-guide-to-open-source-in-data-science">Download our whitepaper</a> to learn more about the benefits of open-source data science.</p>
<p><center><a href="https://www.datacamp.com/business/demo"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1603718763/banner_style_2_m573ef.png" /></a></p>


https://www.datacamp.com/community/blog/open-source-data-science

Open-source software is driving data democratization and closing technical skills gaps.

How Open Source is Driving the Future of Data Science | DataCamp

How Open Source is Driving the Future of Data Science

<p><center><a href="https://www.datacamp.com/workspace"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1613058313/Data_collaboration_trqi8m.png" /></a><br></p>
<h2 id="why-we-re-building-a-collaboration-product-https-www-datacamp-com-workspace-for-data-professionals-and-data-fluent-teams">Why we’re building <a href="https://www.datacamp.com/workspace">a collaboration product</a> for data professionals and data-fluent teams</h2>
<p>When we started DataCamp, we wanted to make it easy, enjoyable, and affordable for everyone to learn data science online. Today, we’ve reached over 7 million learners and actively helped increase the data fluency of more than 1,600 organizations. Over 150,000 subscribers have access to DataCamp today and even more for free through <a href="https://www.datacamp.com/community/blog/datacamp-donates">DataCamp Donates</a> and <a href="https://www.datacamp.com/community/blog/datacamp-donates">DataCamp for the Classroom</a>. However, almost all of them face significant struggles as they start actually doing data work.</p>
<h2 id="the-struggle-of-data-professionals-and-data-teams-and-why-it-matters">The struggle of data professionals and data teams—and why it matters</h2>
<p>Just like <strong><em>learning</em></strong> data science, <strong><em>doing</em></strong> data science work should be easy, enjoyable, and collaborative. Even as the number of data professionals has exploded, there are almost no tools that are easy to use, easy to scale, and that take into account the reality that different people prefer different technologies and integrated development environments, or IDEs.</p>
<p>As a consequence, data scientists today are not as productive as they could be. Let’s face it, many of us data scientists waste a lot of time doing infrastructure and engineering work, whether that’s setting up a machine, finding and accessing the right data, or deploying dashboards and reports. We hear these struggles from our learners and our customers, and we’ve faced many of these struggles ourselves at DataCamp.</p>
<p>Moreover, data scientists don’t work alone. Doing data science work in a team setting should not be as painful as it is today. Most tools used by data scientists lack even the most basic collaboration features. Shockingly, collaboration among data teams often happens by sharing code and data through email, Slack, or other messaging tools. Version control is done through tools that are tailored to the workflow of software engineers and are not intuitive for data scientists—and don’t get me started on the lack of quality control on most data teams. Knowing which analysis, dashboard, or report is still accurate is critical for a team. The struggles of data professionals are real and typically start on day one of joining a team.</p>
<p>Organizations also lose as they lack a central place where all insights are gathered and where data professionals can learn from each other. Some insights live in notebooks, some in PDF reports, yet others in proprietary analytics tools like Looker and Metabase, and the list goes on. This leads to insights getting lost and efforts being duplicated, and creates frustration with business users and leadership interacting with data professionals.  </p>
<p>This lack of proper tooling stands in the way of truly productive data professionals and data fluent organizations. While it is true that there’s been a lot of innovation for more BI-style users, this is often not true for data professionals who want to dig deeper and use the power of Python and R to generate their insights.</p>
<h2 id="what-datacamp-is-working-toward">What DataCamp is working toward</h2>
<p>We want to enable anyone, from anywhere and on any device, to access relevant data online, and to create visualizations, reports, and dashboards from their favorite tool or IDE and share it with fellow data professionals. We want to enable teams to seamlessly collaborate online in real time as well as asynchronously. We want teams to have basic version and quality control automatically built in. The end result should be a centralized insights layer for organizations of any size.</p>
<p>In other words, we want to make it as easy to do data science on your own (or your company&#39;s) data as it is to take a DataCamp course.</p>
<h2 id="how-we-ll-get-there">How we’ll get there</h2>
<p>Rome wasn’t built in a day. We’re currently building this product and are planning a phased rollout in the next 12 to 18 months.</p>
<p>First, we want to make it super easy for our learners to take their learnings from DataCamp—be it in the form of projects or courses—to a popular IDE like Jupyter. Working with the tools that are already widely used in industry and academia is a key step toward applying acquired skills in a realistic environment. In addition, users will be able to publish and share the work they’re doing in a workspace.</p>
<p>Next, we’ll make it seamless to connect your data and upload datasets, enabling users to start using DataCamp for day-to-day data science work. Furthermore, when users invite collaborators to review or edit their work, code and environment will be linked and self-contained, so the concerns around using the right package versions across projects and between different users becomes a thing of the past.</p>
<p>We’ll also focus on vastly improving real-time and async collaboration for data teams. Almost any team product today allows for real-time collaboration, commenting, and tagging. There’s no reason data teams should be deprived of that functionality, but they often are today.</p>
<p>Finally, as the product matures, we’ll continue to add features for organizations, leveraging the extensive user management architecture that we’ve already built for our enterprise learning platform. As an example, admins will only have to specify a database connection once, and manage who has access to which data. On the receiving end, data scientists will have the right data connections in place when they start their analyses.</p>
<p>Improving data fluency and democratizing data science is the core of DataCamp’s mission. <a href="https://www.datacamp.com/workspace">This product</a> is a key step toward achieving that goal, and why we also believe the basic version of this product should be free forever.</p>
<p><em>If you’re interested in changing the way data teams collaborate, email us at <a href="mailto:rocketship@datacamp.com">rocketship@datacamp.com</a>. You can also reach out directly to <a href="https://www.linkedin.com/in/filip-schouwenaars-b576b74a/">Filip Schouwenaars</a>, who’s taking the lead on building this new product, or our CTO, <a href="https://www.linkedin.com/in/dieterdemesmaeker/">Dieter De Mesmaeker</a>. We’re always looking for talented engineers to join our team. <a href="https://boards.greenhouse.io/datacamp/jobs/2582866">Apply now!</a></em></p>


