closeup-diverse-people-joining-their-hands.jpg

Posted on April 26, 2023 by Andrew (Sal) Salazar .

From Google to Microsoft and Now Red Hat, layoffs seem to be everywhere you look.
I want to share my perspective on the recent layoffs in the tech industry and why it could be a positive opportunity for people of diversity who are in data.

The layoffs we have seen in companies such as Red Hat Software, Accenture, and Microsoft are not necessarily a sign of less need for data science personnel. Instead, it represents a shift in the tech industry towards more sustainable growth. These companies have been growing rapidly for the last few (many) years, fueled by venture capital, and the recent layoffs are an indication that these companies are coming back down to earth.

woman-diversity
Layoffs can be cause for uncertainty but, there is always an opportunity to be found if you know where to look.

This shift in the industry can be seen as a positive opportunity for people of diversity who are in data. As the industry transitions to a more sustainable model, there will be greater demand for diverse talent that can bring unique perspectives and ideas to the table. In other words, companies will start to recognize the value of having a diverse team and the impact it can have on their business.

For too long, the tech industry and data specifically, has been known for its lack of diversity, with many companies struggling to attract and retain diverse talent. But with the recent shift towards more sustainable growth, there is an opportunity for companies to reassess their hiring practices and focus on building a diverse team. This could mean more opportunities for women, people of color, and other underrepresented groups in data.

Yes, there has been a reduction in the actual diversity teams of some larger companies so this means HR and recruiting teams will have to work harder to both retain and attract the diversity that companies know is valuable to their growth. 
They could focus on doubling down and working twice as hard or they can focus on smarter options like working with Colaberry, a company that is dedicated to bringing diversity into the data industry. 90% of their consultants are DEI positive and 43% are female. It’s an easy solution to a difficult problem. 

Directors & hiring managers in data departments realize it’s important to recognize the value of diversity and be intentional about creating an inclusive workplace culture. This means not only hiring a diverse team but also fostering an environment where everyone feels welcome, valued, and supported.

The recent layoffs in the tech industry could be a positive opportunity for people of diversity in data and the companies smart enough to attract and fight to retain them. As the industry shifts towards more sustainable growth, companies will start to recognize the value of having a diverse team. As a director or hiring manager, it’s important to take advantage of this opportunity by being intentional about creating an inclusive workplace culture that values diversity and encourages everyone to bring their unique perspectives to the table.

Image of African-American business leader looking at camera in working environment.
Smart companies know that when you’re looking for something special/specific it pays to work with a specialist. This holds true when it comes to data science and diversity.

If you and your company know how valuable diversity coupled with top-tier data skills can be and want to discuss adding talent to your team without the headaches of mountains of applications and having to vet the applicants that look good on paper, then we should talk.

Reach out to Sal and the Colaberry team today
Andrew “Sal” Salazar
[email protected]
682.375.0489

www.colaberry.com/contactus

people at a event or meeting

Posted on April 4, 2023 by Andrew (Sal) Salazar .

The business world is always competitive and companies are always looking for ways to cut costs and improve their bottom line. Costs and the fact that they have an internal sourcing team are why your company may shy away from using outside staffing firms. Valid points? Like most things, the right tool for the right job should be the deciding factor. 

The primary reason why your company should consider using third-party companies is cost savings. Yes, there is a fee for services however, when you look at the overall costs associated in terms of man hours and the focus of your team, it can be faster and cheaper. Especially if you agree that time is as important if not more important than money. More on time in a moment. 

Niche firms like Colaberry have a database of the specific talents you need, so you get the right candidate for your specific needs. This access to specialized data analytics and science coupled with their ability to offer skills testing and handle vetting for your team are the real benefits of using outside resources like Colaberry. 

The idea is that time is money. Partnering with a firm can speed up the hiring process, as they have pre-screened potential candidates and can quickly match them with your job openings. This can save your company valuable time and resources in sourcing and vetting.

Having the flexibility to scale up or down quickly, based on your project or department’s requirements can be particularly enough to justify using an outside company. Especially if your data department is implementing new technology and needs more assistance at the beginning of a digital transformation and less once implemented.

