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The Omaha Data Science Academy: What is it?

In 2008, Contemporary Analysis (CAN) began helping companies build predictive analytics capabilities, mostly through project based work. Last year, CAN recognized a rising need in companies: more and more, businesses needed to bring PA capabilities in house but lacked the staff to do so.  So, in mid-2015, CAN switched from project based work to a staff augmentation model. This last year, the need has grown exponentially as CAN has been asked to train staff for more companies, sometimes two at a time. CAN decided it needed a better, standardized way to train individuals to be part of data science team.
In July of 2016 Contemporary Analysis (CAN) announced the open enrollment for the Omaha Data Science Academy (Oma-DSA), the ultimate goal of which is to train a data scientist for every company in Omaha. With the help of Interface Web School and through the CONNECT re-education grant, the Oma-DSA was born.

Nebraska’s role in the development of the Oma-DSA:

 
Coursework in the Oma-DSA is designed to provide training to those who already have business acumen and don’t need another degree just to qualify for an entry-level data science job. They really only need skill-based training. This goal led CAN to partner with the CONNECT Grant in Nebraska. This federal grant provides Nebraska’s underemployed workforce with skill training and financial support to begin careers in IT with companies throughout the state. The partnership was perfect as both CONNECT and CAN seek to bolster Nebraska’s professional workforce with more highly trained individuals.
 

Interface’s role in development and administration:

 
In search for an example of how to teach an academy, CAN connected with Shonna Dorsey of the Interface Web School. Interface offers courses to bolster skills and knowledge of technology and online softwares to help strengthen the workforce. It appeals the most to people who may already have degrees and careers, but are looking for new opportunities. Class schedules are flexible for busy lives.
 
CAN was excited because Interface is both a platform for learning and a platform for teaching. They offer students an immersive learning program lead by industry experts and a professional network that connects students and businesses throughout the Midwest.
 
“We understand,” commented Shonna, “that first and foremost it takes talented people to build talented people.
 
This was in complete agreement with how CAN thought and wanted to run the data science, and the partnership was set.
 
“Interface is helping us setup the platform and teaching us the very detailed structure that goes into running an Academy such as the DSA”, commented Nate Watson, president of CAN and administrator of the Oma-DSA, “without them, we would still be back at step one.”

Who teaches the Oma-DSA?

 
The answer to this question sets CAN apart from many other data science courses. The Oma-DSA is taught by the data scientists who work at CAN. Each day the professors spend their time solving a problem for a client and then teach the students those same techniques and solutions. With the DSA, there are no textbooks, students are taught scenarios that are sometimes only hours old.  
 

What was the outcome of the first iteration?

 
In December of 2016, the DSA graduated 6 entry level data scientists. Four have already been hired  by local companies looking to implement data science into their daily managerial tasks. Multiple others companies have shown interest in the graduates and many others are excited to see what the next group of graduates will have to offer.
 

What did CAN learn from the first run of the academy?

 
Although the first run was successful, CAN is building improvements for  second run of the Oma-DSA starting in January. The eighteen week course will be divided into 4 modules: Python programming, statistics and mathematical modeling, database design, and data visualization using Tableau. These can be taken individually in any order. When all four are completed, the graduate receives a Fundamentals of Data Science Certificate.
 
The modular system is also significant because it allows students or company to enroll their employee in just one module. If a person were to only want Tableau and not the entire certificate, the module format allows them to enroll in only one module. This also allows a student to test out of a module as well. A Data Base Administrator, for example, won’t have to take a database design class anymore. They can enroll in the other three and receive a certificate.
 

What is the future for the Oma-DSA?

 
In the second half of 2017, CAN hopes to offer masters-level classes in Tableau and machine learning to continue education after the Fundamentals certificate. CAN is also researching customized classes in vertical-specific problems and solutions.  
The next class begins January 23, 2017. You can apply here.
There is nothing else like the Oma-DSA in the Omaha, NE and great plains area. This means that Omaha has the potential to be known internationally as a hub for budding data scientists. Not only that, but it also means that companies in Omaha have an enormous advantage by their proximity to highly educated and expertly trained data scientists.

Every week CAN will highlight a past or present CAN employee as part of a CAN alumni network series. First up to bat is Eric Burns. 

Eric Burns is a former employee of Contemporary Analysis. In 2011, he brought on CAN’s first international clients. Today he is the CEO and founder of Gazella Wifi Marketing, which turns restaurant guest information into a marketing tool. He continues to be an active member of CAN’s alumni network.