https://www.datacamp.com/community/blog/collaboration

Doing data science work should be easy, enjoyable, and collaborative. That’s why we’re building a collaboration product for data professionals and data-fluent teams. 

DataCamp's new workspace product lets you start your own data analysis in seconds

<p>Welcome to the brand-new DataCamp Digest: a monthly roundup of key topics in the field of data. This month will cover trends for the new normal, the state of artificial intelligence in 2020, open-AI’s new DALL.E algorithm, data quality best practices, and more.</p>
<p><br><center><a href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1612888906/insights_qhc4kg.png" /></a></p>
<h3 id="-trends-for-the-next-normal-https-www-mckinsey-com-featured-insights-leadership-the-next-normal-arrives-trends-that-will-define-2021-and-beyond-mckinsey"><a href="https://www.mckinsey.com/featured-insights/leadership/the-next-normal-arrives-trends-that-will-define-2021-and-beyond">Trends for the next normal</a> | McKinsey</h3>
<p>2020 and the pandemic changed everything. 2021 will be a year of transition, from one “normal” to another. From accelerated digital transformation to the dawn of the future of work, what are the trends that will shape the new normal?</p>
<h3 id="-global-survey-on-the-state-of-ai-in-2020-https-www-mckinsey-com-business-functions-mckinsey-analytics-our-insights-global-survey-the-state-of-ai-in-2020-mckinsey"><a href="https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/global-survey-the-state-of-ai-in-2020">Global survey on the state of AI in 2020</a> | McKinsey</h3>
<p>As artificial intelligence adoption increases throughout the organization, which business areas are deriving the most value today? What separates leaders from the rest of the field, and what are the challenges still remaining to scaling machine learning in the enterprise?</p>
<h3 id="-the-modern-data-stack-past-present-and-future-https-blog-getdbt-com-future-of-the-modern-data-stack-dbt"><a href="https://blog.getdbt.com/future-of-the-modern-data-stack">The modern data stack, past, present, and future</a> | DBT</h3>
<p>Over the past decade, we’ve seen an explosion of tools in the modern data stack, enabling data scientists and analysts to get from data to insights faster. This article will take a close look at the history of the data tooling stack, its shortcomings, and how the next generation of data tools will be designed with data democratization in mind.</p>
<p><br><center><a href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1612888907/Editor_s_Picks_nj17hh.png" /></a></p>
<h3 id="-dall-e-creating-images-from-text-https-openai-com-blog-dall-e-openai"><a href="https://openai.com/blog/dall-e/">DALL.E: Creating images from text</a> | OpenAI</h3>
<p>OpenAI introduced a new deep learning algorithm based on GPT-3, trained to generate images from text descriptions. Check out how it performs in the article, and what an AI-generated illustration of a “baby daikon radish in a tutu walking a dog” looks like.</p>
<h3 id="-upskilling-for-shared-prosperity-https-www-weforum-org-reports-upskilling-for-shared-prosperity-world-economic-forum"><a href="https://www.weforum.org/reports/upskilling-for-shared-prosperity">Upskilling for Shared Prosperity</a> | World Economic Forum</h3>
<p>As we transition into the future of work, upskilling has never been more important. This World Economic Forum report outlines the need for major upskilling initiatives, the economic case for upskilling across a wide range of industries and locations, and what organizations can do today.</p>
<p><br><center><a href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1612889346/Inspiration2_wxr25i.png" /></a></p>
<h3 id="-the-people-ai-guidebook-https-pair-withgoogle-com-guidebook-pair"><a href="https://pair.withgoogle.com/guidebook/">The People + AI Guidebook</a> | PAIR</h3>
