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Why DEI Begins & Ends With Learning

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DEI (diversity, equity, and inclusion) is a business priority that has lasting impacts on the world around us — and it happens to be a current buzz acronym on the tip of everyone’s tongue. The truth is, the “buzz” surrounding DEI is inconsequential. DEI is a cultural shift that’s here to stay — and it must be woven into every thread of our modern workplace culture. While 76% of organizations agree that DEI is a business priority, few actually made good on their promises and pledges last year, with only 5% meeting their goals.

We all know that real change doesn’t happen overnight — pledges and commitments need to be substantiated with real and actionable plans. Companies need to play the long game by cultivating the talent that exists in unexpected and underserved places, drawing on a more diverse workforce’s collective strengths and perspectives, and bridging the diversity gaps in high-growth fields. 

Why We Are Talking About DEI

What does learning have to do with diversity, equity, and inclusion? And how can learning help organizations make inroads when there are clear obstacles in the way?

Learning levels the playing field by building key skills and, in turn, provides full access and opportunity. By partnering with businesses to reskill, upskill, and train people, we help break through obstacles and make real progress in diversity efforts — at every level.

Our internal/external “always learning” culture is incredibly unique. From our Inclusivity committee to our employee resource groups (ERGs) to our executive DEI department and officers, we are passionate about DEI and its primacy in our work culture. We are passionate about always doing better and always moving forward. While we may not always “get it right,” we are determined to make it right for all. And we want to impart our knowledge and experience — wins, stumbles, and falls — to help others establish their rightful course.

“At the heart of learning is community,” says David Porcaro, VP of Learning and Innovation at GA. “Students learn best when there is a culture of belonging.”

Read on to see how we break down the elements of DEI into actions — and how they pertain to our core.

How To Build a Healthy DEI Culture

Step 1: Transform Diversity Promises Into Actions

Leaders understand that diverse leadership correlates with better business performance, but they need help moving from making verbal promises to taking real actions. Whether on the job, online, or on-campus, we believe that learning environments flourish when every individual’s inherent value and unique gifts and perspectives get illuminated.

“I believe it is essential that businesses make meaningful investments in building diverse, inclusive workplace cultures,” said Lisa Lewin, CEO of General Assembly. “True social progress is not possible without the business community taking meaningful action to address the most intractable problems facing our world.”

But what is a “meaningful investment” in the business space? (And how do you make one?) A meaningful (DEI) investment is sustainable, authentic, and people-driven — it’s when you invest in employees’ skills, cultures, and happiness. By showing vs. telling about your commitment to your people, you are instilling a trust-driven culture that can allow for challenging and transformative conversations and shifts. 360-degree changes can shape workforce cultures and provide real opportunities for diverse individuals — and real global change.


Step 2: Really Commit to Equity & Inclusion

When workplace cultures build an inherent sense of mutual respect, trust, empathy, connectedness, and belonging within their shared communities, they allow the difficult work of continuous learning — and unlearning — to occur. So, how exactly is GA committed to an inclusive culture? And how can we help you build one yourself?

To start, since 2011, GA has been building a culture of belonging and an open door to tech careers. We have been advocates of DEI from the very beginning. We take it very seriously.

What this means for you: When we take our inclusive ethos of belonging — and the training of it —  to an organization, holistic changes inevitably and authentically happen. A good DEI culture is fully inclusive, authentic, and communicative.

How to be committed in your org:

  • Form groups, departments, and committees within your organization to start the conversation. We have a director of DEI who helms all DEI-driven initiatives and communications, along with an Inclusion Committee, numerous ERGs (employee resource groups), and a supportive senior leadership team that serve as honesty checkpoints — they, along with all of our employees, are our ultimate feedback loop.
  • Show the work. These said groups and individuals promote an array of awareness campaigns and communications for heritage months, holidays, and beyond — and make them visible. These comms air internally, publically on our social channel, and in evergreen downloadable resources. 
  • Build the culture — from top to bottom — with the right people. Our senior leadership team and human resources department fully advocate for diverse hires, promotions, and opportunities by utilizing diverse job-seeker sites, taking the necessary time to find the best, most diverse candidates. In order to create a DEI culture, an organization must “do the work” by hiring individuals who inherently support and adopt DEI practices — and provide learning opportunities at every turn. 
  • Be open — and open to change. DEI is not a set-in-stone process. There will be “oops” moments — DEI is a quick-pivoting effort that requires agility, empathy, and patience.

Step 3: Give Open Access to Skilling Opportunities

Reskilling existing employees is crucial to diversifying teams. That means opening up access to departments that are historically less diverse, such as software engineering, and to underserved people groups, such as women and PoC.

