In 2016 Big Data Will Explode in Volume and Become Much Faster

January 20, 2016 conduentblogs

Click the image above to read the full study, including detailed methodology.

(From the editor: Xerox commissioned Forrester Consulting to conduct an independent study on how organizations in Europe are using big data and data analytics today. Here, Forrester shares some highlights from the study.)

In 2016, your big data initiatives will expand dramatically, with growing data volumes and a greater demand for faster analysis and predictions. Moreover, cloud, big data, and the “Internet of Things” (IoT) will converge. Some of what you can expect in 2016:

  • The type of data you need to process will become more complex. As the value of data is  understood more by businesses, it will be shared more by partners in 2016.
  • Open-source technologies will turbocharge data processing. NoSQL technologies like the open-source project Apache Spark will grow your business’ ability to get relevant insights from big data queries in 2016.
  • There will be an intense focus on how to manage and protect customer data. In 2016, regulators will issue new data protection and data access laws, such as the update of the EU Data Protection Directive. A Forrester study for Xerox underlines that financial services firms feel challenged by the need to keep up with growing expectations for legal compliance (43 percent) and reporting (42 percent).

Big data helps discover hidden demand and improve customer experience

Innovation and customer experiences make or break businesses. Big data boosts those experiences by making offerings more relevant. Yet, today there is too much data and too few insights. Big data can only ever be a means to an end. The best systems combine people, process, and technology to put big data to work for customers. The implications of this are:

  • The focus will shift from the quantity to quality of the data. The Forrester study for Xerox underlines that more than two thirds (69 percent) of financial services firms are still encountering inaccurate data in their systems – pointing to the need for a comprehensive data quality framework. This shift from data quantity to data quality implies that the data in the future will become more specific and relevant.
  • Business lines will demand more involvement in big data initiatives. Self-service data preparation tools are growing in popularity. User-generated discovery tools reduce time to analyze data and bring efficiencies to the retail and consumer space. The Forrester study for Xerox found that retailers already recognize the need to avoid irrelevant offers, with 60 percent of retail firms looking to develop more tailored customer-focused offers to generate business , 43 percent planning to use big data to build real-time, contextual and targeted marketing offers, and 51 percent aiming to deploy big data for cross-channel marketing.

This Xerox commissioned study, titled “Big Data in Western Europe Today,” was conducted by Forrester Consulting and included a detailed online survey of 300 senior decision makers (C-level and heads of departments) at medium to large organization (those with at least 500 employees) in Belgium, France, Germany, the Netherlands and the UK in January 2015.

Build systems of insight to consistently turn data into action

The key in analytics is  consistently turning data into action. For your big data initiatives to succeed in 2016:

  • Apply big data insights as action items across all departments. Systems of insight are based on multidisciplinary teams. Put these insights to work in software, digital experiences, and everyday work.
  • Make security a central part of your big data projects. Our dependency on IT creates risks that are growing faster than our ability to keep systems secure. Big data can help minimize this risk. The Forrester study for Xerox shows that nearly half (48 percent) of IT and business decision-makers will analyze historical customer data to identify and address potential fraudulent behavior.
  • Design for data warehouse-in-the-cloud and data warehouse-as-a-service-type offerings. Plan for a business environment where traditional business intelligence and big data will begin to blur. Combine open source big data technologies.. Ensure that AI and machine-learning is on your radar screen as a way of automatically collecting, storing and analyzing data.
  • Address your big data skill gaps. As you build a system of insights for Big Data, you’ll realize you do not have all the skills you need in house. Finding  the right partners will be the most critical task you face in  2016.

Subscribe to this blog and receive email updates when we publish a new article.

About the Author


Previous Article
When It Comes to eDiscovery, Think Globally, But Localize Your Approach
When It Comes to eDiscovery, Think Globally, But Localize Your Approach

For years, the environmental movement has encouraged people to take action in their own communities, with t...

Next Article
Outrageous Conclusions in Big Data and Learning
Outrageous Conclusions in Big Data and Learning

Data analytics helps us understand how individuals learn so that we can personalize their learning experience.