<p>This Google-developed guidebook offers a range of resources on best practices for scoping and evaluating AI projects for product managers, project managers, and designers. — PAIR</p>
<h3 id="-data-quality-at-airbnb-https-medium-com-airbnb-engineering-data-quality-at-airbnb-870d03080469-airbnb"><a href="https://medium.com/airbnb-engineering/data-quality-at-airbnb-870d03080469">Data Quality at Airbnb</a> | Airbnb</h3>
<p>In this series of articles, the Airbnb data science team outlines its data quality initiative and how it was able to define a shared gold standard for data quality across the organization. The series of articles provides a great overview of how to increase trust in data across the organization.</p>
<h3 id="-how-riskified-s-data-science-team-chooses-what-to-research-https-medium-com-riskified-technology-how-we-choose-what-to-research-57acb835fdd7-riskified"><a href="https://medium.com/riskified-technology/how-we-choose-what-to-research-57acb835fdd7">How Riskified’s data science team chooses what to research</a> | Riskified</h3>
<p>In this article, Riskified’s VP of Data Science Elad Cohen outlines how the data science team at Riskified identifies and prioritizes new directions in research and product development.</p>
<p><br><center><a href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1612888937/Tools_and_Techniques_sf5hut.png" /></a></p>
<h3 id="-best-of-machine-learning-with-python-https-github-com-ml-tooling-best-of-ml-python-lukas-masuch"><a href="https://github.com/ml-tooling/best-of-ml-python">Best of Machine Learning with Python</a> | Lukas Masuch</h3>
<p>This GitHub repository is a weekly updated list containing 840+ open-source projects and datasets in Python across 32 different categories ranging from machine learning, data visualization, recommender systems, data pipelines, streaming, and more.  </p>
<h3 id="-machine-learning-operations-https-ml-ops-org-innoq"><a href="https://ml-ops.org/">Machine Learning Operations</a> | INNOQ</h3>
<p>Want to know more about MLOps? Learn about the motivation for MLOps, best practices when managing end-to-end machine learning workflows, and the state of tooling in MLOps today.</p>
<h3 id="-anomaly-detection-in-sql-https-hakibenita-com-sql-anomaly-detection-haki-benita"><a href="https://hakibenita.com/sql-anomaly-detection">Anomaly detection in SQL</a> | Haki Benita</h3>
<p>This article deep dives into building a simple anomaly detection system that works with just high school-level statistics and SQL.</p>
<p><br><center><a href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1612889508/From_DataCamp_c6kasv.png" /></a></p>
<h3 id="-data-trends-2021-the-year-of-data-fluency-https-www-datacamp-com-resources-whitepapers-data-trends-and-predictions-2021-"><a href="https://www.datacamp.com/resources/whitepapers/data-trends-and-predictions-2021">Data Trends 2021: The Year of Data Fluency</a></h3>
<p>Read our white paper on how data science is headed for further democratization, and how 2021 and beyond will be defined by data fluency. If you prefer video over reading, you can watch our <a href="https://www.datacamp.com/resources/webinars/data-trends-2021">webinar</a>.</p>
<h3 id="-donating-25-000-datacamp-subscriptions-https-www-datacamp-com-community-blog-datacamp-donates-"><a href="https://www.datacamp.com/community/blog/datacamp-donates">Donating 25,000 DataCamp Subscriptions</a></h3>
<p>We’re doubling down on our commitment to donate free DataCamp subscriptions for those most impacted by the pandemic. Find out how you can help in this blog post.</p>
<p><br><center><a href="https://www.datacamp.com/business/demo"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1603718763/banner_style_2_m573ef.png" /></a></p>


