Working With Big Data
Every day, the world is creating new data through online purchases, click-throughs, social media interactions, and the many, many other activities performed which, whether we’re aware of it or not, collect and store information about individual behaviors, preferences, and the likes. In its latest prediction, IDC estimated that by 2025 total worldwide digital data would reach 180 zettabytes, a nearly incomprehensible quantity alone, but even more staggering when considering that in 2011 the world created ‘just’ 1.8 zettabytes of information. This big data is used by businesses to personalize customer experiences and amplify engagement, it helps companies make smarter decisions, and with the right tools and analytics in place can improve conversion rates and raise revenue. However, the power of big data is perhaps more talked about than actually implemented and several obstacles prevent organizations from being more data-driven.
Challenges for Big Data Utilization in the Organization
According to SAS, pairing big data with visual analytics can help significantly with the presentation of data, but there are still a number of hurdles to address. The sheer quantity of data produced may seem challenge enough, creating a minefield of data management and data sharing difficulties, but several more subtle components set up their own complications. Data quality is one such component more often considered today as analysts recognize the necessity for both accurate and timely data for the generation of the most valuable insights, and enterprise data management strategies are being implemented more regularly to help address data quality needs.
Another key consideration is the sharing of data, be it within the business across departments or units, or amongst different people. Organizations face a range of dilemmas regarding data sharing such as adequate security of the data, necessary authentication requirements to ensure only those individuals granted access are able to retrieve information, and protection of privacy related to the extremely personal and sensitive nature of some data. Aside from data security and protection, data sharing introduces a subset of challenges regarding whether or not, and how much, data should be shared between businesses. Though competitive stances would suggest the less shared with rivals the better, there is some advantage to be gained from a more open culture of data sharing.
Big data analytics, while a key solution for better data utilization, also produces its own set of challenges, and currently many marketers feel they lack an intuitive way to make sense of all of the available data and generate actionable insights from it. It’s possible that such concerns can be handled not only with the creation of a resilient data culture within organizations, but an analytics culture that promotes quality data collection, information monetization, and broadens the overall understanding of the insights available through data analysis.
Big Data & the Social Sphere
Aside from the data being collected and analyzed in organizations, big data holds a weighty position in the social sphere too. As the internet creates the channels for personal communication between strangers, it’s necessary to contemplate the trust many of us put in the advice and reviews of product and service provided by other users. Networks such as Amazon, eBay, and Airbnb rely on user interaction and information for repeat business, and these networks have developed sophisticated trust and safety mechanisms that may emulate the intentions of Government regulations is many ways, but instead of implementing up-front granting of permission achieve their objectives through the concentrated use of peer review and data. Utilizing social data efficiently opens up an entirely new field for marketers with a different set of challenges and opportunities.
The role of big data and it’s analysis will only grow in the coming years and with it many avenues for business improvement through marketing, customer engagement, decision making, and product development. The right solutions help organizations make the most of their big data and provide the upper hand in today’s highly competitive markets.
Article sponsored by SAS Software and Big Data Forum
By Jennifer Klostermann
Jennifer Klostermann is an experienced writer with a Bachelor of Arts degree majoring in writing and performance arts. She has studied further in both the design and mechanical engineering fields, and worked in a variety of areas including market research, business and IT management, and engineering. An avid technophile, Jen is intrigued by all the latest innovations and trending advances, and is happiest immersed in technology.