Some of our examples: 

  • We partnered with Disney to diversify their tech department by training a group of nontechnical women for roles as software engineers in the CODE: Rosie initiative
  • At Adobe, we helped to create a diversified talent pipeline for skilled engineers with Adobe Digital Academy. Instead of recruiting outside the organization, GA identified and upskilled entry-level talent into digital apprentices. 
  • Similarly, through CODE for Good, we developed a custom digital training curriculum for both Guardian & Humana that reskilled a diverse talent pool of nontechnical employees for careers as software engineers within the company. We brought these two businesses together and developed diverse curriculums for each, providing networking and learning opportunities. CfG is our enterprise coalition that reskills women and underrepresented groups into skilled and empowered software engineers.
  • We are also excited to work with OneTen as a training partner, joining their mission to upskill, hire, and advance one million Black individuals in America over the next 10 years into family-sustaining jobs with opportunities for advancement.

How do we keep the momentum going?

We’ve identified crucial areas where DEI and learning intersect to largely impact culture in organizations. Fixing a systemic problem from the bottom up doesn’t lead to solving it at the top. Reskilling existing employees becomes crucial to fortifying teams, like offering existing employees career mobility by reskilling them into tech roles.

Ultimately, we must continuously invest in diverse employee bases and build a culture of lifelong learning by upskilling employees to accelerate careers — for every step of their career journeys. The truth is that digital skills are not static, and change is the only guaranteed constant. So, bottom line, all tech professionals, at every stage, need to be able to have the opportunity to skill up to meet the shifting demands of the industry — for a real chance to reach their full potential.

DEI is not a passing movement or one-and-done action. It must permeate every level of the org. DEI is our present and future.

GA Jobs to Be Done: A Series – Build Teams to Thrive in A Digital-First World

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The Third Step: Accelerate Technical Hiring Sustainably

The race for digital transformation has companies across industries under increased economic pressure to digitize. There’s only one issue: Getting ahead of the transformation imperative requires major changes. 

We can help.

Through our deep experience across many types of organizations, we’ve seen leaders’ transformation challenges boil down to four key goals:

  1. Create digital mindsets across the company. This includes understanding digital trends, growing digital mastery, and building a product-driven organization.
  2. Upgrade capabilities to reflect cutting-edge technical skills across marketing, technology, and data functions.
  3. Accelerate technical hiring by upskilling and reskilling current employees and new hires. 
  4. Understand what good looks like — a skill necessary in achieving every goal.

This series, GA Jobs To Be Done, unpacks each of these four goals, providing actionable recommendations that organizations can put into practice to help set their businesses on the path to sustainable digitization and success.

In this series, we’ve revealed how to build a strong digital culture and how to grow the capabilities that allow transformation — but to holistically scale your technology, you need the right talent. 

How do you get the “right” talent? Look internally — and read on. 

Talent Is the End Game

Earlier in the series, we addressed how to set your business up for digital success by upskilling and reskilling your current workforce and aligning your company — from leadership to new ways of working. But scaling these new digital systems, once again, requires acquiring the right talent.

“Help me accelerate my technical hiring” is one of the most common asks we get from executives. Once digital visions are mapped and job functions scoped, companies see the importance of scaling teams — very quickly. Top-performers who have knowledge of technical skills are spending more time interviewing candidates than building technology, causing a major lag in demonstrating transformation-related ROIs.

Rest assured, there’s a way to stay out of this. We studied it, so you can avoid learning the hard way.

The Zero-Sum Game of Buying Talent

Anyone who is hiring knows that good technical talent is hard to come by. To get desired candidates, companies are engaging in a competitive talent battle that is accruing huge recruiting bills and skyrocketing salaries for qualified potential hires. This competition has created a tragedy of the commons in which a $4,000 cost-per-hire is normal, where a company like Netflix can offer a double salary to poach a new recruit, and 70% of employers either have terminated workers due to the implementation of new technology or anticipate doing so.

This is neither a winning strategy for digital companies or the marketplace as a whole. In the meantime, serious inequities have surfaced in underserved and underrepresented groups and their ability to access necessary skill development needed for tomorrow’s roles.

A Virtuous Cycle With Better Market Results

Getting out of this aforementioned vicious cycle is best for your company and the overall market. 

Good news! There is a new and better cycle: Recent studies have shown a $136K potential savings per person from reskilling in-house tech talent instead of layoffs and new hires. Reskilling high-potential employees whose roles may phase out due to automation means you increase your talent pool and demonstrate a willingness to invest in and grow your employees. Contrary to the common fear many companies share (investing in talent only to see their stars work for competitors), these “talent donors” get an incredible boost in employee engagement and loyalty

In fact, companies that invest in talent become more attractive to skilled employees drawn to their growth culture. These investments create a bigger pie for the job market: the more companies grow their internal talent, the more available talent is for the market. Job-filling efficiency also gets boosted.

Many companies are already successfully investing in talent to save time, money, and turnover. Booz Allen Hamilton’s investment in reskilling and upskilling 25,000 workforces across 80+ locations resulted in a growing data capability that secured a 4% lift in contract value and an 11% growth in employee job satisfaction and retention. Some of the largest global technology, insurance, media, and auto companies are doing the same with skilling programs thriving at Interapt, Guardian, Humana, Bloomberg, and more.