By outsourcing recruitment and management, you can free up valuable time and resources to focus on your core operations. Red tape can often be found as the reason why projects go over budget and miss deadlines. Letting another company deal with these barriers can lead to huge overall savings. 

Staffing companies can help mitigate compliance and risk management issues by ensuring the workers provided meet relevant legal and regulatory requirements. This can help avoid costly legal and regulatory issues related to hiring and management.

Some consultants prefer to do contingency work as opposed to being full-time employees. By working with a staffing company to find the right fit for both project and permanent positions, businesses can increase employee retention rates and overall job satisfaction. The positive impact on your company’s culture and bottom line should be a factor in your decision.

Specialty companies like Colaberry have extensive knowledge in the data analytics industry, helping your business make informed decisions about workforce planning and talent acquisition strategies. This knowledge can be invaluable for businesses that don’t want to invest resources in these areas, especially for projects like digital transformation. 

“Stepping over dollars to pick up nickels”

While some companies are stuck in their ways and are willing to step over dollars to pick up nickels, others remain agile and open to exploring outside staffing resources. If your company is staying competitive and wants to explore a specialized staffing firm like Colaberry, you should reach out. Data analytics and science are all we do, so you can focus on your main business priorities. We’ll help get you there inside of budget and on time. 

To find out more about staffing your data team for either project/contingency roles or full-time hires reach out to Sal at 682.375.0489 or [email protected]

Image of abstract hallway

Posted on March 22, 2023 by Andrew (Sal) Salazar .

The Hidden Cost of Development or Technical Debt – Spotting And Stopping It

Technical debt is an often hidden cost a company incurs when a data department is forced to take shortcuts in a project or software development. It is the result of developers’ decisions to prioritize speed over long-term efficiency and stability and not having adequate resources to ensure overall quality. These decisions lead to the accumulation of errors, making the system harder to maintain and scale over time. Technical debt often accumulates unnoticed, as companies focus on delivering products quickly rather than addressing the underlying issues.

How to know if you are accumulating technical debt. What you should look out for:

  1. Delayed project timelines: Technical debt can cause projects to take longer to complete, as developers have to spend more time fixing issues with patches and one-off solutions as they continue to build on it or use it for a longer period of time. 
  2. Decreased quality: Technical debt can lead to low-quality products, making it harder to maintain and scale the system over time.
  3. High maintenance costs: Technical debt can become more expensive to maintain over time, as developers have to spend more time fixing bugs and maintaining the project.

Avoiding it altogether is the smartest solution however, it is often not noticed until it is a huge impediment to continued progress. One way to avoid it from the beginning is to use an outside firm like Colaberry to help with maturity assessments that evaluate the maturity of your data landscape and provide recommendations for improvements and prioritization. Using an outside company helps ensure you receive unbiased feedback and evaluations as they are not invested in any particular product or solution which is a possibility with internal evaluations.

These services provide businesses with the necessary expertise, tools, and infrastructure to be able to analyze the data and develop solutions that improve efficiency, stability, and scalability. By using managed data services, your businesses can focus on delivering features quickly while also ensuring that your systems remain efficient and stable over time.

Having the resources to flex with a project or product needs can be the key to long-term success rather than trying to retain the talent you need on a full-time basis.

Another solution to avoiding technical debt is to ensure you have an adequate amount of analysts who are skilled in the latest tech stacks to identify areas of technical debt and develop solutions that improve efficiency, stability, and scalability. When you choose Colaberry as a partner you get data talents who are skilled in using the latest technology such as AI & Chat GPT to ensure they can meet your product’s technical demands on time and on budget. 

Technical debt can have significant consequences on your overall system’s health and competitiveness. By using managed data services to oversee your data department or hiring additional data analytics talent from Colaberry, you can prevent technical debt from accumulating in the first place. 
Colaberry has a team of experienced data analytics professionals who can analyze complex systems and develop solutions that improve efficiency, stability, and scalability.  Don’t let technical debt hold your business back; contact Colaberry today to discuss a complimentary maturity assessment or what specific types of talents you need to get the job done. Colaberry is your source for simple data science talent solutions.

