<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> 
Data engineering continues to be a top priority for enterprises, and in 2021, there will be exciting developments in the data infrastructure space. In a <a href="https://www.datacamp.com/resources/webinars/operationalizing-data-within-large-organizations">recent webinar</a>, Maksim Percherskiy, Data Engineer at The World Bank and former Chief Data Officer of the City of San Diego, highlighted three trends to watch out for in particular: data orchestration platforms, data discovery engines, and data lakehouses.
<h2 id="data-orchestration-platforms">Data orchestration platforms</h2>
Although orchestration platforms have been around for many years to manage computer systems and software, <a href="https://dzone.com/articles/data-orchestration-its-open-source-but-what-is-it">data orchestration</a> is a relatively new concept that abstracts data access across storage systems, virtualizes data, and presents data to data-driven applications. Data orchestration platforms help companies become more data-driven by combining siloed data from multiple data storage locations and making them usable. Examples include <a href="https://airflow.apache.org/">Apache Airflow</a>, <a href="https://www.prefect.io/">Prefect</a>, <a href="https://luigi.readthedocs.io/en/stable/">Luigi</a>, and <a href="https://www.stitchdata.com/">Stitch</a>, which are compatible with modern software approaches like version control, DevOps, and continuous integration.
DataCamp’s course <a href="https://www.datacamp.com/courses/introduction-to-airflow-in-python">Introduction to Airflow in Python</a> is a great place to start to learn how to implement and schedule ETL and data engineering workflows in an easy and repeatable way.
<h2 id="data-discovery-engines">Data discovery engines</h2>
It makes sense that as data increases, companies will invest more time in enabling their teams to find the data they need, document it, and reduce rework. Data discovery engines like <a href="https://eng.lyft.com/amundsen-lyfts-data-discovery-metadata-engine-62d27254fbb9?gi=a4af847eb7fe">Lyft’s Amundsen</a> and <a href="https://eng.uber.com/databook/">Uber’s Databook</a> aim to improve the productivity of data users by providing a search interface for data. These tools rely on metadata, which support productivity and compliance by allowing data infrastructure to scale as companies grow. The goal of data discovery is to make data more FAIR: findable, accessible, interoperable, and reusable.
<center><a href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610377093/datadiscoveryengines_pi2uj7.png" /></a> 
<h2 id="data-lakehouse">Data lakehouse</h2>
There are different use cases for <a href="https://www.datacamp.com/community/blog/data-lakes-vs-data-warehouses">data lakes versus data warehouses</a>. Each is designed for different purposes and for different end users. For example, data warehouses are typically used by analysts for the purpose of collecting business intelligence—they contain flat files that have been explicitly processed for their work. On the other hand, data lakes are set up and maintained by data engineers who integrate them into data pipelines. Data scientists work more closely with data lakes as they contain data of a wider and more current scope.
Data lakehouses are exactly what they sound like: a combination of data lakes and data warehouses. Companies like <a href="https://delta.io/">Delta Lake</a> and <a href="https://www.snowflake.com/guides/what-data-lakehouse">Snowflake</a> have created solutions to provide a single source of truth for data that combines the benefits of data lakes and data warehouses. Data lakehouses implement data warehouses’ data structures and management features for data lakes, which are typically more cost-effective for data storage. At the same time, they retain the schema and versioning of the data. With data lakehouses, data scientists will be able to conduct both machine learning and business intelligence.
<center><a href="https://databricks.com/blog/2020/01/30/what-is-a-data-lakehouse.html"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610377091/datalakehouse_dv35im.png" /></a>
<h5 id="source-databricks-https-databricks-com-blog-2020-01-30-what-is-a-data-lakehouse-html-">Source: <a href="https://databricks.com/blog/2020/01/30/what-is-a-data-lakehouse.html">Databricks</a></h5>
All three of these trends will be crucial for enterprises to scale data infrastructure in 2021. They’re useful for companies that were built around data as well as for those that are struggling to sustainably integrate data in their workflows. <a href="https://www.datacamp.com/community/blog/data-driven-enterprise">Find out more</a> about the challenges large companies face to operationalize their data and become data-driven.
<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>

https://www.datacamp.com/community/blog/data-infrastructure-trends

Get your data engineering function ahead of the curve with orchestration platforms, data discovery engines, and data lakehouses.