Here are his thoughts on analyzing wifi marketing:

http://blog.gazellawifi.com/10000-visits-to-a-coffee-shop-wifi-marketing-data

No matter what kind of website you are running, web hosting is the first pillar of Website Analytics. In this day and age, it is crucial to rank high with Google and Bing if you expect to draw organic traffic to your site. Many people never make it past page one–no one makes it past page two. It doesn’t matter if your website is a blog, an online marketplace, or simply a static landing page detailing what your business is and how you can be reached. The end goal is to create warm leads of people interested in what you are selling. How do we do this? By measuring who comes to the site, what they read, and how long they stay. But, how do you know your metrics aren’t skewed by unreliable hosting? The answer lies in understanding the measurements. Here are a few things you should know:

First Pillar: Reliable Web Hosting

Uptime and Speed are the key words here. People simply get tired waiting for a site that is ‘temporarily down’ or loading slowly, so they will invariably hit the back button to return to the Search Engine Results Pages (SERPs), never to return. It is through the SERPs that you gain organic traffic, so if you don’t have reliable hosting and your site is often down or slow to load, you won’t gain anything from all that SEO you so painfully worked for (or paid for) to move you up to that coveted first page of Google. Look for hosting from providers such as Flywheel or Best Web Hosting that gives you tools to maximize your up-time as well as speed. Then, and only then, can rest assured you won’t lose traffic due to inaccessible or slow web pages.

Second Pillar: Metrics

Once you are assured that you have a web hosting company that will keep your site up and running at speeds that won’t frustrate visitors, it’s time to see start tracking who is coming to your websites. Externally, this can be done by harvesting Wi-fi log-ins (Gazella Wifi), or internally (Google Analytics). Ideally, you want to track who came, how long they stayed, whether or not moved about through internal pages, or simply didn’t like what they saw and left. It should also be stated, keeping people on your website by leading them to other content is a necessity to keep them on your website, but ultimately your goal is to get them to download something or sign up for something.
How does web hosting have an impact on this? Remember, you can’t get accurate results if you are losing visitors due to unreliable hosting! Your numbers will not paint an accurate picture so your analytics will be skewed.

Third Pillar: Predictive Analytics

Once you have a stable hosting company and are measuring metrics, you can begin to do things like predict which advertisements or offers get a person to buy/interact. This is done through predictive analytics. Contemporary Analysis (CAN) uses data collected from its web site train its machine learning model to offer its potential customers articles they might be interested in. This is similar to what Amazon does with products, Netflix does with movies, and you can do with the right data.
 
Hosting, Metrics, and Analytics are the three elements that must work together if any type of website is to survive, grow, and provide leads. Without reliable hosting, your drop metrics are skewed and your click-through rates are diminished. Your website metrics will be skewed due to bounce rates due, not to bad content, but to speed and hosting. If your site is being damaged by poor hosting, I highly recommend changing hosting companies. With reliable hosting, your metrics will be accurate and your data can be used to predict customer interactions.
Your company will thank you for it.
For additional web hosting information, check out this free guide at https://firstsiteguide.com/web-hosting/. It’s a great way to get familiar with web hosting before you get started.

This summer, long time employee Nate Watson took over as president and owner of Contemporary Analysis. Situated in his new role, Watson has impressive plans for CAN’s future.
Since 2008 Contemporary Analysis (CAN) helped over 100 companies use predictive analytics to find patterns in their business data. CAN uses data businesses already collect, then explores those patterns to figure out what will likely happen. CAN has worked with some of the largest companies in the midwest including Kiewit, Gavilon, Mutual of Omaha, Blue Cross/Blue Shield, and West. CAN holds the reputation of solving the hardest problems in the Omaha data science field.
In mid-2014, after 150+ completed projects, co-founder and CEO, Grant Stanley decided it was time for a new leader to run the company. Stanley appointed then Senior Project Manager Nate Watson to run daily operations while he worked on a new project implementing machine learning into project planning and time management. Stanley’s new company, Bric, launched in late 2014.
Over the next year, Watson kept his eyes open for new ideas on how to make the culture and ideology of CAN work in today’s world. The idea for a new staff-augmentation model (see below) came as a cross between the need to provide a solution to companies that didn’t require massive political buy-in and budgets to build a POC. This idea struck a cord with two friends of Watson who decided to invest in the new ideology and buyout Stanley.

CAN’s motto is “Empower the great to build something greater.” Watson chose two investors who believe in empowering CAN to be something greater.