Andrew “Sal” Salazar
[email protected]
682.375.0489
LinkedIn Profile

image of laptop with coffee mug

Posted on March 21, 2023 by Andrew (Sal) Salazar .

The Power or Pain of Retention: Your Super Power or Achilles Heel?

In today’s fast-paced business world, retaining talented employees has become one of the biggest challenges for companies. Retention is particularly important when it comes to data analytics departments, where skilled employees can make or break a company’s ability to stay ahead of the competition and the average tenure is 2.43 years. In this article, we’ll explore how employee retention can be your company’s superpower because work life is different than it was just a decade ago. 

Employee retention is particularly important in data analytics departments where the field is constantly evolving, and skilled employees who have built up institutional knowledge are essential for staying ahead of the competition. Losing talented employees can set a company back in both the short and long term depending on the role and how in demand the skillset happens to be in the marketplace.

Benefits of Retaining Skilled Employees of retaining long-term employees are easy to list:

  • institutional knowledge and experience
  • Cost Savings-Replacing employees can be expensive, especially when it comes to highly skilled data analytics professionals. 
  • Improved Productivity-Skilled employees who are familiar with the company’s data analytics processes and tools are more productive than new hires
  • Increased Morale-Hard to create a sense of team when you are suffering from churn

Now we get to the good part. How to retain top talent.
Training and opportunities for personal & professional GROWTH. In the last week, I’ve been approached by two Colaberry Alumni who have pretty good jobs with well-known companies to approach me for help finding another role.
My first question was why? More money was actually the second thing listed. They both felt stagnant in their roles as the company was stuck using legacy tech and they had no growth opportunities. Their companies did not offer or encourage any upskilling or continuing education.

Colaberry can be a great resource for upskilling and retraining employees. Why find new talent when you can upskill your existing team?

Offering competitive salaries and benefits packages is usually the first thing we think about when talking about retention. I believe there are 5 areas of a comp plan each employee looks at

  • Financial: Annual salary, bonuses, equity, healthcare, benefits, etc.
  • Psychological: The internal and external meaning you derive from your work. Your connection to the mission, product, work you produce, and praise you receive.
  • Social: Prestige, job title, and identity capital you receive. 
  • Education: Skills, relationships, and learnings that contribute to your development as a person and professional.
  • Freedom: Your ability to work on your own terms. It’s the new normal and especially in the data industry time and location constraints can play a big role in an employee’s decision to stay or go. 

A positive work culture; includes things like team-building activities, flexible schedules, and a supportive management style. This includes 
Providing regular performance feedback to employees to help them understand their strengths and weaknesses. This helps employees feel valued and supported, which can lead to higher levels of engagement and job satisfaction.

Past performance, can be a huge indicator to help assess if a candidate will stick around or take off at the first offer of more pay. While the current sentiment is to not label job hoppers, sometimes it is what it appears to be. I believe these should be judged on an individual’s personality and story. The uncertainty of the last 5 years has been an unexpected adventure for many of us. 

All of these take both time and effort, and there is no silver bullet. Setting yourself and the employee up for a long-term relationship takes planning and dedication in your HR and Learning departments. Finding the right formula can take some trial and error, but there are companies who have clearly figured out the formula and have implemented all of these strategies.

If your company needs to explore how it can offer upskilling or reskilling to help stay competitive Colaberry can be a great resource.  Colabery Alumni boast an 80% interview to offer track record and have been in their role previous to Colaberry for an average of 4 years. Have you explored alternative options to sourcing your data talent? Contact us today to find out if there’s a solution beyond what you have now.

Andrew “Sal” Salazar
[email protected]
682.375.0489
LinkedIn Profile

Open AI chatgpt image with black background

Posted on March 13, 2023 by Andrew (Sal) Salazar .

The One Question to Ask Chat GPT to Excel in Any Job

Have you ever found yourself struggling to complete a task at work or unsure of what questions to ask to gain the skills you need? We’ve all been there, trying to know what we don’t know. But what if there was a simple solution that could help you become better at any job, no matter what industry you’re in?

