Readers:
Last week I attended the Tableau Conference 2017 in Las Vegas.
Since many people are blogging about the conference (14,000+ attended), I decided to just focus on the four data myths discussed by Adam Selipsky, CEO of Tableau Software, and the great data governance practices overview presented by Sheri Benzelock, VP of Business Analytics Transformation for Honeywell.
Best regards,
Michael
Moment of Silence
Elissa Fink, Tableau’s Chief Marketing Officer, started the keynote by having the audience join the Tableau Executive Team in a moment of silence in honor and memory of the victims of the Las Vegas Shooting that occurred the week before.
The best way to help a community in need is to show up. — Elissa Fink
Data Myths
Adam Selipsky, CEO of Tableau Software, started off his keynote with a very timely and prophetic statement.
Data leads to truth. Without truth, the vacuum is filled with myth. — Adam Selipsky
Adam said there are four key myths about the world of analytics and data.
Myth #1 – AI will replace the analyst
Some have seen AI as nothing more than “parlor tricks.” Many people assume AI will magically scan your data and make the best decisions for you. This is false. AI works on assumptions people have encoded or work on behavior. Both of these can have racial and gender bias. Statements made by technology companies relying on the the results of AI have led to a new field known as Ethical AI.
In actuality, AI will assist and not replace the analyst. We will still use human intuition and creativity to answer the important questions.
Myth #2 – Data is only for the analysts
The growth of the amount of data in the world is exploding. IDC predicts that by the year 2025, the amount of data we have will increase twenty-fold. Not only will there be more data, it will become even more valuable.
The world’s most valuable resource is no longer oil, but data. –The Economist, May 6, 2017.
The analytics and data programs being taught in colleges and universities today have doubled in the past five years. Companies cannot find workers fast enough. There are now 800 million knowledge workers. Excel used to be taught as a University class. Now, it is taught to children in grade school. Tableau’s goal is the same; to introduce Tableau to children in grade school today.
Data is not just for analysts. It is for everyone.
Myth #3 – Data Governance Means No
Old conventional wisdom was we need to slow down the process of providing data. Data is valuable so it needs to be protected. We needed to ensure it was safe to the point where we impeded business partners from having data when they needed it. IT’s ability to deliver data became a bottleneck.
True governance means secure enablement!
Enabling the data unlocks curiosity, insights and agility. When you let the business partners have the data they need, shadow IT dies on its own.
Adam next introduced Sheri Benzelock, VP of Business Analytics Transformation for Honeywell.
Honeywell Data Governance Practices
Sheri mentioned that IT is often afraid that Tableau will introduce the “Wild, Wild West of Data” in their companies. Business Partners will create their own data sets, share them, send them attached to e-mails, etc. Well, surprise! This is already happening using Excel.
Sheri said they focused on two key areas of governance:
What is the Truth?
and
Who Gets to See this Truth?
The first thing Honeywell did was implement a Tableau license process where, when you acquire a Tableau license, you need to post a visualization on their Tableau server. It does not matter what kind of viz you create; the point is for you to know there is a Tableau Server and the business partners understand it is the most appropriate way to share your data visualizations. This helps reduce the risk of inappropriate sharing.
The second thing they did was to implement a sandbox and certified data sites for each of their businesses. This allows the businesses to play, but sharing has to go through a certification process first.
Here are the rules.
First, they have to post the data on a certified data site.
Second, it has to comply with Honeywell Data and Security Standards.
Third, it has to be SOX Compliance (if applicable).
Fourth, it has to be fit for purpose.
This helps reduce risk of ungoverned and unvetted data.
The third thing they did was to promote having dedicated data artisans in each area. These people are responsible for the data in their area, gathering and cleaning, and then publishing it.
This is a huge productivity enabler for Honeywell and saves them millions of dollars.
The last point she made was that the Tableau Server helps them see into their data economy. Who published the data, who is using the data, when was it last used, how popular is that data, etc.? For example, if you have an Excel data file that is being used continuously by 500+ users, then this is a data source you probably want to stand up to be populated and refreshed more systematically.
Their Tableau data deployment went viral. In less than two years, they have 20,000 users.
These data and governance standards helped Honeywell strike the right balance of empowering the business, enabling better visibility into their data, and instilling trust and governance in their data.
Honeywell considers this governance myth busted!
Myth #4 – There can be one, perfect source of the truth
Everyone talks about the Single Source of the Truth database. However, innovation occurs so rapidly today that is is hard to predict the different data sources required and what combinations of these you need. Fifteen years ago, no one ever heard of having your data in the Cloud. Ten years ago, no one ever heard of NoSQL, Who knew five years ago that the Internet of Things (IoT) would gain so much traction so quickly.
We now live in a world of many sources of truth.
As data people, we need to embrace that we may require many different data sources to answer the questions our business partners have.
Ask yourself this question: Can you integrate rapidly with all new data sources you need to answer the questions your business partners have?
If the answer is “No,” then maybe it’s time you take a strong look at Tableau.
Michael Sandberg's Data Visualization Blog 