Top 3 Trends in Data Infrastructure for 2021 | DataCamp

Top 3 Trends in Data Infrastructure for 2021

<center><a href="https://www.datacamp.com/tracks/tableau-fundamentals"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610375720/TableauCTA_v2qbt7.png" /></a></center> 

Tableau is a business intelligence (BI) platform that functions like a supercharged Microsoft Excel. Its user-friendly, drag-and-drop functionality makes it possible for anyone who interacts with data to analyze and create presentation-ready visualizations—from data newbies to analysts, and even business leaders. You definitely don’t need to be a seasoned data scientist to use Tableau!

<h2>Which companies use Tableau?</h2>
Tableau’s roster of customers is a who’s who of the business world, including well-known brands such as Amazon, Experian, and Unilever. But it’s not just global giants using Tableau to democratize their data—over <a href="https://techcrunch.com/2019/06/10/salesforce-is-buying-data-visualization-company-tableau-for-15-7b-in-all-stock-deal/">86,000 businesses</a> are using Tableau to extract and share insights from their data.

<h2>Certification overview</h2>

<center><CALLOUT BOX>
<a href="https://www.tableau.com/learn/certification/desktop-specialist">Tableau Desktop Specialist</a> 
Fee: $100 
Title valid for: No expiration 
</CALLOUT BOX></center> 


Tableau recommends that you have at least three months’ product experience before taking the Desktop Specialist exam. If you don’t yet have this experience, DataCamp recommends that you prepare for the exam by completing our online <a href="https://www.datacamp.com/tracks/tableau-fundamentals">Tableau Fundamentals</a> skill track.

The exam will take place on GoToMeeting or Zoom, and you will be asked to set up your workspace using Google Chrome and confirm that your connection speed meets Tableau’s requirements. Additionally, you will be required to:

<ul>
<li>Present photo identification to the exam proctor via webcam</li>
<li>Close programs, tabs, and remove any paperwork that may help during your exam</li>
<li>Demonstrate to the proctor that you are alone in your room via webcam</li>
<li>Agree to being monitored via webcam for the duration of the exam</li>
</ul>

<a href="https://mkt.tableau.com/files/Tableau-Certification-4-steps-to-exam-success.pdf">View the full exam setup requirements</a>

Just like the Tableau learning experience <a href="https://www.datacamp.com/tracks/tableau-fundamentals">on DataCamp</a>, the exam is completed using a Windows virtual machine that has Tableau Desktop installed—this may involve a certain amount of toggling between the question and virtual desktop screens which may result in a slightly smaller screen size than you may be used to. It’s also worth noting that you may not have any other windows or programs open for the duration of the test other than those required for the assessment—just like exams in school, you can’t have any notes hidden in your calculator sleeve. The exam is scored automatically and a passing score of 70% or more is required to obtain your certification.

You can register and book your exam on the <a href="https://www.tableau.com/learn/certification/desktop-specialist">Tableau Product Certification Exam center</a>, managed by Loyalist Exam Services (LES). You can also reschedule your exam using this site.

<h2>Training Resources</h2>
At DataCamp, all our instructor-led courses are fully interactive, with no installation or prior experience required. You will also receive a statement of accomplishment which you can also share on your LinkedIn profile upon completion. Please note that DataCamp’s statement of accomplishment is not the same as the Tableau Desktop Specialist certification:

<a href="https://www.datacamp.com/tracks/tableau-fundamentals">Tableau Fundamentals</a>: 14 hours. 4 Courses
Gain the essential skills you need to confidently use Tableau and prepare to pass the Tableau Desktop Specialist certification. No prior experience required.

<ul>
<li><a href="https://www.datacamp.com/courses/introduction-to-tableau">Introduction to Tableau</a>: 4 hours 
Learn how to use Tableau’s user-friendly drag-and-drop functionality to quickly clean, analyze, and visualize your team’s data.</li>
<li><a href="https://datacamp.com/courses/analyzing-data-in-tableau">Analyzing data in Tableau</a>: 4 hours 
Create detail-rich map visualizations, configure date and time fields to show trends over time, and extend your data using Calculated Fields.</li>
<li><a href="https://datacamp.com/courses/creating-dashboards-in-tableau">Creating Dashboards in Tableau</a>: 4 hours 
Apply dashboard best practices, add interactive or explanatory elements, and use actions to make your dashboard fully interactive.</li>
<li><a href="https://www.datacamp.com/courses/connecting-data-in-tableau">Connecting Data in Tableau</a>: 4 hours 
Discover how to connect Tableau to different data sources and prepare the data for a smooth analysis.</li>
</ul>