Diversity Is a Winning Strategy

While the bidding war for top talent accelerates, the market only exacerbates the well-documented diversity issues within the tech industry. From vast underrepresentation for women and people of color to wage gaps compared to their white peers, institutional barriers prevent a healthy distribution of diverse perspectives in technology.

The exclusivity of skilling access is an obstruction —  and companies are making moves to change that. For example, Disney launched a program called CODE: Rosie to reskill women as developers — and it resulted in a 100% hiring rate for graduates entering technical roles. Guardian and Humana partnered to create the Code for Good coalition that reskilled underrepresented groups (including women, BIPOC, veterans, parents, and LGBTQQIA+ individuals) into engineering roles with perfect program satisfaction scores.

Bottom Line: Invest To Grow

As these programs grow and flourish, it is clear that building talent is the answer to the vicious cycles of talent shortages we see today. Throughout this piece, we’ve highlighted the many opportunities that make building talent more effective than buying it. 

So, how do you accelerate technical hiring for your new stage of growth? Skilling your people from within is simply the most sustainable way. In addition to solving the hiring conundrum and creating numerous additional company and labor market benefits, investing in internal talent also helps you:

  1. Build a talent pipeline to attract and retain high-potential talent.
  2. Make tangible progress on your DEI goals. 
  3. Lower the costs of talent acquisition for tech and data roles.
  4. Reduce the potential shortage risk for projected talent needs,
  5. Reduce the financial and morale impacts of large restructuring efforts by reskilling laid-off workers with competitive skill sets.

As the shifts in digital innovation only accelerate, growing your talent funnel is the most effective strategy for employees, the bottom line, the labor market, and the future of business.

A critical question companies ask is, “How do I know I’m doing everything right?” While “right” means different things to different businesses, we help you benchmark what “good” looks like, so you can set and attain personalized growth goals. We’ll get into all of this in our final installment.

If you’re ready to invest in your talent, we can help today. Explore our catalog to see the digital literacy and upskilling courses that we provide — from IC to strategic leader, across digital fluency, marketing, data, and technology. 

Want to get specific about how we could help your organization? Get in touch. 

Alumni Success Stories: How One GA Grad Changed Careers After 10 Years in Finance

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It’s never too late to pursue work you love — that’s what we learned catching up with User Experience Immersive Design (UXDI) alum, Manan Shah, about his journey from senior finance professional to user experience (UX) designer. Working in a high-paying, secure role for over a decade, you might think, “What more could you ask for in a career?” But it wasn’t until after Manan secured a role at JPMorgan Chase & Co. as a senior UX designer that he learned what was missing: work he loved. Learn how he navigated his career change and what he discovered along the way.

I was brought up in a single-parent immigrant household where education and extracurricular activities were important to my mom as long as they pushed me forward. This honed my creativity, as I had to make more with less.

I graduated from the University of Maryland with a degree in finance and went to work at Lehman Brothers after getting a full-time offer from my internship. I worked there for two years before they went bankrupt, but luckily the division I worked for, Neuberger Berman, was able to spin itself off into a private company.

What were you doing before you came to GA? What was difficult or dissatisfying about it that prompted you to make a change?

At Neuberger Berman, I was most recently a VP in Internal Audit, but there were a few reasons why I decided it was the right time to look for a new challenge. I had worked at the same place for 11 years after graduating college and never even interviewed for a full-time job. I learned how to excel in a structured environment, but I didn’t have the opportunity to flex my creative skills. I also wanted to start a family soon and knew it was my last chance to take a risk and do something different.

What about UX specifically intrigued you to explore it as a career? What was the defining moment that pushed you forward?

Thankfully, my wife encouraged me to look outside of finance. I realized that I wanted to do something future-leaning (i.e. tech) that also repurposed my existing skill set, so I would not have to start from the bottom. I went down a rabbit hole of different career websites and spoke to countless people until I connected with a few design professionals. When I learned about UX, I thought it would be a great fit for my skill set and would incorporate both the left and right sides of my brain.

GA has a great reputation among bootcamps, especially since they have a large employer network. It was also suggested to me by a few people, so I went to an open house. Coincidentally, the instructor was a UX designer at an accounting company. He said things that kept checking boxes for me: 

  • Am I the kind of person who asks how things could be made better?
  • Do I want a seat at the table to advocate for the person actually using the product?
  • Do I like to find new ways to do things, like “hacks”?

When I asked him his opinion on a career change from finance to UX, he intimately understood my skills as an auditor and connected the dots from that role to UX. At that moment, I knew what I wanted as my next challenge.

What was the best thing about UXDI for you and the GA experience overall?

The support and encouragement from my instructors and fellow classmates were key to my success. I was able to help others with concepts I knew, and they helped teach me things I was not as confident in.

The icing on the cake was the final project with a real client. It taught me so much about UX and myself, including what expectations can and cannot be met. It was also one of the main topics I discussed in my first set of interviews.

Can you share more about your capstone project? 

