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7 steps for getting started with data as a business person

Getting started in data can be overwhelming in today’s world. The hype machine of Big Data and Data Science makes it feel like you need to learn 3 different coding languages, 4 BI tools, and have a PhD level skill set in machine learning and statistics.

Case in point. A couple weeks ago, I was in Chicago doing a Data Visualization and Storytelling workshop. After the day-long training, an attendee asked if I could chat. She had been tasked with building some executive dashboards for her small organization and fell in love with data and driving more meaningful analytics. So she started doing some research about moving into the field. But after reviewing several job descriptions, she felt completely lost and pretty discouraged. There was no way she would qualify for those kinds of jobs without going back to school and spending countless dollars and hours.

I assured her there were LOTS of jobs out there for her skill sets, which included Excel, business context, communication, project management, and translating needs into requirements. But, those aren’t obvious to a person just getting started.

If you’re a business person and want to get deeper with using data here are my seven recommendations to get started:

Ignore the hype

There is a real need for great data scientists in this industry. But you’re not going to be one of those. At least not in the next couple years. The good news is that for every 1 data science job, there are 10 business analyst jobs that are just as critical. People who can translate the business. Who can project manage and communicate effectively. Who can drive change management and adoption of data-driven approaches. Those are the jobs for you.

Identify and focus on your unique talents

Focus on the skills you DO have, not the ones you don’t. Perhaps you have an accounting background. Maybe you are great at training people or speaking? Do you like listening and empathizing with your peers and leaders? Find what makes you, uniquely you. I bet your organization will benefit from combining whatever that is with data.

Raise your hand for data-related projects

You DO need some understanding of how data works, and you need to prove it. I once hired a person with virtually no professional experience over a person with 6 years of data 7 analytics experience. Why? Because the no-experience person during a summer internship had raised her hand to do some reporting, found Tableau, tried their free trial and got the whole department to start using it. Organizations want people like that.

Pick a tool

There are a mind-boggling number of data and analytics tools out there. Nobody can learn all of those tools. Pick one and get started. Most of them behave similarly enough that once you learn one really well, you can pick up most of the others well enough. Remember, you don’t need to be everything to everyone. Get good at one thing and build to the rest.

Take a class or workshop

You don’t need to go back to school to be a great analyst. But you can easily pick up some of the basics through cost-effective online or in-person programs. Udemy, LinkedIn Learning, Udacity, and Coursera all offer good self-paced programs for reasonable prices (stay away from the “data science” programs to start). Want a more guided and personal format that’s still cost effective? Check out our programs from Beyond the Data, which are tailored to business professionals like yourself.

Consume lots of blogs & podcasts

There are so many great free resources out there from leaders. Just start reading and listening. You’ll pick up all kinds of useful information on how to become great at using data. Blogs like Storytelling with Data, Flowing Data, and Visualizing Data. Podcasts like Data Skeptic, Data Stories, and Present Beyond Measure. We’re also pretty partial to our own podcast: Data Able.

Join a community and learn from leaders

Getting connected to other people like yourself is THE best way to jump start your new direction toward a data career. You’ll meet influential leaders in your local area who know the right people and can help you navigate your local market. I guarantee they will be willing to coach and mentor you along the way. That person from Chicago? She started networking and within a week had eight (8) different leaders reaching out to HER about their open jobs!

I can hear it now… “That’s all fine and good, but the job description says I need 3 years of SQL and 5 years of Python!” Yep. HR put those requirements on the job description. One of three things will happen if you apply:

  • The hiring manager actually needs those specific skills and you won’t get the job. You probably don’t want a job that technical anyways.

  • The hiring manager is willing to overlook some or all of those technical skills because teaching technical skills is way easier than teaching people/business/soft skills.

  • The hiring manager just copied and pasted the job description from a different role and doesn’t really care if you have it or not… they were just trying to weed people out.

My point is don’t let yourself be stopped by silly things like “x years of z tool.” You have unique talents that you can bring to the table. Fuse those talents with data, and you’ll be a data rockstar in no time.