Tableau also provides an excellent choice of learning resources you can use to prepare for the exam:

<ul>
<li><a href="https://www.tableau.com/learn/training/20204">Tableau Training Videos</a></li>
<li><a href="https://mkt.tableau.com/files/DesktopSpecialist_ExamGuide.pdf">Desktop Specialist Exam Prep Guide (PDF)</a></li>
<li><a href="https://community.tableau.com/s/explore-forums?_ga=2.195627941.886887347.1610106578-1596736181.1607685378">Tableau community forums</a> and <a href="https://community.tableau.com/s/groups?_ga=2.195627941.886887347.1610106578-1596736181.1607685378">user groups</a></li>
</ul>

Found this article useful? If so please share on <a href="https://www.linkedin.com/company/datacampinc/">LinkedIn</a>, <a href="https://twitter.com/DataCamp">Twitter</a>, or <a href="https://www.facebook.com/datacampinc/">Facebook</a>.

 <center><a href="https://www.datacamp.com/tracks/tableau-fundamentals"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610375720/TableauCTA_v2qbt7.png" /></a></center>

https://www.datacamp.com/community/blog/Tableau-desktop-specialist-certification

Add Tableau to your data analyst skill set. Learn to use this BI platform and pass the Desktop Specialist Certification exam with DataCamp.

Pass Tableau’s Desktop Specialist Certification | DataCamp

Tableau Desktop Specialist Certification: Learn How to Use Tableau and Ace the Exam

In a year marked by world-altering events, DataCamp learners have found ways to double down and invest in themselves by building data fluency. Below are some of the milestones we’ve reached together this year—click the image to download the PDF.
Many thanks to the entire #DataCampCommunity for your support this year. We encourage you to join the <a href="https://support.datacamp.com/hc/en-us/articles/360001915993-The-DataCamp-Slack-Community-An-Overview">DataCamp Slack Community</a> to get plugged in with other learners in 2021.
<center><a href="https://s3.amazonaws.com/assets.datacamp.com/email/other/DataCamp+2020+by+the+numbers.pdf"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1609947989/DataCamp_2020_by_the_numbers_ewpxzf.png" /></a>

https://www.datacamp.com/community/blog/2020-year-in-review

Discover DataCamp’s major milestones from the past 12 months and review our top five tracks, assessments, and much more.

DataCamp’s 2020 Year in Review

One of the best ways to stand out on LinkedIn is to use a custom LinkedIn cover image. The majority of LinkedIn users stick with the default LinkedIn cover image, which is a big missed opportunity. It’s easy to inject some personality into your profile and set yourself apart with an image that showcases your professional identity or aspirations.
That’s why we’ve created custom LinkedIn cover images for some of the most common data roles and identities. This is what mine looks like as a reference:
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040765/LinkedIn_Cover_Sample_lr6uj2.png"/> 
If you’d like to update your LinkedIn profile like mine, just click the description below that best matches your identity to download the cover image:
<ul>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040100/Linkedin_Cover_-_Data_Enthusiast_qgfd0z.png">Data Enthusiast</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040676/Linkedin_Cover_-_Data_Analyst_cb4umx.png">Data Analyst</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040100/Linkedin_Cover_-_Data_Engineer_enf4cd.png">Data Engineer</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040100/Linkedin_Cover_-_Data_Professional_vowtyw.png">Data Professional</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040100/Linkedin_Cover_-_Data_Architect_vomzkz.png">Data Architect</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040553/Linkedin_Cover_-_Business_Intelligence_Analyst_pwivdt.png">Business Intelligence Analyst</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610380543/Linkedin_Cover_-_Quantitative_Analyst_zkq29v.png">Quantitative Analyst</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610039229/Linkedin_Cover_-_Database_Administrator_virz8n.png">Database Administrator</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610039227/Linkedin_Cover_-_Machine_Learning_Engineer_nv0ytj.png">Machine Learning Engineer</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610039224/Linkedin_Cover_-_Machine_Learning_Scientist_dwrdkl.png">Machine Learning Scientist</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040100/Linkedin_Cover_-_Data_Scientist_py4mog.png">Data Scientist</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040100/Linkedin_Cover_-_Data_Architect_vomzkz.png">Data Architect</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040550/Linkedin_Cover_-_Statistician_wlxcwh.png">Statistician</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040551/Linkedin_Cover_-_Business_Analyst_typawx.png">Business Analyst</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040100/Linkedin_Cover_-_Data_and_Analytics_Manager_i4ozqa.png">Data and Analytics Manager</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610039231/Linkedin_Cover_-_Data_Storyteller_ygvafx.png">Data Storyteller</a></li>
<li><a href="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1610040101/Linkedin_Cover_-_Data-Driven_t1tqsx.png">Data-Driven</a></li>
</ul>