 
Through the transition, the mission of the company remained unaltered, albeit expanded. Watson partnered with two investors to help him with the buyout.
CAN’s new investors are Nick and Carrie Rosenberry. Both Nebraska natives, the Rosenberrys recently moved back to Nebraska after a stint in Minnesota. They bought into the business because they see a promising future in the data science industry.
“We were looking for a company poised to be on the bleeding edge of a bleeding edge industry. CAN completely fit the bill,” said Carrie Rosenberry.
Carrie is from Tekamah, Nebraska. She received her BS in Mechanical Engineering from UNL while also participating in the Raikes School. She then attended University of Minnesota Law School, where she graduated Magna Cum Laude. She will serve as General Counsel for CAN.
Watson remarked, “Having a lawyer on your team means we can build the ideology behind both the investment group and the agri-tech incubator (scheduled for development next year) using someone who understands the ultimate goal of CAN.”
Nick Rosenberry hails from Scottsbluff, Nebraska. He graduated from UNO with a Bachelors and Masters in Architectural Engineering before getting his MBA from the Carlson School of Management at the University of Minnesota. He serves as Chairman of the Board as well as general wisdom of business management for CAN.
With an on-team lawyer as well as a MBA on the board, Watson believes he has the team built to bring data science to every company regardless of vertical or size.

With the Rosenberrys on his side, Watson unveils a new business plan.

 
While not drastically changing their core business, CAN wants to change how companies interact with data science consultants. CAN aims to shift its main business model from a project model to a staff augmentation model. Previously, when a company needed a project done, they hired CAN, CAN did the job, the company paid CAN, and CAN moved onto a different project.
A staff augmentation model, on the other hand, means that CAN actually provides a data scientist to work directly for the client. By giving businesses the option of hiring a part-time data-scientist, companies no longer need to sift through projects and create extra budgets. It instead allows a company to test out how a data scientist would work in their culture, figure out how to implement ideology, and create the necessary roadmap for success long after CAN’s data scientist has been replaced with their own.
This however, has created a new problem: how and where to recruit the talent necessary to continue data science initiatives after CAN as a consultant has left?
CAN believes the answer lie in one of its new creations, the Omaha Data Science Academy (Oma-DSA). The Oma-DSA is a twelve week course designed to train entry-level data scientists who have business acumen but lack a few of the key skills needed before they take on corporate projects.
The Oma-DSA is designed to augment a person’s existing degree with advice and training from real data science experts in the field. This should provide talent, trained in entry level data science for companies to hire to run their new capabilities.
The first run of the Oma-DSA is this September.

Nate Watson and everyone involved with Contemporary Analysis is ecstatic about these new ventures.

 
CAN has always empowered the great. Under Nate Watson’s new ownership, CAN now has the time and resources to empower greatness within itself.
For more information on the Oma-DSA, or anything you liked about this article, contact Nate Watson below. 
[contact-form-7 id=”4573″ title=”PR Contact Form”]
[contact-form-7 id=”4528″ title=”Omaha Data Science Academy Form”]

CAN is excited to announce, in partnership with the Interface Web School, the creation of Omaha’s first Data Science Academy (ODSA). 
This is something we have been working on for a long time. It is actually a continuation of a service we currently offer to clients where we train a company’s first data scientist. We feel this unique person, trained in both data science and business problem solving, is needed by their company to help implement the ideology more than produce mathematical models or produce visualizations.
In the past, we heard that while companies know how to find and hire a data scientist, they fear not being able to utilize this person or even know how to correctly scope how to use predictive analytics in their business. This caused them to not execute or to execute poorly and leave a bad taste in the organization’s mouth.
CAN has discovered that having a data science advocate (instead of just a data scientist) usually fixes the hangup with implementation in most companies trying to use data science for the first time. The realization there was a considerable lack of talent when looking to fill this need, led us to develop a school that teaches not only entry level data science, but also how to address the political red tape prevalent in changing how an operation thinks and makes decisions.

This academy will help CAN reach its goal of putting a data science advocate in every company in Omaha. While audacious, we feel this is a must to keep Omaha companies relevant in an economy where we are not just in competition from a company down the street but from every other company doing similar work around the world.

 
Details.
This certificate will teach some of the most important techniques and tools necessary to introduce data science into company culture, get necessary political buy-in, find, manipulate, and analyze the data present inside your company’s database, make predictions of outcomes, and create visualizations that can help non-technical users understand and see the identified trends and patterns inside the data.  
The ODSA is designed to help set a company down the road of data discovery and data-driven decision making. While not the heavy mathematician or economist created by four year degrees, the graduate will leave the Academy with the confidence and the skills of an entry-level data scientist and be able to have conversations with business units, build predictive analytical MVPs, and be able to know and manage the skill sets needed for future data scientist projects.