Good luck and happy analyzing!


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When Technology and Creativity Collide - EYEO 2019

Last week I (Dave) had the opportunity to be back at one of my conferences, the Eyeo Festival. What makes Eyeo Festival great is it brings together people from all over the world around art, creativity, technology, data, and social impact. You get discussions around science, machine learning, social justice, art, data visualization, and more and many of the sessions cross multiple disciplines.

One of the key takeaways for me was learning to create better spaces and communities around us. The cross-discipline nature of an event like this opens up so many avenues to creatively address business and social challenges, and in turn makes it easier for people to harness the power of data.

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To give you a sense of just how diverse an event like this can be, here are some examples of the people I met and the conversations I had…

A person came by my table saying he needed our input on visualization. We chatted for a bit, discussing the challenge he was having, without realizing we were talking to famous Bre Pettis, who co-founded MakerBot, a fantastic company that pioneered affordable 3-D printing! Such a cool opportunity to kick around ideas with amazing and talented people!

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I had to laugh when we got into a fascinating discussion on better transportation approaches in large cities. Turns out we were talking with employees from both Google and Uber!

This night is just an example of the excitement Eyeo can bring or really any event where you bring diverse, creatives, and technologists together that have a shared mission.

Needless to say there was no shortage of knowledge being shared and absorbed. Eyeo is a reminder for me that I can never stop learning and sharing. The world is always changing and the challenges are always developing where we can play a small part. Find a way to share something with others and always a way to learn something new from others.

Beyond interesting conversations, there were also great sessions to attend. While I don't like to call favorites, one session I found fascinating is Darius Kazemi discussion around the FriendCamp network that he started. FriendCamp is a “local” social network that is intentionally kept very small with only Darius and a set of friends being allowed in.

Darius encourages others to think about creating a similar type of network. This is somewhat of a natural pullback of the not-as-free-as-we-think culture we live in where our data is sold to others and privacy is challenging. He says it is about taking responsibilities of your data and something we should be doing no matter at home or work. If you are not aware of your data, who has access to it and how, and what it is being used for then don't expect anyone else will treat it any better.

While I certainly agree with some of Darius's premises, I also realize not everyone is going to maintain a social network server and rigorously identify and maintain their private social network.

Thank you everyone that came to #Eyeo2019 and the entire team that puts it on because this event is really inspirational. Hope to see you at #Eyeo2020 back in the Twin Cities.

Quick side note: During Eyeo I had the chance to record Data Able podcast episodes with both Nadieh Bremer and Catherine D'Ignazio. Nadieh and Catherine are both phenomenal people putting out great work into the world and sharing information. Make sure to check out their work and subscribe to the Data Able podcast so you don’t miss their episodes when they drop later this summer. 

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Data Literacy is HOT at Minneanalytics Data Tech 2019

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For people on the technology side of analytics and data science, there can often be a sense of frustration that the business teams don’t fully understand how to use the data, models, insights, and reports that we create for them. Business teams need to DO SOMETHING with the data, or you won’t see the ROI on your analytics projects.

Matt and Dave checking out the vendor hall at Minneanalytics Data Tech 2019

Matt and Dave checking out the vendor hall at Minneanalytics Data Tech 2019

Matt and I had the opportunity to speak about exactly this topic at the 5th Annual MinneAnalytics Data Tech 2019 conference in the Twin Cities last week. The conference was buzzing with energy this year, with over 1,300 people registered!

We were interested to see how a Data Literacy topic would be received at a conference designed for Data Science and Information Tech people. It turns out that both business and technical people are interested in improving the fundamental data capabilities of their organizations, as 200 people signed up for the event!

Our key message was simple: If you’re an analyst or data scientist, and feel like the business team doesn’t quite “get” what you’re doing… start building relationships with them! Data Literacy for your business teams start with you. They know that data can help them, but you need to bring them along the journey.

