Data Analyst

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Are you interested in human behavior?
Do you like to tell stories that persuade people?
Are you detail oriented?
Are you good with numbers?
Is it your mission to help make the world a better place?

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Data Analysis could be your future path

“Understanding and innovating with data has the potential to change the way we do almost anything for the better.” Watch President Obama explain the importance of data science.

Running the government and managing a business requires making informed decisions. The government asks, for example:

Are there enough beds in city hospitals to cope with a health pandemic?
How many people take a bus route every morning, and does it need more frequent service?
Why has the pandemic affected college enrollment?
Which buildings have the most number of tenant complaints?

Businesses ask, for example:

What new services can our business offer to attract new customers?
What was our daily revenue last month compared to the same time last year?
Should we produce more red bikes or blue bikes next year?
Should we open a new office in Austin, Texas?
How can we keep our workers motivated to stay on the job?

Want to try it out now?

You heard President Obama say that the government is making vast amounts of data available for public use. Anyone can use this data to answer questions, solve problems and innovate. Many cities, including New York City, have an Open Data project.

Pet Project

Try this ‘pet project' that involves data about dogs. What can you learn about the city’s dog population and dog owners? How could you use this information if you want to start a dog walking or pet grooming business?

Steps:
1. Gather the data - NYC Dog Licensing Dataset
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2. Review the “fields” of information contained in the data set.
a. How many licensed dogs are there in NYC?
b. Is there a trend to owning more or less dogs over time?
c. How much does it cost to license a dog?
d. What are the most popular dog breeds in NYC?
e. What can you learn about dog owners? For example, in which zip codes are the highest number of dogs?
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3. Besides the open data sets, what other information can you find out about what’s happening in New York with dogs? For example, what can you learn from:

App Project

Suppose you work for a client that wants to create a mobile app that will have the largest amount of downloads possible. This means the app has to be very useful or desirable.

The client has asked you to use a small population set in California as a test group to investigate and identify which types of apps would be popular among users. They want to predict which kind of app would result in the most downloads.

Step 1
Click on this link to view your test group.

Step 2
Gather information about your test group. Look for things they have in common. This will give you insight into things they may need or want - and what apps could make their life better.
-Click on the graph button located on the top left. If you click on the left hand title it changes the variable/attribute represented in the graph.
-When you select income you notice that many people earn less than $40,000.

With this data which of these apps would you recommend:
1. an app that offers luxury vacations
2. an app that shows local free job training programs

Step 3
Now come up with your own data set to analyze.
‍Communicate your findings to the client - what type of app is likely to have the most downloads among this small sample community?

Meet a few Professionals who work in the Field

Here are some ‘day in the life’ stories you can read about people in the data services field:

Meet Data Analysts at Google

Jenny Rogers

GOOGLE

REALISTIC WFH DAY IN THE LIFE OF A DATA ANALYST | CAREER LIFE | Ohema Nae

Jenny Rogers

GOOGLE

real talk about my Data Scientist jobs + salary for entry level data science

Jenny Rogers

GOOGLE

MY NON-TRADITIONAL JOURNEY TO BECOMING A DATA ANALYST | BLACK DATA ANALYST | CAREER LIFE | Ohema Nae

Jenny Rogers

GOOGLE

Kim Arcand, NASA

Jenny Rogers

GOOGLE

Understand the Business

Consider where you can work.

With the emergence of faster, cheaper and more powerful computers, more sophisticated tools and techniques for analyzing data have emerged. The data storage and computing power of a machine that used to be as large as a football stadium is now contained on your phone. What used to take years for a computer to calculate can now be completed in a matter of minutes or seconds.

Data Science has emerged as a field that can answer sophisticated questions with data.. Data scientists use machine learning (for example, a machine can be trained to recognize images), algorithms (which combine a wide range of complex data inputs to come to a conclusion) and build predictive models to suggest a future outcome. At the heart of all of these more sophisticated techniques is the work of the Data Analyst – acquiring, cleaning, housing and understanding the data you need to answer both simple and complex questions.

Data Analysis provides a foundation for technical careers in Information Technology (IT) such as data engineering, systems integration, database administration, data warehousing, business intelligence and reporting, cybersecurity or cloud computing.
Data Analysis is also a pathway into business operations. For example, learning about financial data can lead to a career path within Finance (such as a Financial Analyst), including a leadership function such as head of financial analysis or revenue analysis.
Data Analysts work in every industry, and for governments and nonprofits. There is even an emerging field for journalists who are skilled at analyzing and describing data for the public in the news!

