The boom in the B2B big data market (from a sub-$100m industry in 2009 to $130bn today) mirrors an enterprise-led scramble to invest in data mining, reminiscent of the California gold rush, accompanied by a similar media buzz.
Although much is still written about the near-magical potential of data analytics for business, this fervour is now giving way to a more serious debate on where the real business value can actually be found. It’s clear that data prospectors are diverging into two camps: the ‘haves’ and the ‘have-not-yets'.

Customer experience is constantly evolving as new products and technology are introduced, but nothing has changed it more than social media. Instead of brands just talking at customers, social media puts the power back in the hands of the customers and gave them a voice to share their experiences. Social customer experience opens huge opportunities for companies to build relationships with their customers, but it also changes the strategy of how brands communicate.

At a community college in upstate New York, 12 cafeteria workers recently learned that they will lose their jobs — and be replaced by self-serve machines. It's an issue that has played out in communities across the country, as robots get better and better at doing jobs — from taking fast food orders to mining coal — that once belonged to humans.

Can I predict churn? Having an email list and being able to predict my churn, is a valuable tool in the hands of any marketer. The idea of predictive analysis and its application in email marketing is not new. The aim is to formulate a more effective strategy by modeling customers’ or consumers' behavior based on historical data, using statistical algorithms and machine learning techniques.

Israeli startup Anodot uses machine learning and time-series data to monitor business metrics and identify anomalies that might take data analysts days to figure out.

Business intelligence comes down to the ability to identify and analyse issues based on a series of variables. While data analysts are adept at identifying issues they have been trained to look for, it is just as important to account for the so-called "unknown unknowns" -- the issues that analysts don't know about or wouldn't think about investigating -- before they escalate into a crisis, said Ra'anana, Israel-headquartered startup Anodot.

Everywhere you look, businesses of all shapes and sizes are looking to transform themselves into digital businesses. This digital transformation tidal wave is often predicated on building a more robust, data-driven organization.

Executives want to make more informed, more strategic decisions, and see analytics technologies, from big data to predictive analytics to good old fashioned business intelligence, as the silver bullet to do so.

Worldwide revenues for big data and business analytics are expected to reach $150.8 billion (€141 billion) in 2017, a rise of 12. 6 per cent on last year, according to a new forecast.

Research firm IDC predicts commercial purchases of related hardware, software and services are expected to maintain a compound annual growth rate (CAGR) of 11.9 per cent through to 2020 when revenues will be more than $210 billion.

The volume and complexity of data requires a systematic organizational effort to derive its maximum benefit.

For years, business intelligence (BI) has been the industry standard for helping leadership gain visibility into business operations and make data-driven decisions. Many companies saw the analysis of their data so vital to their brand that they created roles for ‘Business Intelligence Experts’ to vet the information and prepare it into easily understandable packages.