https://www.datacamp.com/community/blog/digest-feb-2021

Introducing a brand-new series highlighting our favorite articles of the month on all things data.

DataCamp Digest February 2021: Trends for the New Normal | DataCamp

DataCamp Digest February 2021: Trends for the New Normal

<p><center><a href="https://www.datacamp.com/jobs/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1612474246/Jake_r1iznn.png" /></a><br></p>
<h2 id="tell-us-about-your-path-to-joining-datacamp-">Tell us about your path to joining DataCamp.</h2>
<p>I graduated from Ithaca College in December 2019 with a B.S. in Business Administration. When I graduated, I went directly into sales at a small third-party logistics company. After that, I gained experience in a remote sales position at an Injection molding company. When I found the Business Development Representative position at DataCamp, I immediately applied—and the rest is history. We’re actually looking to expand the team and hire more BDRs—<a href="https://boards.greenhouse.io/datacamp/jobs/2423593">here’s the link to apply</a>!</p>
<h2 id="what-excites-you-about-datacamp-">What excites you about DataCamp?</h2>
<p>I love what DataCamp offers—our product is super helpful and a great tool for learners all over the globe! I’m especially proud of our philanthropic initiatives, <a href="https://www.datacamp.com/community/blog/datacamp-donates">DataCamp Donates</a> and <a href="https://www.datacamp.com/groups/education">DataCamp for the Classroom</a>. These are two awesome programs that we are using to help communities in need.</p>
<h2 id="what-do-you-like-to-do-in-your-spare-time-">What do you like to do in your spare time?</h2>
<p>I love reading! I’m currently reading <a href="https://www.amazon.com/Atomic-Habits-Proven-Build-Break/dp/0735211299">Atomic Habits</a> by James Clear and am always looking for book suggestions. I meditate every single day, and I stay active with cycling, running, strength training, and yoga. Other than that, I love Star Wars and I play a lot of PlayStation.</p>
<h2 id="how-do-you-feel-about-datacamp-s-evolution-and-positioning-in-the-market-">How do you feel about DataCamp’s evolution and positioning in the market?</h2>
<p>DataCamp is in an amazing position. People all around the world are investing in themselves to learn all kinds of new skills, and one of the most in-demand skills is data science. We have an amazing <a href="https://www.datacamp.com/interactive-learning">platform</a> with awesome <a href="https://www.datacamp.com/instructors">instructors</a> and I believe we can make a difference in many people&#39;s lives. I’m excited for our big expansion goals for <a href="https://www.datacamp.com/community/blog/datacamp-2-0">DataCamp 2.0</a> and working with a growing team.</p>
<p><em>Would you like to join Jake at DataCamp? We’re currently hiring in New York; London; Leuven, Belgium; and remote locations. Check out our <a href="https://www.datacamp.com/jobs/">open roles</a>.</em></p>