At Colaberry, we’ve discovered the power of asking the right questions at the right time. Our one-year boot camp takes individuals with no experience in the field and transforms them into top-performing data analysts and developers. And one of the keys to our success is teaching our students how to use Chat GPT and how to ask the right questions.

Everyones talking about Chat GPT but the key to mastery with it lies in knowing how to ask the right question to find the answer you need. What if there was one question you could ask Chat GPT to become better at any job? This a question that acts like a magic key and unlocks a world of possibilities and can help you gain the skills you need to excel in your career. 

Are you ready? The question is actually asking for more questions. 

“What are 10 questions I should ask ChatGPT to help gain the skills needed to complete this requirement?”

By passing in any set of requirements or instructions for any project, Chat GPT can provide you with a list of questions you didn’t know you needed to ask. 

In this example, we used “mowing a lawn”, something simple we all think we know how to do right? But, do we know how to do it like an expert?

Looking at the answers Chat GPT gave us helps us see factors we might not ever have thought of. Now instead of doing something “ok” using what we know and asking a pointed or direct question, we can unlock the knowledge of the entire world on the task!

And the best part? You can even ask Chat GPT for the answers.

Now, imagine you had a team of data analysts who were not only trained in how to think like this but how to be able to overcome any technical obstacle they met.

If you’re looking for talent that not only has a solid foundation in data analytics and how to integrate the newest technology but how to maximize both of those tools, then Colaberry is the perfect partner. We specialize in this kind of forward-thinking training. Not just how to do something, but how to use all available tools to do something, to learn how to do it, and more. Real-life application of “smarter, not harder”.

Our approach is built on learning a foundation of data knowledge that is fully integrated with the latest tech available, to speed up the learning process. We use Chat GPT and other AI tools to help our students become self-sufficient and teach them how to apply their skills to newer and more difficult problem sets. 

But, they don’t do it alone. Our tightly knit alumni network consists of over 3,000 data professionals throughout the US, and many of Colaberry’s graduates have gone on to become Data leaders in their organization, getting promoted to roles such as Directors, VPs, and Managers. When you hire with Colaberry, you’re not just hiring one person – you’re hiring a network of highly skilled data professionals.

So why not take the first step toward unlocking the full potential of your data? Let Colaberry supply you with the data talent you need to take your company to the next level. 

Contact us today to learn more about our services and how we can help you meet your unique business goals.

Want more tips like this? Sign up for our weekly newsletter HERE  and get our free training guide: 47 Tips to Master Chat GPT.

colaberry-emotional-intelligence

Posted on March 3, 2023 by Andrew (Sal) Salazar .

data talent internships
EQ training helps Students build off their technical expertise to grow in their company 

Unlocking the Potential of Data Talent: How Internships Can Benefit Your Company

As companies continue to face a shortage of quality data talent, they are increasingly turning to alternatives to traditional recruitment methods to build their talent pipelines. Internship programs have emerged as a great way to acquire top-tier data talent while also promoting Diversity, Equity, and Inclusion (DEI) in the industry.

Colaberry School of Data Analytics is a prime example of an organization that transforms individuals with no experience in the data field into highly skilled Data Analysts and BI Developers with skills equivalent to those with 3-5 years of experience in 1 year. Colaberry’s AI-infused curriculum empowers students with the ability to use tools like AI & Chat GPT to become self-sufficient by understanding the right questions to ask at the right time. Additionally, Colaberry’s focus on Emotional Intelligence equips its alumni with the skills to grow into leadership roles in their companies.

students working at table with laptops smiling
students working at table with laptops smiling

Internship programs are a smart solution to the current shortage of quality data talent and the unfortunate inequity currently present in the data industry. Partnering with Colaberry can help your company acquire top-tier data talent and improve DEI numbers while benefiting from the expertise of an organization that is at the forefront of data analytics. 

To learn more about how Colaberry can help you develop a customized internship program or other unique ways to staff your data department, reach out to Sal today. Simple Data Staffing Solutions is Colaberry.