I went into the project with really high expectations, but I was not prepared for the amount of work the client’s product required to achieve its goals and reflect my new skill set. I was disheartened to say the least. I shared my feelings with my team, and they felt similarly. But our instructors pointed out that our project was the best one to highlight the impact we can make with UX. As we finished presenting to the client, we braced for negative feedback. Much to our surprise, the client was overjoyed with our design, and I left feeling so much pride in what I had accomplished. This was a clear example of not judging a book by its cover. 

How has GA been a resource to you in terms of finding a job after completing your program? 

My career coach, Anna, was amazing!!! She made us stick to a plan and carry it out — even when we were insanely busy. Through every up and down, she was a great resource when you needed something, as long as you showed you were committed.

How do you think your background in finance prepared you for your career in UX? 

My finance career honed a lot of the soft and hard skills I use today as a designer, such as running my own projects, time management, prioritization, creating reports and presentations, interviewing auditees, learning from missteps, speaking up or taking a back seat when needed, analyzing qualitative and quantitative data, and problem solving.

What do you love most about your current role?

I was thrilled to get the senior UX designer role at JPMorgan Chase & Co., since it married my previous job as an auditor at an asset management company to my new career. But the things I love the most are:

  • I have met so many interesting, open-minded people who bring fresh ideas and experiences to the table.
  • I am able to own the product from a design perspective. My manager pushes me but also allows me to shine and take in wins. 
  • The product I work on helps users to see their finances in one holistic view. I am helping the greater good, and I feel good at the end of the day because of it.

How did the skills you learned at GA help you in your current career?

I would not be where I am now — which is in a much happier place — without GA. One of the biggest skills my instructors taught me was navigating ambiguity. When I was in finance working as an auditor, I requested everything I needed to accomplish my work. With UX there is no final answer; the discipline as a whole requires some comfort with gray area and making decisions without having all the answers. 

As you know, creativity and logic are not mutually exclusive. How have you witnessed those left-brain and right-brain skills complement each other in your current role? 

As a UX designer, the visual skill set is obviously important, but it is easy to underestimate how much impact an analytical skill set can have on your work. I’ve been brought onto many projects simply to nail down the root cause of a problem we should solve. A seamless and easy consumer experience, at the end of the day, is a logical one. From a collaboration standpoint, I have product and tech partners who appreciate how I can think beyond the design and see the big picture.

Do you find that combo to be an uncommon hybrid skill set that gives you a competitive edge? Or is it something typical in your field?

This is a skill that great designers have. It’s also one that designers can learn, but some pick it up quicker than others. Those that do are able to move onto more complex designs and deliver a cohesive product. I believe that having both enabled me not to have to start my new career from scratch. 

Sometimes, we can unintentionally lock ourselves into a label: “I am a creative” or “I am a technician.” What would you say to someone who is interested in UX but doesn’t consider themself to be either creative or technical enough? 

UX is one of those careers where there is something for everyone. As long as your goal is to produce the best product for the customer, you can find your niche based on your strengths. You can be a designer, researcher, content editor, architect, or any mix of those areas. While being technical or creative will most definitely help, there are so many skills that you can bring to the table that will help you in your journey. Soft skills can elevate you. There are designers who may not be the best at presenting — and if you can’t sell your design, then it doesn’t matter how creative it is. Or, if you can’t convey to the developer what you are designing, it won’t be created as intended. 

In respect to UX, what do you want your legacy to be? Is there a change you want to inspire or a mission that defines the work that’s important to you?

In my prior work, I was able to help my company do things better, but I wanted my work to be more personally fulfilling. In my new career, I wanted to do better for the public and have a direct impact. I want a legacy where I see other competitors using elements of my work because the competition views it as the best experience for their users — which I have already begun to see.

5 Key Excel Skills You Can Learn in Minutes

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Since it was created in 1985, Excel has practically become synonymous with data itself, and still is many years later. Spend a few minutes with our expert instructor in the videos below to learn the kinds of Excel tools that can help you be your own analyst—and make smarter decisions with data. 

How to Create an Excel Bar Chart

Bar charts are an important visual tool that can help express your data over time and tell a story in a visually appealing and digestible way. Learn more in our 2-minute lesson below:

How To Create an Excel Pivot Table

Pivot tables allow you to effectively summarize and highlight the importance of your data sets. They are an important presentation tool and can help you simplify your data. Learn more in our 3-minute lesson below:

How To Create a Histogram in Excel

Histograms provide a visual representation of variations within your data and can help display degrees of difference in an impactful way. Learn more in our 2.5-minute lesson below:

How To Create a Pie Chart in Excel

Pie charts can express percentages of a whole and represents a set period of time and can be helpful to show differences among a handful of categories. Unlike bar charts, it does not express changes over time. Learn more in our 2.5-minute lesson below:

How To Create a VLookup in Excel

A VLookup (vertical lookup) can help you lookup data that is organized vertically. It is useful in helping you spot trends and find important pieces of data that can be difficult to locate in large data sets. Learn more in our 2.5-minute lesson below:

A Beginner’s Guide To Tableau

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Featuring Insights From Iun Chen & Vish Srivastava

Read: 2 Minutes

Tableau is a powerful data analysis and data visualization tool that anyone can use. It can be used by beginners to create simple charts and by advanced practitioners to solve complex business problems. It is user-friendly, easy to learn quickly, and includes a portfolio of business intelligence tools with the potential to give a wide range of roles the advantage of professionally analyzing data.