To add the image as your background photo on LinkedIn:
<ul>
<li>Click the Me icon at the top of your LinkedIn homepage.</li>
<li>Click View profile.</li>
<li>Click the Camera icon on the top right corner of your introduction card.</li>
<li>Click Upload photo to select an image from your computer, and click Open.</li>
<li>Click Apply. The photo will upload automatically. There’s no need to reposition the image.</li>
</ul>

For additional assistance, view the <a href="https://www.linkedin.com/help/linkedin/answer/49960/add-or-change-the-background-photo-on-your-profile?lang=en">LinkedIn help article</a>.
Let us know what you think about these banners on <a href="https://www.linkedin.com/company/datacampinc/">LinkedIn</a>, <a href="https://twitter.com/DataCamp">Twitter</a>, <a href="https://www.facebook.com/datacampinc/">Facebook</a>, or <a href="https://www.instagram.com/datacamp/">Instagram</a>! We hope this will be a fun way for you to express your love of data.

https://www.datacamp.com/community/blog/linkedin-covers

Is your New Year’s resolution to land a data role or get to the next level in your career? Tell the world that you’re a data enthusiast by updating your LinkedIn cover image.

New Year, New LinkedIn Cover Image

Last August, DataCamp’s VP of Product Research, Ramnath Vaidyanathan, hosted a <a href="https://www.datacamp.com/resources/webinars/scaling-data-science-at-your-organization-part-1">three-part webinar series</a> on scaling data science with our IPTOP framework. The IPTOP framework breaks down every organizational lever to democratize data science and become data fluent organization-wide.
IPTOP stands for Infrastructure, People, Tools, Organization, and Processes. The three-part webinar series goes into great detail on how organizations can scale each of these levers to democratize data science and become data fluent in the process. Here’s a breakdown of each of those levers:
<center><a href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1608306088/Demand_Gen_Themes_2021_eebx0u.png" /></a>
<h2 id="1-infrastructure">1 - Infrastructure</h2>
The goal of any data strategy is to transform raw data into insights and decisions. This requires organizations to collect, record, and store their data safely and efficiently to be accessible by all. As such, this involves understanding best practices and frameworks for enabling data access, ensuring data governance, clarifying data lineage, and more.
<h2 id="2-people">2 - People</h2>
People are arguably the most critical lever in the framework, as organizations won’t make the most of their data if their members don’t have the skills to work with data. This is why cultivating the necessary data skills <a href="https://www.datacamp.com/resources/webinars/l-and-d-leaders-data-fluency">across every persona</a> in an organization is imperative for democratizing data science and becoming data fluent.
<h2 id="3-tools">3 - Tools</h2>
While infrastructure enables organizations to deliver insights from data, tools facilitate and incentivize a common data language across the organization. This is why it’s necessary to understand the range of possible tools that can be used for a specific task and invest and build tools that lower the barrier to entry for data science work.
<h2 id="4-organization">4 - Organization</h2>
An essential dimension of scaling data science is how data professionals are organized. Given that reporting structures and agendas drive work in most firms, the organizational structure must set up your company for sustainable success. As such, setting up and organizing data science talent within an organization requires careful consideration.
<h2 id="5-processes">5 - Processes</h2>
Finally, scaling data science requires alignment on conventions, best practices, and processes. Fostering alignment is essential to facilitating collaboration and avoiding a siloed organization. This allows all teams to work together and seamlessly communicate under a common data language.
Last week, we released our <a href="https://www.datacamp.com/resources/whitepapers/data-trends-and-predictions-2021">data trends and predictions for 2021</a>. Our predictions touch upon every lever in the IPTOP framework, from enabling more robust data access through increased cloud adoption and metadata tools (Infrastructure), a higher commitment to data upskilling (People), more collaborative and robust tooling (Tools), emergent roles for managing machine learning models in operation (Organization), and finally, best practices in data storytelling and visualization (Processes).
This is why we’re excited to renew our commitment to bringing the latest and most important insights from data science practitioners and leaders on how to best scale data science and become data fluent.
In 2021, we’ll be hosting a series of monthly webinars tackling how different industries can leverage data science, how organizations can govern their data and enable better data access, best practices to upskill people for data science, how to lower the barrier to entry to working with data with modern tooling, how to organize and hire the best data science talent, and how to set up processes to become data-driven, and more.
Keep an eye on our <a href="https://www.datacamp.com/webinars">Upcoming Events</a> page to stay in the loop—see you in 2021!

