We Live in a Data Culture
At the beginning of the last decade, the global market intelligence firm, IDC, estimated that 1.2 zettabytes of new data were created in 2010 and predicted that the amount of new data in 2020 would reach 35 zettabytes. In an interview with MIT Sloan Management Review at the time, data science leader Bruno Aziza talked about how such a data-steeped culture is impacting younger generations’ mindsets:
“I have a 10-year-old daughter. She’s part of the analytics generation. She wants to know something, she pulls out my phone, she talks to it and then she gets the answer. There’s no other way that she can think about life. She doesn’t think that it’s possible that we could be in a situation where we don’t know and have to make a judgment call. But you look at people that are 10 years older than we are, and that’s how they grew up. They grew up thinking most of the time you’re not going to have the information and you’re going to make a judgment call on just about everything.
Most of the time it’s okay to run a business and not know exactly when is the peak hour of your traffic in your store. Well, our kids are not going to go to work like that. They’re going to go to work thinking I don’t need to work 10 hours. I need to work the most two productive hours so I can do a bunch of other things in between. I think they’re looking at the world in a totally different lens than we are, and I think it’s going to be the norm.”
Fast forward to today, where the phenomenon that Aziza is describing is only accelerating. IDC revised their earlier forecast, predicting that 175 zettabytes of new data will be created globally in 2025.
We live in a data culture, one where generations who have grown up in this era know no alternative. They expect nothing less than on-demand access to information that they can analyze and act on themselves. They expect to be able to use data to automate as much manual effort as possible and to get to answers faster.
All Companies Must Be “Big Data Companies”
Teradata is sometimes referred to as a “Big Data company,” since we specialize in helping organizations collect, manage, analyze, and act on data. However, we see yourselves a bit differently — we see our role as facilitating every company’s journey towards becoming a “Big Data company” themselves. We exist to not just provide the enterprise with the right technology to analyze data effectively, but also the services, insights, and support they need to transform their cultures.
In our work with thousands of enterprises, we’ve seen the roadblocks that leaders across industries are encountering along this journey. Below are the four key steps we recommend to any organization looking to transform its culture into one that’s driven by data:
4 Essential Steps to Becoming a Big Data Company
1. Start with Leadership — To Set the Tone
Every leader in your enterprise needs to be making decisions based on data, not just intuition. When your people see that data is the key factor in every strategic decision, they’ll shift their own processes and mindsets.
2. Get Governance and Access Right — To Empower Everyone
If data is essential to every person’s job, no matter what that job is, you’ll need to open up access to everyone at your enterprise. But equal access does not mean equal permissions. Some data will need strict governance but be open to many functions, while other data sets can be stored without strict permission settings but accessed only by a limited set of users. It’s your call.
3. Integrate Data, Engines, and Tools — To Align Around a Single Source of Truth
Creating easy avenues to access will prevent teams feeling a need to create their own data marts and workarounds. This will make it easier to integrate your data into a single source of truth for the company, but you’ll still need to make it easy for users to apply their engines and tools of choice without compromising your data’s integrity.
Teradata Vantage does this by providing the necessary connectivity across data storage environments. We bring different types of analytics engines together into a logically central architecture where they can be called upon when needed. We also extended beyond a SQL Analytic Engine to include Machine Learning and Graph engines. Now all types of programmers can reference the engine and function they need, using whatever tools and languages they prefer, minimizing the impulse to move data to another platform and create siloes.
4. Build in Flexibility — To Support Diverse and Dynamic Needs
The needs of your business today won’t be the same as next quarter, month, or perhaps even tomorrow. That’s why your data architecture needs to support whatever requests various functions may make in response to market and consumer demands. We address this challenge by making it possible for our customers to deploy Vantage in whatever way works for their businesses, whether across cloud, hybrid, or on-premises. Customers have the option to start small and scale Vantage to an enterprise-level mission-critical analytics system if desired. We’re also continuing to expand the as-a-service options for Vantage, each of which will extend the way our customers deploy and manage the platform. With each new as-a-service offering, our aim is to empower customers to focus on answers, not IT.
The Big Data Cultural Urgency
In his interview, Aziza made this prediction: “If you forward 10 years from now, the people that were able to run their business with analytics, they’re going to be either retired or their company is going to die.” To run a business on analytics, however, requires not only the right technology but also the right culture.
A Big Data company succeeds if it empowers people to take full advantage of the analytics tools available to push innovation forward. As Mike Barlow wrote in The Culture of Big Data, “Technology does not exist in a vacuum. In the same way that a plant needs water and nourishment to grow, technology needs people and process to thrive and succeed.” At Teradata, we embrace this thinking in every interaction with our customers, focusing not only on architecture but on creating the best experience for the people working with analytics everyday across the enterprise.
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