Simply put, if you can present data in a clear, compelling format, you gain a competitive advantage in today’s data-driven marketplace.

“Tableau enables you to quickly connect disparate data sources and utilize a drag-and-drop interface to analyze data and create dashboards,” says Vish Srivastava, who leads our Data Visualization & Intro to Tableau workshop. As a product leader at Evidation Health, he relies on Tableau to turn around fast data analysis. “For example, product teams use it to analyze user growth and analytics, BizOps teams use it to analyze operational data, and sales teams use it to analyze customer and revenue data.”

Businesses survive and thrive on data. The amount of data available to businesses today is impressive. To keep organizations on a successful path, analysts need to provide the key insights needed to make important decisions.

Here’s where Tableau comes in.

Tableau takes business intelligence to the next level, making it fast and efficient to analyze large amounts of data and create beautiful, presentation-ready visualizations that generate insights.

Data is the lifeblood of modern teams. Being able to quickly answer ad hoc questions and integrate data analysis into your day-to-day decision-making will make you an MVP. Though not all data analysts use Tableau, they do need some way to quickly create data visualizations.

Tableau is the data viz tool of choice.

Tableau is so popular in part because it is easy and fast to learn. In Iun Chen’s Intro to Data Analytics course, students learn the life-changing basics of Tableau in an afternoon. Aspiring analysts come to understand the power of data and the impact their numbers can have. As more data becomes available, there are more opportunities for data to be misused, a risk that every data scientist soon realizes. To quote the Nobel laureate and economist Ronald Coase, “If you torture the data long enough, it will confess.”

The ethics of data form the foundation of Chen’s syllabus so pitfalls are avoided from the start. “Overanalyzing and manipulating data too deeply can always give you the information you want,” says Chen. “Unfortunately, this is all too common in professional settings, though it’s usually unintentional.”

Tableau is a powerful tool.

Business insights are only as good as the data behind them, and the best data analysts understand that the human choices they make matter.

“Data is the perfect example of garbage in, garbage out,” says Srivastava, who defines good data as data that is ethically collected, complete, objective, and thoroughly analyzed. ”The double-edged sword of using powerful data analysis and visualization tools is that beautiful charts can create a false precision and obfuscate data integrity issues.”

To delve deeper into this topic, Chen recommends How Charts Lie, by Alberto Cairo, an exploration of how data can be altered:

“This book details how the use of data and data visualizations in journalism can be distorted and misleading, without the audience even realizing it, due to the urgency to present findings in a timely manner to the public.”

Want to learn more about Iun?
https://www.linkedin.com/in/iunchen 

Want to learn more about Vish? https://www.linkedin.com/in/vishrutps

7 Tips to Learn Tableau Fast

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Featuring Insights From Iun Chen & Vish Srivastava

Read: 2 Minutes

Let’s get it straight: How difficult is it to learn Tableau for a complete beginner? Are there shortcuts to learning Tableau? Any tips, tricks, or time-saving work-arounds? Thankfully, the answer is yes. Try these top tips, approved by our expert instructors, and start data viz now.

“It’s a little overwhelming at first but as soon as you understand the basics, like what are dimensions and measures, everything falls into place pretty quickly,” says Vish Srivastava, product leader at Evidation Health and GA instructor.

“In essence, you need to understand two things: The basics on how data works — for example, what are common formats of data and what is a primary key? And a basic understanding of data visualization in a business setting. Can you answer the question: When is a time series vs. a pie chart valuable for decision making?”

But can you really learn the basics of Tableau in an afternoon?

“The best way to learn is to download a sample dataset and dive right in and start creating data visualizations. To keep going from there, check out various portfolios online to get inspiration, and try to build those.”

According to Iun Chen, who conducts internal Tableau training at LinkedIn, Tableau is easy to learn, but hard to master.

“The basic concepts of charting and color theory are easy to pick up and can take just a few weeks. However, if you are looking to be a subject matter expert, this can take years to perfect,” she says. 

Chen preps students in her Intro to Data Analytics course to achieve close-to-mastery in these key areas.

  1. Can they quickly prep and analyze large volumes of data?
  2. Identify key information and determine the best visual method to present them?
  3. Take business questions and determine which visualizations to use?
  4. Translate raw datasets to storylines with a beginning, middle, and end? 
  5. Format charts, graphs, titles, text, and images for a polished deliverable? 
  6. Articulate best practices on design and visualization techniques?
  7. Provide feedback on ineffective visualizations and how to improve them?

    This checklist is the closest thing to a Tableau cheat sheet you’ll find. Prioritize these skills, and you’ll waste no time learning Tableau. Now that you know what you need to succeed, you can choose whether to take our Data Analytics course fast or slow. Learn Tableau — along with data analytics tools SQL and Excel — in a 1-week accelerated format, or over 10 weeks in the evening.

