The act of collecting business data for analysis is a practice as old as business. It wasn’t that long ago when organizations used to scramble to get access to data. Often this data was purchased in raw form from survey companies or business information services organizations. It wasn’t always accurate, it wasn’t always considered inexpensive, but for many organizations these were consistent and reliable sources to capture market data.
My how things have changed…
It’s becoming a daily occurrence. Businesses are overwhelmed by never-before-seen growth rates in data volumes and complexity. And each day thousands of business analyst and IT professionals are locked into their legacy systems and applications hoping to glean insights from these abundant data sources yet are simply unable to meet the demands of the new Big Data paradigm. Fundamentally, a new approach is required or the foundation built on these traditional approaches will crumble beneath them. All the participants in this exercise—executives, business analysts, IT staff, and virtually anyone with iterative analysis requirements—agree they need to find a faster way to access all data types for exploration and informed decision making. The risks for not mastering Big Data analysis are significant; in today’s ever-changing economy the difference between winning and losing market share may be the ability for organizations to harness all their data sources to extract unique insights and trends, which can separate them from the competition…