Data Analyst vs. Data Scientist: What’s the difference?

Data analysts and data scientists both work with data, but what they do with it differs. Data analysts typically work with existing data to solve defined business problems. Data scientists build new algorithms and models to make predictions about the future.

The Job Outlook

Jobs in data fields are in high demand. The US Department of Labor terms this a ‘bright outlook’ career path. LinkedIn predicts that there will be 11.5 million jobs in data fields by 2026.

Nationally, salaries for data-related jobs range from $59k to $167k, with the median salary hovering around $100k. In NYC, the average base salary is around $86k.

To learn more about the job outlook: Why Choose Data Science for a Career.

Career Paths

There are many paths to a Data Career.

Project Management is a field where you can create your own pathway. Read how Noorbani, Amina and Chris got started.

The Business Operations Path

An accessible entry point is to start as a data entry clerk. These entry level jobs involve entering data via spreadsheets or data platforms:
Data entry typically involves entering data on spreadsheets like Microsoft Excel or Google Sheets. These tools are central to any career with data.
Most businesses and nonprofits track data relating to sales with Customer Relations Management (CRM) software, like Salesforce. Learn more about CRM.
Data entry is important because mistyping information can have real world consequences. People can miss an appointment reminder, be given the wrong drug or receive the wrong information about a party or package!
The step beyond data entry is data analysis - collecting, synthesizing, interpreting and presenting the data. A Data Analyst is the most common starting point in any sector.
Data Analysts can have specialist skills. For example, Business Analysts, Financial Analysts, Marketing Analysts.

Large companies often have Data teams, for example:

An image of the Org chart for a data science team

People in this short video explain some career pathways, starting from a Data Analyst.

Viewpoints: Career Options for Data Professionals - Career Opportunities and Data Analysis in Action | Coursera

Skills to Pay the Bills

Take stock of the skills you already have:

You are a problem solver. You are good with numbers.

You enjoy math, including statistics and algebra. You always ask questions and look for ways to find the answer. You enjoy making connections, finding patterns and solving problems.

You don’t need a technical background but you should know your way around a spreadsheet.

You can learn many of the programs as part of your training, but it will help if Microsoft Excel/Google Sheets is your friend. You should not be intimidated by these programs and you can learn the basics on your own. There are free resources such as Grow with Google and Microsoft Excel training.

You are a good communicator.

You can find a way to tell complex stories simply, often without words but through images, charts and other graphics. You enjoy working on a team where people have different perspectives and you can add your own ideas, backed up with evidence.

Skills you will Learn

There is a continuum of skills to learn.

Foundational Skills - learn on your own:

Math skills
Spreadsheet skills
Basic SQL Programming Skills

Advanced Skills - learn through training programs:

Analytic Skills and Tools such as R/SAS
Database Skills and Tools such as Advanced SQL
Coding, especially R, Python, Java C/C+
Data visualization skills and tools, such as Tableau or Power BI

Certifications are important attestations of skill. Examples include:

Postsecondary training is essential

Pursue a college degree and major in Computer Science or Statistics or Math
Enroll in a boot camp like Merit America or take online workshops through organizations like Data Camp. But before you enroll, please read the section of the Toolkit on “Navigating Training Pathways” - it will help you evaluate training programs and understand certifications. Be sure to look into free programs and avoid paying for a course until you are very certain that this is a career path with a job outcome for you.
Get started now! For free! You can
Pursue a certificate program like Google’s Data Analytics
Start earning credentials through Salesforce Trailhead for free
Begin a free trial Introduction to Data Analytics with IBM

Review a Job Description

Job Descriptions are the way a company recruits and hires talent. You can learn a lot from a Job Description about the skills and qualifications you need to prepare for the job. Even if you are not ready to apply for a job now, reading the Job Description helps you prepare.

This company [name withheld] is hiring a Junior Data Analyst. This is an entry level job. Read the job description and take note of all the skills you need to apply for the job. As you read, look for technical skills that you will need to learn, and behavior skills that you are already good at.

GET PREPARED

Make Your Plan

Be ready to apply to this job in a few years by writing a paragraph of less than 250 words explaining why you want the job and why you will be a good fit for the company.

In your paragraph, include:

Why you want to pursue a career in Data Analyst and specifically what aspects of this position interests you
What skills you have that will be an asset for this kind of job
What skills you need to learn after high school, and what certifications you intend to pursue
What is the career path you see for yourself in the future?

Keep this paragraph as part of your career plan.

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