Personal View: Cleveland's Digital Future Must Have These Elements

Personal View: Cleveland's Digital Future Must Have These Elements

In the world of information technology, there is a distinct advantage to being either a first mover or fast follower. Company wealth formation and catalyzing regional economic development accrue to those who harness one of those two strategies.

So, here are five ideas for advancing the region's data analytics capabilities, from 2017 to 2025...

5 Steps To Get You Started with Data Analysis 

5 Steps To Get You Started with Data Analysis 

Many aspiring data analysts or others who want to learn how to use data better have likely Googled “How to start learning data analysis”, only to be confronted with millions of search results suggesting everything from SQL, R, Python, Tableau, PowerBI, to classes from DataCamp, DataQuest, Udacity, Coursera, and Galvanize.  While this is useful information, the sheer amount of it is very overwhelming.

From a largely self-taught data analyst (I studied economics in college, but saw the writing on the wall that the need for and use of data was in every organization and an in-demand skill), here are suggested first 5 steps to help you clear a path through the jargon and buzzwords and get to the data.

  1. Understand the process of data analysis

  2. Learn statistics

  3. Maximize your prowess with Excel

  4. Learn a data visualization tool like Tableau

  5. Consider a scripting language, like Python or R

3 Reasons to Learn Data Analytics

In today’s data-rich world, whether you’re an entry-level worker or a Fortune 500 executive, a doctor or a programmer, a marketer or a teacher - there’s a benefit to learning how to analyze data. No subject area is immune to getting the data treatment.  

ESPN teams with Five Thirty Eight for regular stats and data analysis so you can understand sports from every angle. Data scientists at OkCupid and CoffeeMeetsBagel build algorithms to help people find love. At the New York Times, data journalists reshape how their readers consume information through data visualizations.

With so much data around us, understanding how to use that data effectively can help you to expand your skill set, critical thinking ability, and career trajectory.

Here are three great reasons why you should pick up some data skills...

Innovating Lake Erie- The Start to a Smart Lake

Innovating Lake Erie- The Start to a Smart Lake

Innovation has long been a part of life and work on the Great Lakes. The unique water resources of this region set the stage for the greatest period of technological advancement the world has ever seen and continue to drive one of America’s most dynamic regional economies. Despite their essential role in our commerce, industry, and entrepreneurship, the Lakes are consistently undervalued as an economic asset and catalyst of innovation. However, the systemic undervaluation of our Great Lakes has not gone unnoticed.  The Cleveland Water Alliance (CWA), a collection of forward-thinking research institutions, industry leaders, environmental organizations, and public utilities, came together to develop a new way of thinking about regional economic development. This framework focuses on creating a Blue Economy where innovating and monetizing solutions to water challenges replaces continued pollution of our resources as a key driver of prosperity.

Creating a Data Smart Culture through Learning

Creating a Data Smart Culture through Learning

Now, data is everywhere. You can track what you eat, how much you walk, and what you wear.  It’s not just personal data for yourself either.  Every organization also wants to know how to get value out of data and apply to real life situations as quickly as possible.

From nonprofit organizations to the largest healthcare organizations to businesses big and small, data skills are in demand across all industries.

Why? Because data is one of the best way to predict outcomes, help fix a problem before it becomes a crisis, and to find relationships between details you may not have considered before. With that in mind, organizations are asking: what data skills are the most important for my team to learn?

Tyler Byers, Data Scientist and Machine Learning Engineer at Itron said it best at a Meetup of aspiring data scientists, “The most important skill for a data scientist is to know how to learn, and how and where to acquire new skills.”

This more than anything is what can help professionals who have no formal training in data skills get up to speed fast. Being willing to learn new skills is what will help organizations fill the data scientist gap that exist on staffs now.

DigitalC Makes Learning Data Skills Easy

Being open to learning is the first step. The second is knowing how and where to acquire new skills. For this reason, DigitalC has created three types of data analytic bootcamps with a focus on data skills for professionals: The Data Analytics Workshop, Data Science for Analysts, and Data-Driven Executives.

Unlike online courses, these workshops and bootcamps are taught in small cohorts in-person,  focused on specific data questions or areas for analysis.  Our corporate bootcamps are designed with executives and managers prior to beginning.  Working with managers and IT staff, the data available in the organization, governance and access policies, and top goals for the organizations are identified. We tailor the bootcamps ensuring that what’s learned supports staff with their daily work when they leave the class.

Case Study: Data Science for Analysts in Healthcare

Recently DigitalC designed a 10-week Data Science Analysts in Healthcare bootcamp in conjunction with the executives and managers of University Hospital with the goal of training a cohort of 15 employees on how to gather and uncover data to solve pressing data questions to improve performance.

After taking the Data Science for Analysts bootcamp focused on R, Abby Williams, Operations Analyst at University Hospitals says “Digital C helped me think outside the box and understand the true meaning of exploratory analysis”

Now Abby and others are using R to describe, summarize, and filter data; using visualization tools to plot, chart, and share results; and using design thinking as a new mindset to find the best solutions for their problems.

"Putting the power of data-driven insight into the hands of those whom can best act on it is paramount to UH's success. With the tools DigitalC can teach, we can help build a broader and deeper team of data-savvy employees to lead these activities. I am excited to see what innovations and insights these new tools will bring to the organization," said John Shanahan, Manager Enterprise Data, Reporting & Analytics at University Hospital.

Sing up HERE for our upcoming Data Analytics Workshop Oct. 10-12. 

For more information on the Learning Studios or the R Bootcamp, visit the Learning Studios page, or contact Kauser at