Which Technologies Are Set To Make Data Analytics Easier?
In a recent Teradata survey, 96% of business leaders who responded said they consider a big data analytics strategy vital for the future success of their enterprises. Despite this, just six in ten claimed to be satisfied with how they manage their information assets.
With technologies in the sector evolving rapidly, organizations are likely to find their data efforts improve vastly over the next year. We asked nine data professionals what technologies they believe will have the most impact on their ability to analyze the wealth of data now at their disposal.
Mario Trescone, Senior Director of Business Intelligence and Data Analytics at YMCA of the USA
Open source code, greater accessibility to external information (market and consumer data), and the availability of tools that allow you to capture data, connect it to operational information, and then apply predictive analytics and machine learning will have the biggest impact in how the Business Intelligence role operates moving forward. These new technologies and methods will allow for faster, richer insights, enhancing decision-making capabilities, and provide companies of all sizes a way to stay competitive, allowing them to tap into new opportunities than ever before in history.
Calvin Dudek, Head of Data Science Research at the Department for Work & Pensions
One of the real breakthroughs was the release of the open source big data platform, Apache Spark. It’s a big step up from Hadoop and makes large scale machine learning and near real-time analytics doable for everyone. Databricks recently released a community edition which makes it easy for beginners to learn Spark without all the pain of setting up their own Spark cluster, which is ideal for students and people who want to get their hands on it.
All of the data engineering solutions which allow for real-time data processing – Redshift, Spark w/ Hadoop, etc – are transforming the way that we evaluate quantitative data sets to allow for immediate optimization. I think advances in cognitive analytics and natural language processing offer the same opportunities for the qualitative data sets that businesses rely on for creative/strategic decision making.
Mobile has become the new canvas. Our associates and customers spend countless hours with their mobile devices so our team is putting more emphasis in developing self-service apps to answer basic reporting questions.