Andrew “Sal” Salazar
682.375.0489
[email protected]

Image of large factory at night

Posted on February 13, 2023 by Kevin Guisarde .

This blog post explores the applications of the Pivot and Unpivot data manipulation techniques within the context of the Oil and Gas industry. These powerful techniques are commonly used in data analytics and data science to summarize and transform data and can be especially useful for professionals in this industry who need to analyze large datasets. Through the use of SQL Server, the blog will demonstrate how these techniques can be effectively applied to the Oil and Gas industry to streamline data analysis and improve decision-making.

Agenda

  1. Introduction to Pivot and Unpivot in SQL Server
  2. Understanding the different concept types in Pivot and Unpivot
  3. Real World Examples in the Oil and Gas Industry using SQL Server
  4. Most Commonly Asked Interview Question in Pivot and Unpivot
  5. Conclusion

Introduction to Pivot and Unpivot in SQL Server

Pivot and Unpivot are powerful data manipulation techniques used to summarize and transform data. These techniques are widely used in the data analytics and data science fields. In this blog, we will discuss how these techniques can be applied to the Oil and Gas industry using SQL Server.

Understanding the Different Concept Types in Pivot and Unpivot

Pivot

Pivot is used to transform data from a row-based format to a column-based format. It allows data to be summarized and grouped based on columns.

Example:
Consider the following data table that shows the sales of different products for different months.

CREATE TABLE Sales ( 
  Product varchar(50), 
  Month varchar(50), 
  Sales int 
);
INSERT INTO Sales (Product, Month, Sales) 
VALUES 
  ('Product A', 'January', 100), 
  ('Product A', 'February', 200), 
  ('Product A', 'March', 300), 
  ('Product B', 'January', 400), 
  ('Product B', 'February', 500), 
  ('Product B', 'March', 600);

The data can be transformed using the PIVOT operator as follows:

SELECT * 
FROM 
  (SELECT Product, Month, Sales 
  FROM Sales) AS SourceTable 
PIVOT 
( 
  SUM(Sales) 
  FOR Month IN ([January], [February], [March]) 
) AS PivotTable;

The result will be as follows:

Product | January | February | March 
--------------------------------------- 
Product A | 100   | 200   | 300 
Product B | 400   | 500   | 600

Unpivot

Unpivot is used to transform data from a column-based format to a row-based format. It allows data to be summarized and grouped based on rows.

Example:
Consider the following data table that shows the sales of different products for different months.

CREATE TABLE Sales ( 
  Product varchar(50), 
  January int, 
  February int, 
  March int 
);
INSERT INTO Sales (Product, January, February, March) 
VALUES 
  ('Product A', 100, 200, 300), 
  ('Product B', 400, 500, 600);

The data can be transformed using the UNPIVOT operator as follows:

SELECT Product, Month, Sales 
FROM 
  Sales 
UNPIVOT 
( 
  Sales FOR Month IN (January, February, March) 
) AS UnpivotTable;

The result will be as follows:

Product | Month | Sales 
----------------------------- 
Product A | January | 100 
Product A | February | 200 
Product A | March | 300 
Product B | January | 400 
Product B | February | 500 
Product B | March | 600

Real-World Examples in the Oil & Gas Industry 

Using SQL Server:

CREATE TABLE OilProduction ( 
  Country varchar(50), 
  January int, 
  February int, 
  March int 
);
INSERT INTO OilProduction (Country, January, February, March) 
VALUES 
  ('USA', 100, 200, 300), 
  ('Saudi Arabia', 400, 500, 600), 
  ('Russia', 700, 800, 900);

1. Display the total oil production of each country for the first quarter of the year (January to March).

View Answer

2. Display the oil production of each country for each month.

View Answer

3. Display the oil production of each country in a column-based format.

View Answer

Most Commonly Asked Interview Question in Pivot and Unpivot

Q: What is the difference between Pivot and Unpivot?

A: Pivot and Unpivot are data manipulation techniques used to summarize and transform data. The main difference between these techniques is the direction of transformation. Pivot is used to transform data from a row-based format to a column-based format. Unpivot is used to transform data from a column-based format to a row-based format.