To that end, here are our three ideas for Data Science, Analytics and BI teams to start dipping their toes in the water of data literacy for their organization:

  1. Find a business buddy. Get at least one and more preferably business buddies where you can share your knowledge around the power of data literacy. In turn you can get more knowledge around the business domain. Seek out people that are in a similar stage in their career but on business side. important: This is different than and not a mentor relationship.

  2. Do a data viz challenge or hackathon together. Working on the same team in a close time-boxed competitive environment with those that are business-side people will help you empathize and respect them more with them and vice versa. Remember we talk about diversity and it's strength and an element of diverse teams is different organizational backgrounds.

  3. Judge a student data challenge together. There are a lot of student analytics challenges nowadays and they are always looking for judges. Find one and get your business buddy or another business-side person to participate in this challenge as a judge. You will both be better able to understand more of your strengths from the questions you each ask and engagement with student teams. Plus you will be doing a social good by doing this and better helping these students understand different perspectives from an organization.

Thank you MinneAnalytics, their sponsors, and everyone that attended Data Tech 2019 and especially those attending our session. We love coming to these events to see just how powerful a community’s passion around data can be.

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5 Things Executives Must do to Support a Data Culture

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Executives today are faced with many pressing needs. Customer success, your P&L, internal politics, shareholders and investors, managing your teams, strategy and goals, keeping your key projects moving forward. But there’s a new growing factor to add to this never-ending list: Data.

You hear about it from Harvard Business Review. You hear about it from Forbes. You hear about it from McKinsey, and the Wall Street Journal, and CIO. You hear about your competitors doing things with data to get an edge.

In a previous article, we talked about the critical components of making data work in your organization. Hint: It isn’t just investing in a data science team and then waiting for profits to roll in.

Culture change must be part of the equation. Probably not what you wanted to hear, but that’s what it’s going to take. Changing your team’s culture takes several things, but the critical part we’re discussing today is the top-down approach.

Here are the five starting items that executives need to consider when implementing your data culture change.

Support a data-informed decisioning culture

This is first because without this then there simply isn’t anything else. Everyone in your organization must be on board to seek out data, learn from data, and make decisions based off analysis. A core tenant of hiring, promoting, and rewarding people needs to be off of strong data-informed decisioning. This applies just as much to executives themselves as their staff. Too often data is produced to back a gut-based decision and proper analysis and experimentation not performed. Then, when something does not workout then people raise their hands saying the data told them to do so but instead data just supported the desired outcome. There is a component to this item which requires that data and ability to access and analyze it must be put in place and maintained through proper data governance and self-service business intelligence platforms.

Support your Key data champions

Every organization needs data champions to keep your momentum going. You should have many of these data champions, embedded in the business lines, singing the praises of analytics and what data can do for them. Who are your data champions? Are they being recognized, rewarded, and empowered in their efforts? It is vital that executives understand that data champions are needed to drive data culture bottom-up.

Support data-informed decisioning technologies

It is no surprise that having appropriate data and analytics technologies available for not just the analytics teams but also the business teams is a must. Having the proper tools to do the job whether it is Tableau, Qlik, Power BI, Domo and others. That data and ability to access and analyze it must be put in place and maintained through proper data governance and self-service business intelligence platforms.

Support an information-sharing culture

It is not alright for departments to silo off data so they can benefit from it and other departments can’t. Yes, there are instances that data cannot be shared for various data privacy reasons. But, when data is shareable within an organization, the default should be to do it. It is not alright for departments and people to indiscriminately put up data silos against other areas of the company.

Support organization-wide data literacy

Data literacy is essential for all of your employees. This doesn’t mean that everyone needs to be a data scientist. In fact, there are different levels of data literacy needs depending on organizational roles. First, understanding your employees’ data literacy is essential. Then, helping those employees close data literacy gaps with training that is done in an engaging and practical way.

All these items are essential for executives to drive a data culture. However, it is really important to point out that executives must eat their own dog food. No longer is it alright for you to tell others to do what you say, now what you do. Demanding data in your own decisions and even getting hands-on with an executive level dashboard should be expected.