Chen sums it up perfectly: “As long as you are actively learning, applying your learnings, and ensuring innovation of your work, you will be a data visualization expert in no time.”

Want to learn more about Iun?
https://www.linkedin.com/in/iunchen 

Want to learn more about Vish? https://www.linkedin.com/in/vishrutps

Top 3 Reasons To Learn Tableau

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Featuring Insights From GA instructor Candace Pereira-Roberts

Read: 2 Minutes

Do you communicate data? Do you want to create more effective data visualizations? Tableau is the data analytics tool you’re looking for. Here are the top three reasons why you should learn how to use Tableau, the popular data viz software focused on business intelligence. Read on for the advantages of being a Tableau professional.

#1 Tableau Is Easy

Data can be complicated. Tableau makes it easy. Tableau is a data visualization tool that takes data and presents it in a user-friendly format of charts and graphs. And here’s the rub: There is no code writing required. You’ll easily master the end-to-end cycle of data analytics.


Need to showcase trends or surface findings? Tableau will make you an expert. Proficiency in business intelligence is a transferable skill that is quickly becoming the lifeblood of organizations. 

“I see students who are new to analytics learn Tableau desktop and be able to develop Tableau worksheets, interactive dashboards, and story points in a couple of weeks — essentially a complete data analysis project,” says Candace Pereira-Roberts, FinServ data engineer and one of our Data Analytics course instructors. She adds, “I like to share knowledge and watch people grow. I learn from my students as well.” 

 #2 Tableau Is Tremendously Useful

Would you rather tell visual stories with data? Or present the same old boring reports and tables? Is that even a question?

“Anyone who works in data should learn tools that help tell data stories with quality visual analytics.” Full stop.

The smart data analyst, data scientist, and data engineer were quick to adopt and use Tableau tool by tool, and it has given those roles a key competitive advantage in the recent data-related hiring frenzy. But their secret is out. And the advantages go beyond the usual tech roles. Having a working knowledge of data, and specifically knowing how to use Tableau, can help many more tech professionals become more attractive to recruiters and hiring managers.

Plus, it has a built-in career boost. Tableau’s visualizations are so elegant, you’ll be confident presenting the business intelligence and actionable insights to key stakeholders. Improving your presentation skills is par for the course.

#3 Tableau Data Analysts Are in Demand

As more and more businesses discover the value of data, the demand for analysts is growing. One advantage of Tableau is that it is so visually pleasing and easy for busy executives — and even the tech-averse — to use and understand. Tableau presents complicated and sophisticated data in a simple visualization format. In other words, CEOs love it.

Think of Tableau as your secret weapon. Once you learn it, you can easily surface critical information to stakeholders in a visually compelling format. That will make you a rockstar in any organization. 

“Tableau helps organizations leverage business intelligence to become more data-driven in their decision-making process.” Pereira-Roberts says. She recommends participating in Makeover Monday to take your skills to an even higher level. 


Want to learn more about Candace? Check out her thoughts on how to become a business intelligence analyst, or connect with her on LinkedIn.

What Is Data Visualization?

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An Interview With Iun Chen

Read: 4 Minutes

Data is big, and it’s getting bigger. How do you parse and understand data when the sheer amount of information can be overwhelming? The answer is data visualization. Using concepts of design theory like elements of color and layout, the discipline of data visualization, or data viz, is essentially the graphic representation of data. We called on one of our data viz experts, Iun Chen, to break it down further. 

Let’s start with an introduction and how you came to the world of data viz.

IC: I’m Iun (pronounced ‘yoon’), and I work in the data analytics space focusing on business intelligence tools and building scalable resources for LinkedIn. I also teach the 10-week Intro to Data Analytics course for GA, which includes the professional skills of SQL, Tableau, and Excel.

In college, I was a business major with a specialization in marketing and advertising. I became more interested in how the ad business model worked behind the scenes and in how software and systems worked. As a result, I worked at many major media companies in a quantitative capacity — revenue planning, ad pricing, finance, ad sales strategy. That led me into a formalized analytics route.

How do you define data visualization?

IC: Data visualization is the idea of communicating information graphically. It’s the science of information design, in which you take massive amounts of data in whatever format it comes in and use it to surface high-level insights and findings in a visually compelling way so audiences can easily understand the main points.

How does data visualization differ from data analytics?

IC: Data analytics is the process of cleaning, prepping, analyzing, and presenting data. Data visualization is part of the presenting data step and is defined as the act of visually organizing data through the use of charts, graphs, and dashboards. Concepts of data visualization are closely aligned with concepts of design theory: color, font, scale, layout, organization.

Why is data viz important?

IC: Data visualization is easy to learn but hard to master. In my classes, I heavily emphasize the design element of data visualization. It’s easy to whip together a quick bar or pie chart, but is it the best way to communicate the point you are trying to make? The goal of collecting mass amounts of data is to be able to quickly translate it into insights that can help make smart business decisions. The final form of this translation is often a chart or graph, which is why the ability to design and visualize these mass amounts of data grows as we collect more of it.

What is a data narrative?