https://www.datacamp.com/community/blog/jake

Q&A with Jake Sigman, Business Development Representative at DataCamp

New Hire Spotlight: Selling the Best Platform to Build Data Skills | DataCamp

New Hire Spotlight: Selling the Best Platform to Build Data Skills

<p><center><a href="https://www.datacamp.com/resources/webinars/data-science-is-driving-the-future-of-automotive"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1611953206/Automotive_CTA_rxhbht.png" /></a><br></p>
<p>Ford Motor Company’s Model T was first built in 1908 and achieved longevity for its low cost, durability, versatility, and ease of maintenance. It’s credited with “putting the world on wheels,” scaling global mobility through manufacturing efficiencies at a price that the average consumer could afford.</p>
<p>Today, the automotive industry is still on the leading edge of technology and transforming the way the world gets from point A to point B. In our <a href="https://www.datacamp.com/resources/webinars/data-science-is-driving-the-future-of-automotive">recent webinar</a>, Michael Crabtree, Lead Data Scientist at Ford Motor Company and instructor of our course <a href="https://www.datacamp.com/courses/credit-risk-modeling-in-python">Credit Risk Modeling in Python</a>, says the key difference is that its innovation is now driven by data science, not manufacturing.</p>
<blockquote>
<p>Innovation at Ford is now driven by data science—not manufacturing.</p>
</blockquote>
<h2 id="smart-cities-require-data-science-in-the-automotive-industry">Smart cities require data science in the automotive industry</h2>
<p>Similar to how the manufacturing scalability of the Model T brought mobility to the masses over 100 years ago, data science is scaling mobility for lower income communities today. It makes transportation easily accessible without the high cost of ownership and is facilitating this change for everyone, no matter their class, gender, or ability.</p>
<p>For instance, optimization algorithms can provide businesses with energy efficient vehicles to service rural communities for anything from Amazon deliveries to plumbing and food delivery. Data scientists are also working with reliability engineers to produce vehicles that assist differently abled communities.</p>
<p>These are just a couple of examples, but Michael states that there are almost endless use cases for data science, with many yet to be explored.</p>
<p><center><a href="https://www.datacamp.com/resources/webinars/data-science-is-driving-the-future-of-automotive"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1611953452/Screen_Shot_2021-01-25_at_4.17.55_PM_qdqjwx.png" /></a><br></p>
<h2 id="working-with-data-in-the-automotive-industry">Working with data in the automotive industry</h2>
<p>Because of the automotive industry’s maturity and wide reach, there are many opportunities for companies to <a href="https://www.datacamp.com/community/blog/data-driven-enterprise">rebuild around data</a>.</p>
<p>One application is working with data across different data systems and data types. Many data scientists are accustomed to using tabular data, which means the data is in a table format, similar to Excel. But automotive data scientists have a much greater variety of data to work with. For example, raw instrumentation data in the automotive industry is commonly stored as a stream of hexadecimal digits. They may also encounter data from intelligence systems in the form of images and sensor point clouds. And to understand why an autonomous vehicle behaves a certain way and how that varies among vehicle models, an automotive data scientist might combine point clouds with instrumentation data and join that to a set of tables.</p>
<p>Another opportunity is volume: The largest database Michael has created at Ford contains 80 billion rows, and queries in less than 10 seconds! Some of the real-time and transactional systems within the automotive industry process over 150 million records per day. Because so much automotive data is generated, very large data clusters are needed. Many companies in the automotive industry have data clusters in the petabyte (a million gigabytes) range.</p>
<h2 id="data-science-is-involved-in-every-step-of-the-automotive-product-lifecycle">Data science is involved in every step of the automotive product lifecycle</h2>
