Regardless of the size of a business, most have one thing in common: using data science to improve business outcomes. Organizations want data to be user-friendly, intuitive, instantaneous, scalable and, most importantly, affordable.

According to Gartner, Inc.’s 2016 Magic Quadrant for Advanced Analytics, “by 2018, more than half of large organizations globally will compete using advanced analytics and proprietary algorithms, causing the disruption of entire industries.”

Delving into everyday use of data science, theCUBE, from the SiliconANGLE Media team, has interviewed some of the biggest “tech athletes” to tap into their expertise on how to achieve the best results.

Create a cultural shift to the democratization of data

Paul Lilford, senior director of technology and market intelligence at Tableau Software, Inc.

Culturally, how do data-driven organizations embrace empowered analytics? I don’t even like the word self-service because I can use a traditional tool make a cherry-picked self-service tool. And that’s very different from a blank screen analytic idea where the user starts with a thought, they start asking questions and they iterate from that. So changing this thinking in organizations is actually the biggest blocker to data driven in general.

Christian [Chabot, Tableau chief executive officer] always said you can’t remove the subject expert from their own data, and as this cultural shift starts to take and organizations evolve to the democratization of data, we will see the big shift. And it’s a big opportunity.

I do believe the existing workforce based on the consumerization of technology has a changed expectation. This is everyone’s expectation. We make data-driven choices today in our personal life, and we don’t even think about them anymore.

Make it easy for citizen data scientists

Lars Bauerle, chief product officer at RapidMiner (Rapid-I, Inc.)

With our new releases, we think about the users themselves and try to think about a broader audience than in the past. This field is so focused on the data scientists, but we are also seeing a budding group of users that are more advanced business analysts — sometimes referred to as citizen data scientists.

We have added three things in the [RapidMiner system] (in this release) to really target them, in fact. The first thing we have done is to overhaul the look and feel of the product to make it look a little more modern. The power is still there for the experienced and powerful data scientist user, but it also may seem easier for the less technical starter type.

The second thing we did was overhaul our learning experience. People can learn the initial steps and use the basic mechanics. We have also added a really great set of tutorials. They start with the basics, how to get your data, how to clean it up and modeling techniques. Then it progresses goes deeper into the more advanced functionality.

The last one goes into more of the validation. How do you know the models you are using are good and how to move them into deployment within the business. This will take users up the ramp to get started more quickly.

Connect the unconnected to gain insight

Dr. Tom Bradicich, VP and GM of hyperscale servers and IoT systems at Hewlett Packard Enterprise Co. (HPE)

Imagine being perpetually connected to things and people. This notion of perpetual connectivity gives great value, and companies are discovering that — even our own.

Perpetually connectivity offers three main values, and I like to call them the three Ms, such as you can monitor and understand the behavior of things and people. The second is you can maintain, and the famous example there is you can upgrade functionality of a car or smart car or cell phone. And the third part is monetize. You can promote an action by a person or a company to sell up, to move to another product in the line, etc.

There is a big move to connect the unconnected because the assets are invested in and they exist. You connect to the Internet of Things (IoT) to gain insight from that thing to do some sort of activity that will help your enterprise. Insights, satisfaction and convergence come together to form predictions that provide value.

Get data into the right hands

Jeff Veis, VP of marketing, Big Data platforms for HPE Software

The one focus that my business is focused on — in fact, I would argue is at the center of — is empowering a data-driven organization. It’s not a new concept, but what’s new is the kind of data we are talking about, the scale of it, the velocity of it and who’s using it.

The big question is that when you are producing the data, does anybody care? Is anybody using it? The monthly report is dead. It’s got to be near real time, and that’s not the exception. That is where the focus seems to be going: Data-driven getting your data into the hands where it can affect the business in a way that’s meaningful.

Secure data, choose encryption sources wisely

Sudeep Venkatesh, VP of solutions architecture, HP Security Voltage  

Our approach is to protect that data at the data level itself but still make it usable to the vast majority. We go straight to the source — the data — and encrypt it.

One of the problems with traditional ways of doing data-level security is that format the data changes, which becomes disruptive to the deployment of the database. You constantly need to encrypt and decrypt data to access it, which leads to a lot of performance problems. What we can do with the HP Voltage site [which delivers innovative encryption and tokenization solutions] is take data elements and encrypt and weaken the format. And in that case, security through encryption has zero impact on performance because you can run queries on protected data because the format is retained and the properties are returned.

One of the things that we have been almost fanatical about is the standardization of the encryption that we bring to the market. We advise all customers that not all encryption is the same. Look for encryption technologies that are open, that have been peer reviewed and most importantly that have gone through the necessary application process as well.

Featured image: Pixabay