I have used these techniques in a previous project where I was required to analyze the sales of different products for different months. I used Pivot to summarize the data and transform it into a column-based format. This allowed me to easily analyze the sales of each product for each month. I also used Unpivot to transform the data back into a row-based format so that I could perform further analysis.

Conclusion

In this blog, we discussed the basics of Pivot and Unpivot and how they can be applied to the Oil and Gas industry using SQL Server. We also looked at real-world examples and the most commonly asked interview questions in Pivot and Unpivot. These techniques are powerful tools for data manipulation and can be used to summarize and transform data in a variety of industries.

Interested in a career in Data Analytics? Book a call with our admissions team or visit training.colaberry.com to learn more.

Book a Call
Close-up of colorful pencils with black background

Posted on February 3, 2023 by Kevin Guisarde .

Why DEI Initiatives & Boards May Not Be The Answer

Data analytics is an ever-growing field, with the potential to revolutionize the way businesses and organizations operate. However, this potential can only be tapped into if the data analytics departments are truly diverse, equitable, and inclusive. While establishing DEI initiatives and boards is a great step towards creating a safe, respectful, and equitable environment, it may not be the best long-term answer we think it is. The real solution is investing in upskilling and educating members of underrepresented populations.

Diversity, Equity, and Inclusion (DEI) initiatives are essential for creating a safe, supportive, and equitable environment. The benefits of diversity are well known and touted, however as the tech layoffs of 2023 continue the HR and DE&I teams tasked with making these changes are getting axed. (https://www.shrm.org/executive/resources/articles/pages/tech-layoffs-hitting-hr-diversity-teams.aspx) The better long-term solution lies in making sure Underrepresented populations (URPs) have the right skill set that makes them more likely to weather uncertain economic conditions.

Smart directors and managers recognize the importance of investing in upskilling and educating members of URPs. Companies like Colaberry School of Data Analytics are making it easier than ever for women and minorities to enter the data analytics field. Through their comprehensive training programs, using cutting-edge technology like AI and Chat GPT, they are helping to ensure that qualified professionals can get the skills they need to succeed, regardless of their background. This makes it possible for companies to add and retain data talent to their team based on merit and ability, instead of arbitrary DEI initiative numbers.

Smart and innovative organizations are Investing in equity and diversity to not only open up the team to a wealth of knowledge and insights but to also create a more productive and creative environment that encourages collaboration and innovation. With the right blend of upskilling/training and DEI initiatives in place, a data analytics team can unlock its full potential and help your business succeed. So if you’re looking for qualified data professionals, come and explore what Colaberry is doing to help change the face of data science by upskilling women and minorities. With their commitment to diversity and equity in data analytics, they are the perfect partner to ensure your team has access to the best talent available.

Do you agree or disagree with this idea? Let me know, I’d love to hear your feedback and thoughts at [email protected] 

Come see how Colaberry makes the bold claim to “produce a data analytics professional with the equivalent of 3-5 years of experience, in one year”.
You can see the available talent at www.hire.refactored.ai or come and see these professionals showcase and compete at our monthly Data Talent Showcase. 

Image of a man presenting a dashboard on projector in the dark

Posted on January 16, 2023 by Kevin Guisarde .

colaberry data talent showcase

See The Future Leaders of Data Science in Action At Our Data Talent Showcase Event

Are you interested in learning more about the future leaders of data science? Join us for our Data Talent Showcase Event, where you will get to see the next generation of data scientists in action! We will be showcasing some of the most innovative and ambitious projects from students who have completed Colaberry’s training program. This is an event you won’t want to miss!

https://info.colaberry.com/colaberry-data-talent-showcase

The Power of Data in Action

Are you looking to get a glimpse of the future of data science? Here, you’ll get to witness the power of data in action and get inspired by the limitless possibilities of data science.

At our event, you’ll get to see how businesses are leveraging the power of their data. You’ll also hear from experts in the data field and discover what smart business leaders look for in data projects. Plus, you’ll gain insight into data-driven innovation and how data science can help drive your business forward.