https://www.datacamp.com/community/blog/data-fluency-2021

DataCamp is hosting a monthly webinar in series in 2021 focused on scaling data science and building organization-wide data fluency with our IPTOP Framework.

Data Fluency in 2021

The past year has been tumultuous, with many lessons still being revealed today. The Covid-19 crisis has accelerated digital transformation, forcing incumbent organizations to digitize their processes, modernize their business models, enable data access, and upskill their workforce for a data-driven age (<a href="https://www.youtube.com/watch?v=FoIOFEp2HiY">Microsoft</a>). Digital, data-driven organizations like Zoom, Amazon, and PayPal benefited from the new normal (<a href="https://www.ft.com/content/844ed28c-8074-4856-bde0-20f3bf4cd8f0">Financial Times</a>) and solidified their places as leaders in their respective markets. The Covid-19 crisis has also proven the need for everyone to be data-fluent, informed citizens (<a href="https://www.dataversity.net/the-dangers-of-data-illiteracy-coronavirus-and-data-distortions/">Dataversity</a>), as data can be used to inform and misinform us on the state of the pandemic.
This year, we stand on the precipice of a great acceleration. Organizations across the world are looking to increase their digital resilience, and become more data-driven in the process. The data science revolution has always made the impossible possible. With data science methodologies and technologies, specialized teams have worked on solving important problems like self-driving cars, algorithmic trading programs, and protein folding. However, the real data science revolution <a href="https://www.datacamp.com/resources/webinars/scaling-data-science-at-your-organization-part-1">makes the possible widespread</a>, where everyone in an organization can understand data, communicate insights from that data, and make more informed decisions with data. It’s about creating data fluent organizations and societies, where everyone is equipped with the necessary skills they need to be informed, citizens, and employees.
Over the next year and beyond, we will see better tooling across the spectrum of data fluency, higher emphasis on skills, and richer, easier access to data across the organization.
<center><a href="https://www.datacamp.com/resources/whitepapers/data-trends-and-predictions-2021"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1608132378/2021_trends_CTA_gb5log.png" /></a> 
<center><a href="https://s3.amazonaws.com/assets.datacamp.com/email/other/Data+Trends+2021_+The+Year+of+Data+Fluency.pdf"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1608133443/Data_Trends_2021__The_Year_of_Data_Fluency_mhcmlb.pdf" /></a> 
If you want to dive deeper into our trends for 2021, download our white paper.
<center><a href="https://www.datacamp.com/resources/whitepapers/data-trends-and-predictions-2021"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1608132378/2021_trends_CTA_gb5log.png" /></a>

https://www.datacamp.com/community/blog/2021-data-trends

In 2021 and beyond, we’ll see better tooling across the spectrum of data fluency, higher emphasis on skills, and greater access to data across organizations.

