2014 will be over in just a few short weeks, but we at Praescient have our eyes set on the future. Data analytics has emerged as a vital tool for industries of all kinds and there is every indication that the practice will evolve tremendously in the coming years. Here are some of the trends and predictions we’re tracking for the upcoming year – and beyond.
Data analytics will become increasingly important to law enforcement missions
Operations centers like this one above can empower police with a range of analytical tools
Praescient has long used data analytics to help law enforcement agencies achieve their critical missions and it looks like the rest of the world is catching up. Police and private sector analysts came together at the recent Analytical Prague 2014 Conference and zeroed in on specific data analysis methodologies that the law enforcement community could lean on to improve their effectiveness. Social media analysis, geographical data collection, and crime prediction emerged as some of the key topics at the conference.
“Based on the data that you have, there is already software being used by some countries that can give you a percentage of how probable, in the next 24 hours or three days or something like that, the specific crime will happen in a specific area,” said Kareol Pelan, an analyst and team leader at the European Union law enforcement agency Europol.
Read more in this article from V3.co.uk: Data analytics playing bigger role in fight against crime
Analysis of shopping behavior will become critical in order to grab Millennials’ purchasing power
The increased purchasing power of Millennials can be tapped with smart analytics
Retail companies have been forced to adapt to a rapidly changing marketplace in the past decade, but data analytics can help these economic drivers navigate big data challenges and achieve business success. Praescient recently published a blog post on the use of analytics in retail and the findings of other organizations echo our conclusions. Online employment aggregator Monster posted their predictions for emerging big data careers for 2015 and the retail sector was identified as a major area of focus. Monster urged retailers to use data analytics to track the purchasing habits of the Millennial demographic in order to create personalized content marketing. This new dynamic will create jobs centered on a combination of digital marketing and analytics skillsets.
The Monster article cited Edgell Knowledge Network’s (EKN) 3rd Annual Analytics in Retail Study which stated that “seventy-one percent of retailers perform basic or no analytics.” EKN Research Director Gaurav Pant described the best potential candidates for these newly created positions as “great at looking at not just internal customer data but [able] to bring together external and public data to drive micro-segmentation and targeting.”
Check out the full article from Monster: Trends to Track: Big Data Analytics, Cyber Security and Personalization Drive 2015 Hiring
Data Analytics will be integrated into mobile applications and emerging technologies
Mobile applications and other technologies generate tons of data which should be harnessed through analytics
Mobile applications have become ubiquitous in our lives – helping connect people, tracking personal health, and changing the way we get around. We are using apps more than ever, with global information and measurement giant Nielsen reporting that in Q4 2013 users spent 30 hours, 15 minutes per month using mobile apps compared to 18 hours, 18 minutes in Q4 2011. A huge of amount of data is generated that could be leveraged into software improvements and market insights through this increased app usage. Companies like Flurry have already identified ways to use the wealth of mobile user data to understand how people use services, optimize conversions, and drill down into demographics. In one prominent example, Flurry’s analyis services helped online retaiker Overstock.com increase in-app purchases by 25%.
Influential technology research and advisory firm Gartner highlighted a push for greater app analytics in their list of strategic technology trends for 2015. They also urged decision makers to consider an analytics approach to making sense of information from related technologies like social media, wearable devices, and the internet of things. “Analytics will become deeply, but invisibly embedded everywhere,” said Gartner Fellow and Vice president David Cearley.
Read the full list of Gartner’s technology trend predictions: Gartner Identifies the Top 10 Strategic Technology Trends for 2015
Decision making will be informed by real-time data collection
This typical supply chain diagram shows how complex these networks can be. Image by Andreas Wieland under CC BY-SA 3.0
As data collection technologies become more advanced, users from many backgrounds gain access to an unprecedented ability to collect massive amounts of information in real-time. This kind of data is highly dynamic and fluid, so much so that an actual human analyst could not possibly hope to track its flow. However, with the proper software in place (such as the GeoVigilance platform from Praescient’s tech partner, TransVoyant) users can derive actionable insight from this ocean of information.
Online technology news site TechRepublic featured real-time data collection in their big data predictions. They identified the retail sector and supply chain management as the two biggest potential avenues for the use of real-time data collection. Smart use of such collection can allow analysts to track consumer buying patterns and “enable managers to respond immediately to supply chain blockages”.
Read TechRepublic’s full list here: Big data trends in 2015 reflect strategic and operational goals
Machine learning fuses with big data
(IBM’s famous Watson computer system is an example of machine learning at work. Image by Wikimedia user Clockready under CC BY-SA 3.0
Machine learning is the ability of computers to improve and behave in new ways without explicit instruction. “In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome” according to educational technology company Coursera. With machine learning, analytic software can better identify useful data while discarding extraneous information.
The fusion of machine learning and big data was called out in Deloitte’s recent 2014 Analytic Trends Report. They described the biggest challenge in getting machine learning to be a useful tool for business is its complexity – data scientists might understand how it works, but CEOs do not. Deloitte suggests that machine learning techniques should be paired with “smart human overseers” in order to bridge this gap. These are “people who specify the types of variables that can enter models, who adjust model parameters to get better fits, and who interpret the content of models for decision-makers.”
Find out more about the future of machine learning in the full report, starting on page 10: Analytics Trends 2014 (And why some may not materialize)
These predictions represent just a few of the exciting new advancements happening in data analytics in the coming years. Check back with the Praescient Ideas Blog for more of our thoughts on the latest analysis trends.
Praescient Analytics is a Veteran-Owned Small Business that delivers training, data integration, platform customization, and embedded analytical services in partnership with leading technology providers. Praescient’s teams of analysts and engineers provide comprehensive solutions to federal and commercial clients engaged in critical defense, law enforcement, intelligence, cyber security, financial, investigative, and legal analytics missions.
Charlotte Stasio is Praescient’s Communications Specialist.