IC: People think in stories and narratives, not in black and white figures. Just like you would share a story with a friend using a beginning, middle, and endpoint, you would do the same when sharing details about data analysis. Here’s a simple example.

  1. Beginning: Sales are down year-over-year; identify the symptoms.
  2. Middle: Furniture sales — our largest segment — are doing poorly in the last six months; conduct the analysis to investigate reasons and uncover root causes.
  3. End: Review retail store reports and conduct manufacturer visits; recommend next steps.

The key point to any data narrative is that it should present a compelling business case and surface unrealized insights to the audience. The business challenges, rationale, and next steps should be clearly presented, and people in the room should be able to walk away and know what to action on. 

Which tech roles use data visualization?

Data visualization — like data analytics — is a skill set that can be applied to any job. But if you are looking for a job that has data visualization skills as part of the function and responsibilities, look for roles like business analyst, data analyst, business intelligence analyst, data scientist, and data engineer. Keep in mind that the formal skill of data visualization is still relatively new, so depending on the maturity of the company, those functions may not be fully established yet. However, with the increase of data in the world, there’s a growing need for experts who understand data visualization techniques more and more.           

Check out this Medium post which details how Spotify’s business has evolved with the creation of their data visualization roles.

What’s the future of data visualization?

As we continue to collect more and more data, the need for people with the skills to analyze and present data becomes ever-growing and critical in the workplace environment. More companies will need to generate insights quickly to keep up with advances and competition in their respective industries. The skill of data visualization will become more and more attractive as teams and organizations seek to translate their data into insights more efficiently and effectively. The ability to work with data is increasingly critical to the success of any company in any job function. 

Iun Chen’s Recommended Data Viz Reading List

FlowingData

StorytellingWithData

InformationIsBeautiful

Tableau Public Gallery

New York Times Data Journalism

The WSJ Guide to Information Graphics

Storytelling with Data: A Data Visualization Guide for Business Professionals 

Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations

Edward Tufte’s The Visual Display of Quantitative Information

Want to learn more about Iun?
https://www.linkedin.com/in/iunchen

Business Analytics Vs Data Analytics: What’s the Difference?

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Featuring Insights From Iun Chen & Vish Srivastava

Read: 4 Minutes

Data analytics and business analytics are often confused, understandably, because both data analysts and business analysts work with data. What matters — and differentiates these two roles — is what the data is intended to do.

When comparing the roles of business analyst and data analyst, one must consider the audience. Who will be taking action based on the analyses?

Business analysts use data to improve business metrics.

Business analysts work directly with stakeholders to steer company objectives and keep the business on a successful path. They set and maintain key performance indicators for the organization. A business analyst may recommend strategies or business plans to executives, sometimes when a company is at a critical juncture, say quarterly or during a turnaround. Stakes can be high, but so can the rewards. (Think McKinsey analysts or other coveted consultancy jobs.) Business analysts are more likely to use presentation skills as they’ll need to present findings to executives and give recommendations in high-level meetings. 

Data analysts collect, extract, and analyze data.

Data analysts are more technically focused. They are responsible for getting the data and analyzing it, working with datasets and tables. For example, a data analyst at an eCommerce company may analyze customer information, aggregate email marketing lists, or use data to identify demographics for new customer acquisition plans. Data analysts are more likely to work in teams alongside marketing partners or with other technology roles such as programmers or product managers, depending on the size of the company. They also work with business partners across entire organizations, including business analysts, as needed for tasks and projects. 

Different roles mean different salaries.

Both business analysts and data analysts solve business problems. As such, they are in high demand. According to Glassdoor, the average salary for a data analyst in the U.S. is $72K. Compensation for business analysts is a bit more, averaging $79K. Of course, exact amounts depend on location and will vary from country to country. While a business analyst can command a higher salary, there is wider latitude for data analysts to carve out their niche in practically any industry. Since the function of data is increasingly integral to every enterprise, there is more flexibility for data analysts to dig into areas of the business where they can make the most difference, with more potential for creativity.  

In GA’s Intro to Data Analytics course, Iun Chen teaches SQL, Tableau, and Excel, business intelligence tools she uses in her professional role as a data analyst at LinkedIn.

“My formal job function is to build data tools for internal colleagues so they can successfully grow our business,” she says. “I create dashboards, reports, and anything else to ensure revenue keeps going up and anticipated risks go down for the company. In my experience, the skill set and mindset of the individual can define the role of a data analyst in any organization, large or small. Everyone uses data in their day to day so being able to clean, prep, analyze, and report data — regardless of what your actual job title is — is critical to not only the company’s success but your personal success as well.”

Both business analysts and data analysts are storytellers. 

Whether a business analyst’s more strategic and decision-making role is for you, or the technical, numbers-crunching, team-playing data analyst sounds more your speed, know that the two roles share one crucial skill: They use data to tell stories. Those stories lend insights that factor into decisions that affect the bottom line. Translating raw data into digestible and human narratives can be one of the most challenging skills for analysts to master, according to Vish Srivastava, who’s led multidisciplinary teams across tech sectors. So how does an analyst develop this multifaceted skill and set their career on the path for success?

