Big data has for some time become prominent industry-wide in economic decision making. The ability to analyze large amounts of data and find buying patterns, consumer trends and future needs critically affect how businesses respond using predictive analytics. Deep data, however, takes large subsets of information that data scientists will use to narrow the scope of analytical findings based on the relevancy of useful data while understanding what parts to discard. The process focusing on a specific demographic that helps improves the accuracy of determinations.
How Big Data Influences Deep Data
There are few corporations that have the infrastructure to analyze deep data. Most data scientist jobs in London are found in prominent financial institutions. While there are dozens of sites that offer data mining software, few people are properly trained or knowledgeable enough to analyze deep data. There is also issues with housing the data for analysis which is why it is usually larger, technically advanced organizations that have the best return on deep data investments.
What is the potential for new data production? According to Domo, Internet of Things users produce more than 2.5 quintillion bytes of new data every day that is ripe for deep data analysis.
How quickly does information build up? In the last two years, internet users generated ninety percent of the data currently online. User behaviors that contribute to the massive data production include 3.7 billion users online who are practicing repetitive behaviors like Google searches (40,000 per second), mobile accessibility and endless shares, likes and comments on social media platforms. With so much information available, why is there a lack of scientists?
Why the Switch From Big to Deep Data?
No longer are companies worried about getting lots of data. The deep data focus is now on observing deeper by leveraging the web to find the most valuable and lucrative information rather than finding patterns among large data streams. There is also a direct correlation between consumer behavior analysis and deep data collection as they result in actionable insights that result in exponential profits when the right deep data infrastructure is driving it.
How England’s Marketers Rely on Deep Data
English marketers have for decades closed aligned business goals with innovative technology, so it’s not too surprising to see how big data and now deep data, has influenced the markets while meeting the demands of their consumers. The use of data has also been widespread from English-based tech startups to corporate capital ventures all looking to their information grab to determine policy, procedure, daily operations and in-house applications. Investors capitalize heavily by financing data technology as England-based IQ Capital, 83North and Northzone.
Many of their investment funding helps smaller startups build deep data technology that relies heavily on having money to perform research and develop the technology. While it has been difficult to gain access to the needed investment funds, more money is flowing in from all parts of the world from companies all too cognizant of the financial benefit of helping smaller tech companies boost their resources. Investing ultimately develops deep data marketing tools that will allow global access to data software analysis that boosts predictability factor availability.