Data Trends 2021: The Year of Data Fluency

I discovered the DataCamp giveaway from their <a href="https://www.datacamp.com/community/blog/free-datacamp-subscriptions">blog post</a> looking for nonprofit partners to make data science education accessible to everyone. I’d originally wanted this partnership for my local data science community at AI+ Obafemi Awolowo University, but we weren’t eligible because we didn&#39;t have a website. Luckily, we were a sub-community of <a href="http://www.datasciencenigeria.org/">Data Science Nigeria</a>, which was already <a href="https://www.datacamp.com/community/blog/data-science-nigeria">involved in the giveaway</a>, so we were able to get free access to DataCamp after all.
Data science is a booming field and many even go as far as to say that data is the new oil. The opportunity offered by DataCamp was too good to pass up, so I forwarded the registration link to all the communities that I know of that share the vision of empowering young people to acquire digital skills. Some of the communities, like <a href="https://ingressive.org/">Ingressive For Good</a> and <a href="https://dscoau.com/">Google Developer Student Club Obafemi Awolowo University</a>, have since become partners of DataCamp, and I’m happy to see so many people learning data science through my referrals.
<center><a href="http://www.datasciencenigeria.org/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1607358970/Felix_Ayoola_bavwtw.png" /></a> 
I particularly enjoy using DataCamp because of its simplicity and the way lessons are broken down. I’ve come to more deeply understand libraries like <a href="datacamp.com/community/blog/how-to-learn-pandas">pandas</a> and Matplotlib. As of today, I&#39;m taking my fifth course on DataCamp and I can say it’s been a great journey. The assessments are my favorite—they’re not too complex and they help me to be able to recollect and practice the lessons learned in a step-by-step approach.
I like to take the courses early in the morning before 6 AM because it allows me to use a lower-cost midnight data subscription to take these courses. One thing westerners might not realize about Nigeria and other countries in Africa is that Internet access is charged by the megabyte. That’s why it’s truly commendable that DataCamp addresses this additional hurdle by making its course videos and slides available to download for offline viewing. Combined with the fully-featured mobile app and their generous donation of thousands of subscriptions to disadvantaged communities, DataCamp is making it radically easier for citizens of developing nations to still attain world-class data science training, even when a computer and Internet access are out of reach.
<blockquote>
DataCamp’s impact on my community has been huge, and I urge others to take advantage of this amazing opportunity. —Felix Ayoola
</blockquote>
As a graphic designer, what really interests me about data science is that it&#39;s applicable in every field. In fact, I think everyone should learn the basics of data science regardless of your field or domain. Let me give a graphic design use case to demonstrate this: When I started designing, I taught myself, so I wasn&#39;t able to learn the basics first and instead simply used the tools I could find, like <a href="http://remove.bg">remove.bg</a> to remove pictures from backgrounds. Understanding data science has helped me to appreciate websites that match fonts, create color palettes, and other awesome graphic design tools that are powered by data science. To ease your way into data science, DataCamp’s <a href="https://www.datacamp.com/courses/data-science-for-everyone">Data Science for Everyone</a> course is a great place to start.
I&#39;m really interested in how to use data science to create plots for graphic design, saving Matplotlib figures in .svg format enables editing with vector softwares like Adobe Illustrator or Figma. I&#39;m transitioning into product design and in the process, I’ve seen how data is used to create products that solve problems, like Netflix’s recommendation engine. Data science is a powerful tool to create amazing graphics, and there’s a ton of opportunity to leverage data science to maximize profit and impact.
Using my skills learned on DataCamp, I wrote a Twitter thread on <a href="https://twitter.com/Ayoolafelix/status/1324331120192856064?s=20">How to become a Data Analyst, Data Scientist or Machine Learning Engineer before the end of 2020</a>. DataCamp’s impact on my community has been huge, and I urge others to take advantage of this amazing opportunity. Thank you, DataCamp!
If you know of a nonprofit organization that could take advantage of free subscriptions to DataCamp, please reach out to <a href="mailto:giveaway@datacamp.com">giveaway@datacamp.com</a>.
Felix helped 1,500+ Nigerians get free access to DataCamp. He is a fourth-year chemical engineering student at Obafemi Awolowo University in Nigeria who wants to build products that leverage data science and product design to solve social and business issues. He is deeply interested in helping people get into the tech ecosystem and connecting them with resources. You can find him across social media platforms @ayoolafelix.

https://www.datacamp.com/community/blog/felix-ayoola

How Felix Ayoola, a student and graphic designer in Nigeria, helped over 1,500 learners get free access to data skills training.

