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Predictive Analytics Software Prevents Downtime for Manufacturers
June 06, 2018
How AI and Mobile Technology Are Changing Retail
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Three Things We Learned About Big Data Applications From DataWorks Summit Berlin

Stories. Use cases. Best practices. As you explore big data applications within your company, these are the things you want to hear about from peers. They spark your own new ideas and give you insights into what to try next. At the DataWorks Summit Berlin 2018, presenters shared their experiences of the transformative power of big data applications. Here are three key takeaways.

1. The GDPR Is a Journey, Not a Destination

Based on its name, you might think the General Data Protection Regulation (GDPR) is solely about protecting data, but not necessarily. According to Enza Iannopollo, a security and risk analyst for Forrester Research, it’s about much more than that. GDPR affects governance, processes, people, and technology. Many of the companies she worked with viewed May 25 (the date the regulation took effect) as a goal line, as if meeting the regulation requirements would end their focus on compliance. However, she noted that its impact will be felt long past then; becoming compliant is simply the start. Every company—those in Europe and those who work in the European market—now must include data privacy by design and by default in all that they do. She joked that “compliance takes a village.” Staying compliant demands collaboration across your entire organization, and with outside parties as well. This presents a challenge, but the GDPR should not be considered all bad news: Iannopollo’s clients have discovered that a focus on data protection has led to smarter risk mitigation, better customer service, and improved design of big data applications.

2. Break Down Data Silos

Kamélia Benchekroun, data lake squad lead for French automobile manufacturer Renault Group, believes data belongs in the hands of decision-makers. To make that a reality, you have to break down your data silos. Renault Group believes the key to success for digital transformation is creating a data lake. The company achieved this by collecting data from its available sources and compiling it onto a common platform. Renault Group’s team takes an iterative approach so they can learn from mistakes and apply what they learn in the future. The company also sees the advantages of using open source solutions. Its architecture embraces various component types across its IoT and data platforms, making the most of its cloud architecture, data lake, and legacy systems.

3. Data Feeds the World

The global population is growing. Usable farmland is declining. Climate change is altering weather cycles. As food production becomes more complicated, global food and agricultural bank Rabobank uses data to help feed the world more sustainably. The goal is to make farming more productive and profitable while creating less waste. According to two Rabobank representatives, Jeroen Wolffensperger and Martijn Groen, the company achieves this by providing its customers with insights based on data. It struggled with the three Vs of data—variety, velocity, and volume—as it tried to implement a traditional data architecture. So the company started to experiment, using Hadoop open source technology to look for better ways to support its clients. One of the key takeaways from this experimentation was that certain technologies might appear to be the right fit in the moment, but can turn out not to be later on. Thus it’s essential to create architecture that can respond to change. Open source offers more freedom to switch out or even add components as needed.

Every DataWorks Summit session offers something new about how big data applications are used. You never know what insights you might discover to apply at your own organization.

What could you learn at the next DataWorks Summit? Register now for the DataWorks Summit in San Jose.

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