The Certificate consists of 4 Modules: 

• Basics of Python Programming
• Data Manipulation and Management
• Statistics and Computational Modeling
• Data Visualization

All classes meet 2 nights per week for 20 weeks over the course of 28 weeks for a total of 154 hours of in-class instruction to complete the certificate.

 
For more information on course offerings and to apply, go to www.canlearnsmart.com
You may also contact Nate Watson, director of the academy, at nate@canworksmart.com if you have specific questions about offerings or custom classes. 
 
[contact-form-7 id=”4528″ title=”Omaha Data Science Academy Form”]

Contemporary Analysis (CAN) is recognized nationally as a leader in the data science field and is regularly asked to “Spread the Good Word of Predictive Analytics” by presenting on various topics at conferences around the US.  In fact, CAN has presented at six conferences in the past 14 months, including:
 

• InfoTech– Omaha, NE- “Politics and Big Data”
• 2015 Predictive Analytics World– Chicago, IL- “How Predictive Analytics Fundamentally Changes Marketing”
• Internet of Things Summit– Overland Park, KS- “The Implementation of Data Science into Production”
• Big Data Summit– Kansas City, MO- “Finding and Managing Data Science Talent”
• Vistage Sales Seminar– Omaha, NE- “Improving Sales and Customer Service using Predictive Analytics”

• 2016 Predictive Analytics World– San Francisco, CA- “How to implement Predictive Cross-Sales” 

 
CAN is thrilled to spread the word about the data revolution that the world is undergoing, and about the business advantages that can be exploited from understanding that data.  Because data science is an emerging field, many firms have questions about:
How do companies implement data science?  
How should data scientists be managed?  
 
Here are some important things to consider:
Every current data scientist comes from another field
Because data science is a new field, there is very little formal, university training available.  Although data science programs are under development at UC-Berkeley, Northwestern, and UN-Omaha (among others), current data scientists have all made the transition from some other area of expertise.  Some of the most common fields producing data scientists are Mathematics, Economics, and Political Science, and other scientific professions that measure and use data.
Data Scientists are not your average employee
Data scientists feel an innate need to solve problems.  This causes them to be creative thinkers who can think outside the box and operate when there is no box.  They tend to get deeply invested in problems, and use their creativity to find or simulate the right data.  Data scientists are tenacious, and because they place such a high value on finding answers, it is paramount that their solutions be utilized.
Managing a Data Scientist can be tricky
Data scientists are not necessarily businesspeople.  It’s a manager’s job to understand what a data scientist is trying to say, and to help them explain what their solutions mean to the rest of the company.  Additionally, data scientists are not to be managed agilely – the time it will take to find the answer to a hard problem cannot be predicted or scheduled.  Lastly, it is imperative that data scientists not be moved from projects or given menial tasks: they will get bored and leave.
Implementing Data Science is also tricky
There’s an old saying that “it’s hard to teach an old dog new tricks”, and this idea translates to business practices.  It is often difficult for firms to embrace new, proactive methods when they’ve been doing things the same way for years.  Occasionally, resistance to the implementation of data science is borne out of a fear of what will be found – data scientists are known for shining a light in places where light has never been shone before.  Another challenge is being patient once data science has been implemented.  Data science is very difficult, and predictive models require considerable fine-tuning before their true potential can be realized.  Confidence and complete company “buy in” is crucial to the implementation of predictive analytics, particularly in the earliest stages.  
The rewards are immense
When properly implemented, predictive analytics will take a firm to previously unattainable heights.  We live in an age where information is king, and firms who learn to obtain more accurate information in a shorter amount of time will have a distinct advantage over those who do not.  Generally, the first step down this road involves implementing data science. There exists a staggering amount of information in your company’s data… all you need is the key to unlock that knowledge!
 
Let us know how we can help you build predictive analytics into your company. We would be glad to help.
For more information or to gain knowledge as to who and how we have helped implement predictive analytics, go to our website at:
www.can2013.wpengine.com
or connect with the president on LinkedIn at: http://www.linkedin.com/in/natewatson
or send us an email at:
support@canworksmart.com
Download our Predictive Analytics ebooks:
[contact-form-7 id=”4029″ title=”Predictive Analytics eBook”]