Whether you’re a data enthusiast or a business leader, this event is the perfect opportunity to get a glimpse of the future of data science and get inspired by what’s possible. Get ready to see the future leaders of data science in action!

data talent showcase judge

Guest Judge Minoo Agarwal

We’re proud to announce the addition of Minoo Agarwal as one of our esteemed guest judges at our Data Talent Showcase event! Minoo’s expertise and insights into the industry will be invaluable to the event.

A data and analytics evangelist with a successful history of transforming data assets into enterprise capabilities that drive outcomes.

 In her current role, Minoo is responsible for the short-term and long-term strategic roadmap for RTI’s analytics capabilities that promotes RTI’s strategic goal of digital transformation. 

RTI is an independent, non-profit institute that provides research, development, and technical services to government and commercial clients worldwide.

As a guest judge, Minoo will provide her unique perspective on the projects developed by our talented contestants. Hear her insights on what makes a project stand out and what she looks for in potential team members.

We’re thrilled to have Minoo join us for our Data Talent Showcase and can’t wait to hear what she thinks of the projects and the abilities of our contestants.

See Real Data Projects

At our Data Talent Showcase Event, you’ll have the opportunity to see real data projects in action. Attendees will gain insight into how data science is helping to shape business decisions and watch as the next generation of leaders in the field is empowered with data-driven insights.

You’ll also have the chance to learn from and network with some of the top data science experts in the field. Our event will feature great presentations, giving you a firsthand look at their expertise.

Come join us at the Data Talent Showcase Event to witness the future leaders of data science in action and see the people that are driving the industry forward.

data talent showcase

Support DEI Change in Data Science

At our Data Talent Showcase Event, you’ll have the opportunity to witness and support the future face of data science. Our goal is to create a more diverse and equitable data science landscape and to do this, we are showcasing top-tier talent from underrepresented communities.

We know that diversity, equity, and inclusion in data science is a key factors in any company’s success. That’s why our showcase will feature individuals who are a part of and passionate about making a positive change in the industry. 90% of Colaberry consultants are from under-represented populations and an astounding 50% are female.

The industry as a whole is in need of a drastic change. This event is a step in that direction.

Don’t miss this great opportunity to support DEI change in data science. Come be a part of the change.

Attend as an Audience Member or a Guest Judge

Gain insight into what businesses and organizations looking to the future are using and looking for.

Network with a diverse group of attendees from the data science field.

As an audience member, you can cast your vote for the winner and you’ll get to learn more about data science and how Colaberry is creating a movement to drive innovation and DEI change.

If you’re feeling adventurous and want to help others with your experience and knowledge, you can take part as a guest judge. If you are an experienced leader in data we would love to have you come to be a part of our event and mission. If you enjoy helping others, especially women and underrepresented populations then this is for you.

Don’t miss this chance to get a front-row seat to the future of data science! Our Data Talent Showcase Event is the perfect place to be inspired by the brightest minds in the field, and get a glimpse of the potential that lies ahead. We can’t wait to see you there!

To attend the event, become a guest judge, or if you are just simply looking to learn more, click on the link below.

https://info.colaberry.com/colaberry-data-talent-showcase

Jupyter Hub Architecture Diagram

Posted on March 15, 2021 by Yash .

Serving Jupyter Notebooks to Thousands of Users

In our organization, Colaberry Inc, we provide professionals from various backgrounds and various levels of experience, with the platform and the opportunity to learn Data Analytics and Data Science. In order to teach Data Science, the Jupyter Notebook platform is one of the most important tools. A Jupyter Notebook is a document within an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text.

In this blog, we will learn the basic architecture of JupyterHub, the multi-user jupyter notebook platform, its working mechanism, and finally how to set up jupyter notebooks to serve a large user base.

Why Jupyter Notebooks?

In our platform, refactored.ai we provide users an opportunity to learn Data Science and AI by providing courses and lessons on Data Science and machine learning algorithms, the basics of the python programming language, and topics such as data handling and data manipulation.

Our approach to teaching these topics is to provide an option to “Learn by doing”. In order to provide practical hands-on learning, the content is delivered using the Jupyter Notebooks technology.