Learner Spotlight: Nigeria’s DataCamp Evangelist

Seven years ago, DataCamp was founded with the goal of making the world more data fluent by building an affordable, engaging and scalable data science education platform. Today, this mission to fight data illiteracy is shared by 100+ employees. With the cost of education skyrocketing in many countries around the world, and economic opportunity increasingly reliant on understanding and utilizing data, our mission has never been more important. In a world where data is the new gold, data skills give people and organizations the opportunity to get ahead, and at DataCamp, we want to expand that opportunity to everyone.
We have seen firsthand the incredible demand for data science education as DataCamp’s growth has exceeded our wildest expectations: we’re now helping well over 1,600 businesses and 150,000 individual subscribers build data skills. This year, over 2 million courses will be completed on DataCamp, and DataCamp’s revenue has grown an astounding 1,232% in the past three years, landing us in the top 100 of Deloitte&#39;s Technology Fast500 ranking for 2019 and 2020!
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1607616280/image_8_n8eynd.png" /></center>

But we believe we can do more.
There are still many significant obstacles on the journey to a more data fluent world.
We think the 3 biggest obstacles are:
<ol>
<li>Labor market inefficiency– 
A huge supply-demand imbalance exists in the labor market across the spectrum (from highly technical roles like data engineers or data scientists to the less technical citizen data roles). Additionally, many applicants have trouble signaling their skill level and many organizations struggle to find the right talent. DataCamp is well positioned to address this labor market challenge by helping learners find the right job for them, and helping organizations find the right data talent. Offering scalable, affordable and trustworthy credentialing is an important aspect of resolving these labor market inefficiencies.
</li>
<li>Most data tools lack collaboration– 
Collaboration is at the heart of understanding and leveraging data. But despite the fact that the number of data professionals is growing rapidly, they lack access to tools that easily scale as data teams grow and help facilitate and encourage collaboration. As a consequence, insights from data teams are often scattered across various tools, analysis is duplicated, etc. Furthermore, in many organizations, it’s not easy to get started as a data scientist or analyst. You are likely to waste time getting access to data, finding data, repeating analysis, using dashboards that are broken or have errors in them, etc. This fragmented approach and knowledge base is not only inefficient, but a threat to the quality control of data work, low productivity of data talent and a massive financial cost to organizations.
</li>
<li>Lack of data fluency skills– 
To ensure more people can acquire data skills we must have scalable, engaging and affordable educational tools. With more than 7 million registered learners, DataCamp has come a long way in providing the best learning-by-doing learning products and is a market leader today. That said, we believe that there is still a lot of room for improvement and innovation, as we look to reach many more learners. For example, there’s an opportunity to provide DataCamp learning products for free or at a very low price point to lower-income customers throughout the world.
</li>
</ol>
We believe that we can create a virtuous cycle to fight data illiteracy by tackling each of these 3 challenges.
This is how we envision our product offering to evolve in the next few years:
On the consumer side, learners are joining DataCamp to improve data fluency. We enable them to track their progress through assessments, get real-world experience through projects and ultimately provide them the option to get certified and use that credential to find a job. In parallel, we make it easy for learners to start to do data analysis and data science in the cloud and enable them to create a portfolio with their data science work that they can share with colleagues, friends and potential employers.
On the organizational side, the learning product helps lift data fluency of the organization while the assessment tools allow them to understand the skill level of people across the organization and its evolution over time. Furthermore, credentialing can be a simple tool to create clarity around that skill level as well as help the organization evaluate and find the right people to join the organization. As the data fluency of the organization increases, a knowledge base emerges that is accessible to anyone with all key insights and with the ability to efficiently collaborate and build on these insights.
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<h3>Growing the team and leadership changes</h3>

The DataCamp 2.0 vision is the result of conversations with customers, employees, leadership members, and investors; and it is exciting to finally be able to start sharing it publicly. 
As part of this new vision we are realigning our executive team. I will step back into the CEO role. As one of DataCamp’s founders I am thrilled to be leading DataCamp again as we work to create a data-fluent world through the democratization of data science. Martijn will step into the Chief Operating Officer role with an initial focus on growing the B2B business, while Dieter will lead our innovation efforts around the collaboration platform for data teams and career services &amp; recruiting as the Head of New Products. We made this decision together with the full support of the Board of Directors and all our major investors and we are excited to move forward with this vision.
To realize DataCamp 2.0, we’re planning to hire more than 50 new DataCamp’ers in the next year. If you are interested in joining us, and are excited about our future path, make sure to keep an eye open on our <a target="_blank" href="https://www.datacamp.com/careers">careers page</a>.
— Jonathan

https://www.datacamp.com/community/blog/datacamp-2-0

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