Recently, Contemporary Analysis (CAN) was asked by the Indianapolis Business Journal to weigh in on how Predictive Analytics is changing the marketing space. We believe by combining predictive analytics and marketing, called contextualized marketing, marketing can move closer to the holy grail of one person, one sale.  Most companies do this by purchasing a software–it’s dactyl, most companies have a line item in their budget, and it gives a third-party marketing company reoccurring revenue. While CAN itself doesn’t have a piece of software to sell, we believe that contextualized marketing is the right move for companies and that those with the edge are “the ones using data scientists to predict who inside of a group of people have the propensity to buy.”
Because CAN doesn’t have the software solution, we approached the solution from a slightly different angle. We provide modeling and results in way that can be easily added to your current tracking software. This way, a company can begin the transition from shotgun marketing to tactical marketing with a low cost of entry. Once implemented, the case can be made for the software using predictive analytics to be purchased and used if needed.
Additionally, because software companies provide a tool and very little in the way on why the tool is important, most software implementations fall flat. We believe our value is helping companies manage the change management necessary to implement the software and to understand how to use them effectively–which greatly increases both the adoption and the ROI from the adoption.
Let us know how we can help you build data science into your marketing. We would be glad to help.
For more information or to gain knowledge as to who and how we have helped implement contextual marketing, go to our website at:
www.can2013.wpengine.com
or connect with the president on LinkedIn at: http://www.linkedin.com/in/natewatson
or send us an email at:
support@canworksmart.com
 
Full article IBJ article:  http://www.ibj.com/articles/54753-smarterhq-gobbles-up-venture-funds

Contemporary Analysis (CAN)–A new president of CAN was announced earlier this month. Nate Watson, long time employee, Sr. Project Manager, and Head of Sales will take over for Grant Stanley, in early June. Grant said the lead change was a long time coming, “I am staying on as the Chairman of the Board so I can provide vision and strategy, but I am relinquishing the day-to-day operations to Nate.”
This change comes as Grant takes over as CEO of a new startup, Yield. Yield provides a tool for design and marketing companies to better project staff capacity for a given scope of work. It allows management to know how much work a designer has left and alerts the manager to when the designer is running out of work. Yield and CAN will remain close as the two are set to do work for each other for the rest of the year. “It will be a great predictive project for CAN”, says president-elect Nate, “Yield gets the leadership of Grant, we (CAN) gets to keep the strategist and visionary our company is known for, and we (CAN) get to build predictive analytics into a new product slated to change a whole vertical.”

New Leader

Nate has been steadily taking on more and more of the operations since mid-2014 when he began managing the projects he was selling. It was an important step for the company because it no longer meant there was a drop off in knowledge between setting up the project, and the implementation of the project. “We will operate like we always have. We will help companies use their data to understand and get a better handle on how to make decisions faster. When you let data do some of the heavy lifting, it’s amazing some of the insights a leader can get. They still have to make the final decision, but predictive analytics gives them access to relevant data to make decisions in seconds instead of spending hours combing through a pile of reports.”

New Verticals

Nate also brings new energy and ideas to the business. After adding political campaigns to CAN’s capabilities in 2014, Nate managed 2 governor campaigns, 2 local campaigns, and 2 bond issues. In fact, politics became 33% of the total business CAN secured in 2014. “We faired pretty well getting 3 of 6 through the primary and going 3 for 3 in the general.” In fact, CAN predicted the turnout of the primary election to within .27% or 876 votes out of 324,227, and the final vote count to within 2.8% or 1,577 out of 56,324–all 3 weeks before the election. These numbers catapulted them into the spotlight for regional and national campaigns and many took notice. To date this year, CAN has taken on a Governor campaign, two ballot initiatives, and looking to add a presidential candidate later this year.

New Ideas

CAN is working on a number of new ideas as well. Later this year, they are going to release their first piece of software. CAN’s analytical software is designed to help non-mathematical leadership interact with and learn from their data without the need to employ data scientists and includes the ability to run scenarios on live data. This will accelerate political buy-in and implementation time of analytics into a company. Their software will give CAN an entirely new revenue stream and will allow CAN to sell to much smaller companies. “We are hoping this product allows all companies to use their data to create better marketing, sales, customer retention, HR, and forecasts,” says Nate.  The system is slated to come out in the fall.
CAN is also being asked to develop auditing capabilities as well as a predictive analytics and a data science recruitment arm. “Finding, hiring, and training data scientists is a real problem for companies. The lack of data scientists is the bottleneck we think we can solve. We understand how to attract and vet data scientists better than traditional HR and hope we can partner with companies to lend them our knowledge.”
With these new ideas and growth, CAN is also going to need more staff. Currently open are positions for two new data scientists and a sales person. “We are looking for those individuals who are gritty, and can solve a problem when the solution isn’t easily found. This goes for both data scientists and salespeople.” “After all,” says Nate “finding solutions to problems–really hard problems–is how CAN has been known for the last 8 years.”
 
More data on Contemporary Analysis can be found on their website at: www.can2013.wpengine.com or by connect with Nate Watson on LinkedIn at: http://www.linkedin.com/in/natewatson