Jupyter notebooks allow users to combine code, text, images, and videos in a single document. This also makes it easy for students to share their work with peers and instructors. Jupyter notebook also gives users access to computational environments and resources without burdening the users with installation and maintenance tasks.

Limitations

One of the limitations of the Jupyter Notebook server is that it is a single-user environment. When you are teaching a group of students learning data science, the basic Jupyter Notebook server falls short of serving all the users.

JupyterHub comes to our rescue when it comes to serving multiple users, with their own separate Jupyter Notebook servers seamlessly. This makes JupyterHub equivalent to a web application that could be integrated into any web-based platform, unlike the regular jupyter notebooks.

JupyterHub Architecture

The below diagram is a visual explanation of the various components of the JupyterHub platform. In the subsequent sections, we shall see what each component is and how the various components work together to serve multiple users with jupyter notebooks.

Components of JupyterHub

Notebooks

At the core of this platform are the Jupyter Notebooks. These are live documents that contain user code, write-up or documentation, and results of code execution in a single document. The contents of the notebook are rendered in the browser directly. They come with a file extension .ipynb. The figure below depicts how a jupyter notebook looks:

 

Notebook Server

As mentioned above, the notebook servers serve jupyter notebooks as .ipynb files. The browser loads the notebooks and then interacts with the notebook server via sockets. The code in the notebook is executed in the notebook server. These are single-user servers by design.

Hub

Hub is the architecture that supports serving jupyter notebooks to multiple users. In order to support multiple users, the Hub uses several components such as Authenticator, User Database, and Spawner.

Authenticator

This component is responsible for authenticating the user via one of the several authentication mechanisms. It supports OAuth, GitHub, and Google to name a few of the several available options. This component is responsible for providing an Auth Token after the user is successfully authenticated. This token is used to provide access for the corresponding user.

Refer to JupyterHub documentation for an exhaustive list of options. One of the notable options is using an identity aggregator platform such as Auth0 that supports several other options.

User Database

Internally, Jupyter Hub uses a user database to store the user information to spawn separate user pods for the logged-in user and then serve notebooks contained within the user pods for individual users.

Spawner

A spawner is a worker component that creates individual servers or user pods for each user allowed to access JupyterHub. This mechanism ensures multiple users are served simultaneously. It is to be noted that there is a predefined limitation on the number of the simultaneous first-time spawn of user pods, which is roughly about 80 simultaneous users. However, this does not impact the regular usage of the individual servers after initial user pod creation.

How It All Works Together

The mechanism used by JupyterHub to authenticate multiple users and provide them with their own Jupyter Notebook servers is described below.

The user requests access to the Jupyter notebook via the JupyterHub (JH) server.
The JupyterHub then authenticates the user using one of the configured authentication mechanisms such as OAuth. This returns an auth token to the user to access the user pod.
A separate Jupyter Notebook server is created and the user is provided access to it.
The requested notebook in that server is returned to the user in the browser.
The user then writes code (or documentation text) in the notebook.
The code is then executed in the notebook server and the response is returned to the user’s browser.

Deployment and Scalability

The JupyterHub servers could be deployed in two different approaches:
Deployed on the cloud platforms such as AWS or Google Cloud platform. This uses Docker and Kubernetes clusters in order to scale the servers to support thousands of users.
A lightweight deployment on a single virtual instance to support a small set of users.

Scalability

In order to support a few thousand users and more, we use the Kubernetes cluster deployment on the Google Cloud platform. Alternatively, this could also have been done on the Amazon AWS platform to support a similar number of users.

This uses a Hub instance and multiple user instances each of which is known as a pod. (Refer to the architecture diagram above). This deployment architecture scales well to support a few thousand users seamlessly.

To learn more about how to set up your own JupyterHub instance, refer to the Zero to JupyterHub documentation.

Conclusion

JupyterHub is a scalable architecture of Jupyter Notebook servers that supports thousands of users in a maintainable cluster environment on popular cloud platforms.

This architecture suits several use cases with thousands of users and a large number of simultaneous users, for example, an online Data Science learning platform such as refactored.ai