<h3 id="data-science-drives-product-development">Data science drives product development</h3>
<p>There are a lot of steps before a vehicle can be sold to a consumer.  Data science in automotive begins with product development. Data science is used for tasks like analyzing new model configurations and modeling component part reliability. Instead of building components and testing at each stage as an isolated system, data science supplements the process through simulation and analysis at scale.</p>
<h3 id="data-science-drives-excellence-in-manufacturing">Data science drives excellence in manufacturing</h3>
<p>Automotive data scientists also ensure that only high quality vehicles are sold. While engineers are capable of testing the quality of each vehicle, this has to be performed on an individual basis for each vehicle. Data scientists can analyze an entire population of parts, suppliers, and test data. They closely analyze the financial performance of suppliers, predict their ability to deliver on time given past performance, and use econometrics with regressions to check the economic conditions of supplier locations.</p>
<h3 id="data-science-drives-connected-and-autonomous-vehicles">Data science drives connected and autonomous vehicles</h3>
<p>One of the hottest topics in futurism today is connected and autonomous vehicles, which rely on deep learning models and sensor fusion algorithms. Data science is crucial to building these vehicles: It’s used to translate IoT indicators like oil life monitors, battery charge monitors, and full diagnostics instrumentation into actionable insights. For example, it’s not enough to simply detect a pedestrian—sensors must be able to discern where they’re walking to. Also important are safety systems, including driver protection and environmental safety.</p>
<p>The new connected systems for these vehicles provide new services—they connect with other vehicles, cities, and infrastructure. And we’re just at the beginning stages of exploring the potential of this market. The global connected vehicle market was around \$63 billion in 2019, and that market is set to almost quadruple to \$225 billion by 2027 (<a href="https://www.globenewswire.com/news-release/2020/06/18/2050256/0/en/Connected-Car-Market-to-Garner-225-16-Billion-by-2027-AMR.html">Allied Market Research</a>)!</p>
<h3 id="data-science-drives-sustainability-initiatives">Data science drives sustainability initiatives</h3>
<p>Sustainability is very important to all automotive manufacturers. Governments set targets for fuel efficiency, but each auto company has its own goals. And each vehicle has a different fuel efficiency, so data science is necessary to optimize the fuel efficiency of a company’s entire line of vehicles. So if a company wants to offer both a large gas-guzzling pickup truck and an electric car in its product line, automotive data scientists can perform an optimization to minimize the fuel consumption of the entire fleet while adhering to the company’s global sales targets. Optimization efforts can allow auto manufacturers to claim government credits for fuel efficiency. This has a threefold benefit of being good for the environment, providing more value for customers, and opening up a potential source of income.</p>
<h3 id="other-automotive-use-cases-for-data-science">Other automotive use cases for data science</h3>
<p>Beyond what we’ve mentioned, data science impacts so many other stages in the automotive lifecycle. In marketing and sales, data science predicts customer movement and churn. In service and customer analytics, data science improves the customer post-purchase experience and delivers improvements in product quality. To dive deeper into use cases for how data science is driving the future of automotive, <a href="https://www.datacamp.com/resources/webinars/data-science-is-driving-the-future-of-automotive">watch Michael’s webinar on demand</a>.</p>
<p><center><a href="https://www.datacamp.com/resources/webinars/data-science-is-driving-the-future-of-automotive"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1611953206/Automotive_CTA_rxhbht.png" /></a></p>


https://www.datacamp.com/community/blog/automotive-data-science

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