“My recommendation is twofold,” he says. “One, always start your analysis with a hypothesis that you’re testing. You need to know right out of the gate why your analysis is going to matter. Two, after you’ve spent some time with your data, step away and write down your presentation storyline in three to five bullets. The final bullet should be your recommended next step. Of course, make sure you have the analysis and charts to back up your storyline and fill in the gaps as needed.”

When it comes to storytelling with data, the difference between a boring story and a compelling one can come down to data visualization. The tools at your disposal and your proficiency with them can make or break a presentation. Communicating the insights for business intelligence hinges on clear and impactful data viz, whether we’re talking business analytics or data analytics.

One classic example of data visualization’s power is the cholera map by John Snow, an early pioneer of disease mapping. “This is a beautiful example of how collecting data and visually presenting it can generate amazing insight,” says Srivastava. “In this case, the insight was that the sewer systems were spreading disease. This informed public policy and saved so many lives.”

The future of business intelligence will be determined by the democratization of data.

The prevalence of data and its part in tech careers is changing. To hear Srivastava tell it, future conversations on business intelligence will center less on the specificities of data analysis vs. business analysis and more on how data is creeping into even more roles.

“We’ve come a long way, but there is still far to go for data analysis skills to be deeply embedded in all functions across a company. In the future, I think we will see fewer dedicated teams for business analysis and data analysis; instead, all professionals will have these skills and utilize them daily. This democratization of data analysis will be incredibly powerful. It will create even more emphasis on making high-quality data available across every enterprise.”

Want to learn more about Iun?

https://www.linkedin.com/in/iunchen 
Want to learn more about Vish?
https://www.linkedin.com/in/vishrutps

Tableau vs. Power BI

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Featuring Insights From Matt Brems

Read: 2 Minutes

Tableau and Power BI are powerful tools for business intelligence, with capabilities to take loads of big data and create elegant visualizations that convey key insights to stakeholders in easily digestible presentations. Both help organizations leverage business intelligence to become more data-driven in their decision-making process. So which tool is better? We asked a few industry experts their thoughts on the data analysis tools Tableau and Power BI. Here’s what they had to say.

Candace Pereira-Roberts, Data Engineer & GA Data Analytics Instructor

“Anyone who works in data should learn tools that help tell data stories with quality visualizations. Tableau is a wonderful tool for the technical and nontechnical to build these visualizations. I love how we teach the Tableau unit in the Data Analytics bootcamp. I see students who are new to analytics learn Tableau desktop and be able to develop Tableau worksheets, dashboards, and story points in a couple of weeks to do a complete analysis project.”

Iun Chen, GA Instructor & Data Analyst at LinkedIn 

“In my professional capacity, I lead data visualization workshops to share best practices on charting and design theory, with a focus on Tableau. But with the growth of big data analytics, there are more players in the data viz space. Looker. Qlik, Domo, and Microstrategy are a few with out-of-the-box solutions. Check out other marketplace BI and analytics leaders and their reviews at Gartner.

Alternatively, if you are up for the challenge you can start from scratch and build out completely customized solutions through coding packages, such as with Python plotting libraries Matplotlib, Pandas, and Seaborn.”

Matt Brems, GA Instructor & Data Consultant at BetaVector 

“Most data analyst roles will expect some experience with data visualization. They may prefer your visualization experience be tied to a certain tool like Tableau or Power BI or simply want you to have experience designing graphics or dashboards. As with any platform, the human element is key. A good data analyst is curious and detail-oriented. Diving into the data and spotting anomalies or identifying patterns requires curiosity. Looking at large datasets for long periods of time can invite mistakes, so being detail-oriented ensures you’re interpreting the data correctly.” 

Vish Srivastava, GA Instructor & Product Leader at Evidation Health

 “Most teams I’ve seen are not comparing Tableau and Power BI. Instead, it’s more about whether to adopt a business intelligence tool at all, or whether to use Tableau or Power BI in place of Excel. Tableau is a great option when you need to quickly create data visualizations.Tableau is incredibly powerful because it’s designed for nontechnical users, meaning business users can set up and tweak dashboards and charts without the support of engineering or data science teams.”

When it comes to research, the most common data analytics tool is SQL — no surprise there. But once you get into more niche industries, that can vary, says Brems.

“In academia, R is probably the most prevalent data analysis tool, though Python is quickly gaining popularity. SAS and Stata are often used in specific industries, though their popularity is diminishing. (R and Python are open source tools, which means, among other things, that they are free.)”

Want to learn more about Candace?
https://www.coursereport.com/blog/how-to-become-a-business-intelligence-analyst
https://generalassemb.ly/instructors/candace-roberts/13840
www.linkedin.com/in/candaceproberts

Want to learn more about Iun?
https://www.linkedin.com/in/iunchen 

Want to learn more about Matt?
https://betavector.com/
https://www.linkedin.com/in/matthewbrems

Want to learn more about Vish?
 https://www.linkedin.com/in/vishrutps