Taking these items and putting into practice will help create a data culture at your organization. Then, everyone will not only be speaking the language of data together and making decisions on analysis in a sustaining data culture.


This article appears in a series of blog posts about Data Culture, Data Literacy, and why it matters for organizations to think beyond Data Science. If you liked this article, make sure to read the rest of the series:

Five Reasons Why Data Culture is Just as Important as Data Science

The Key Roles of a Data-Informed Organization

Who is Driving your Data Culture? The Role of the Data Champion


Beyond the Data is on a mission

We help organizations like yours to build a more data-driven approach. We believe that data science is only part of the equation.

Getting value out of data requires building a culture that starts with YOU, is supported by executives, and trickles down to every front-line specialist in your organization.


 
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Who is Driving Your Data Culture Transformation?

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There are several critical roles that are critical to increasing the maturity of your analytics. But the glue that holds it all together is the person we refer to as the Data Champion. You won’t see a job description for a “Data Champion”, but all organizations that have a strong data culture will have at least one, and likely more.

Data Champions are people that spearhead data culture within an organization. Sometimes they are an executive or senior leader, but often-times they’re the boots-on-the-ground people who are simply passionate about promoting and improving data-informed decisions for their organization. They may be part of a business team, data team, or technology team. They may be extroverts or introverts.

What does a Data Champion Look Like?

Data Champions are natural disruptors, communicators, and networkers who can establish, drive, and support a clear data-informed vision. Data Champions are made not born. You will often spot them because they will be seeking to start an internal meetup around a data-related topic or starting a data visualization competition or maybe they will be the person that is at other’s desk showing them how to approach a data problem. They aren’t necessarily the most technical person in the room. But they are most certainly the ones who are building communities, telling stories about the possibilities, and focused on embedding analytics into every corner of the organization.

These Data Champions will be present in an organization whether they have been sought out or not. Organizations with a strong Data Culture though will have more of these Data Champions and their level of empowerment and satisfaction will be higher.

What does a Data Champion do?

Data Champions play a key role in helping translate between the business and their area of the organization to help drive data-usage when making decisions. They engage with business and technology partners to ensure they are smoothly working together. Further, Data Champions will have relationships with other current and future Data Champions including those not within the Chief Data Officer’s direct area.

Data Champions are more than just translators though. They create vision, alignment and empowerment to the teams they support. They build energy and excitement for a data-informed approach. They are skilled at working with business leaders to build trust in the analytics solutions being built. And they constantly communicate the benefits that data can provide, the results that the organization has gotten from analytics investments, and they communicate the vision for the future.

Champions are Critical but not sufficient

Getting the organization moving in the right direction is obviously important. But doing so without executive buy-in will result in frustration, limited results, and lack of funding. Executives have to be part of the equation.

Similarly, moving forward without a technology foundation (quality data, storage platforms, reporting tools), and skilled analysts to dive into that data, will also result in limited results and frustration. The data team and technology must be a critical part of the equation.

Finally, it’s important to not that the best champions are ones that work themselves out of jobs. “Translating” between the business and analyst teams is critical in the early going. But think of the benefits if translating didn’t need to happen, and both teams simply spoke the same language. Reduced friction, reduced effort, and faster/clearer communication would result. The data champion only translates until they can get the teams talking in the same “language”.

Here’s a great video about how Data Translators are critical pieces, but are a stepping stone to the whole organization being data literate.

 
 

This article appears in a series of blog posts about Data Culture, Data Literacy, and why it matters for organizations to think beyond Data Science. If you liked this article, make sure to read the rest of the series:

Five Reasons Why Data Culture is Just as Important as Data Science

The Key Roles of a Data-Informed Organization


Beyond the Data is on a mission

We help high-performing individuals become champions for a more data-driven approach in their organization. We believe that data science is only part of the equation.

Getting value out of data requires building a culture that starts with YOU, is supported by executives, and trickles down to every front-line specialist in your organization.


 
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