Keeping Up With Data-Fueled Growth |
Posted: September 13, 2017 |
Big data, machine learning and artificial intelligence are impacting businesses in incredible ways and their influence is not going away. For businesses that are trying to catch up or at least maintain their standing in this data-fueled growth environment, which trends will stay and which will go? What innovations will help businesses in the long-term and which provide much-needed relief in the present? Improved Infrastructure Data lives in the cloud, but the cloud lives in data centers where the cost of maintenance impacts consumer prices. Should even one section of a data center experience a loss of power, or another calamity, then entire systems, networks, and websites would go down. The need for backup generators, cooling systems, and rack maintenance is ongoing. Fortunately, these costs are decreasing as innovators turn to green solutions. Current trends in infrastructure improvement include green sourcing for energy and climate control. Since data centers are housed in rural areas, there is access to natural resources and the ability to scale. Privacy Gains in Big Data Maintaining customer trust is an essential element of a successful business. Data breaches send customers running. Less dramatic are the customers who make a silent exit when they find a business' data collection methods intrusive. Businesses can avoid out-migration of customers and improve their reputation by securing their customers' private information and maintaining customer anonymity during customer behavior and marketing research. Though some old-school privacy solutions include tape and disc back-ups which are useful for legacy systems, transferring data to the cloud makes it scalable and easy to access. Cloud-native solutions are highly agile and their security updates are continuously maintained. Technologies like blockchain are highly secure because they store data across multiple servers across the globe. If one data center goes down another server can pick up the slack. Multiple points also make it possible to limit the spread of worms and viruses. Business Intelligence and Artificial Intelligence The advent of big data pushed business intelligence capabilities and heightened its power. But all that data would have stagnated in a data lake had it not been for online analytical processing. Online analytical processing powered BI since its early days and has continued to increase its sophistication in a rapidly changing environment. OLAP programs allows marketers, salespeople, managers and other users to slice and dice data, aggregate data and navigate through detailed data sets. The system is not only maintaining its strategic position within the MarTech landscape, but it is poised to take on new roles, namely in its ability to analyze large collections of historical data which can then be used to power AI. Increased Knowledge and Decreased Specialization Businesses continue their struggle to find talented data scientists. In an effort to fill the data science gap they have hired individuals from within their industry despite their limited data knowledge. Hiring from outside an industry has become a new data trend that is filling the data skills talent gap. Organizations that have hired outside their industry have found that individuals skilled in data science are quick to pick up the industry's missions and strategies. Though they may not have as much industry knowledge as key players, they have what they need to supplement their data knowledge. Emphasizing data knowledge over industry specialization is a hiring practice likely to be seen occurring with greater frequency. These four trends in data innovation are solving numerous problems that the burgeoning field of data science has encountered. Once the growing pains have subsided and these trends become protocol, it will be interesting to see what businesses are able to accomplish with data.
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