If you're not measuring your data in petabytes and exabytes, you're not truly in the world of Big Data, at least according to the purists. But increasingly, big data has come to mean the powerful analysis of much more reasonably-sized datasets, and that's where big data becomes a tool for all publishers to consider.
Consider just one of big data's outstanding virtues: its ability to drive innovation by providing
insights from data correlating customer behaviors, patterns and specific requirements -- including data that have traditionally been cast off as odds, ends and by-products of "analyze-able" data.
Big data enables the collection and analysis of offline and online data across touchpoints. Customers are generating more data about their buying behavior, likes and dislikes in more places than ever before. In addition to data stored in widely used CRM applications, untapped and tremendously useful customer satisfaction data exists in tweets, blog posts and other social media
content.
Using big data collection and analysis to capture behavior including preferences, product
selection and spending patterns across thousands of customer interactions enhances the ability to measure and impact customer satisfaction and loyalty in ways never before possible. Operational, financial and customer data across a business can now be integrated and processed efficiently to aid the identification and attribution of revenue drivers, yield actionable insights into product development and to provide deeper levels of customer engagement. Customer level revenue attribution, channel optimization, triggered marketing and marketing can occur more efficiently and reliably than ever before.
Big data is quickly becoming mainstream, and as a consequence, both the tools and associated pricing are becoming accessible to almost everyone. Earlier this week Google launched BigQuery which puts a powerful, straightforward and relatively low cost cloud-based data analysis in the hands of a broader category of companies.
Powered by Google's might, BigQuery's best application is interactive analysis of very large datasets. BigQuery is a SaaS program service that runs on Google infrastructure. It accepts CSV files uploaded from customers via an API. The API uses concurrent compressed streams which allow customers to upload several hundred gigabytes in minutes with analysis that Google estimates is "about 10 times faster than the speed of many corporate data systems." Uploaded data is secure, replicated across multiple data centers and can easily be exported. Data is accessed via group- and user-based permissions using Google accounts.
One advantage of Big Query is its straightforward nature and its ability to keep costs low. Cost is $0.12 GB per month for storage with a 2TB limit and queries are $0.035 per GB with a limit of 1,000 queries per day. Prices are negotiated beyond those limits.
As capital "B" Big Data increasingly becomes small "b" big data, we're going to see even more tools and services that will allow publishers to easily and cheaply find important new insights about their customers and their markets, and that's what makes big data a big opportunity and a big deal.
-- Nancy Ciliberti